Medical Policy: 02.04.57 

Original Effective Date: June 2016 

Reviewed: May 2020 

Revised: December 2019 

 

Notice:

This policy contains information which is clinical in nature. The policy is not medical advice. The information in this policy is used by Wellmark to make determinations whether medical treatment is covered under the terms of a Wellmark member's health benefit plan. Physicians and other health care providers are responsible for medical advice and treatment. If you have specific health care needs, you should consult an appropriate health care professional. If you would like to request an accessible version of this document, please contact customer service at 800-524-9242.

 

Benefit Application:

Benefit determinations are based on the applicable contract language in effect at the time the services were rendered. Exclusions, limitations or exceptions may apply. Benefits may vary based on contract, and individual member benefits must be verified. Wellmark determines medical necessity only if the benefit exists and no contract exclusions are applicable. This medical policy may not apply to FEP. Benefits are determined by the Federal Employee Program.

 

This Medical Policy document describes the status of medical technology at the time the document was developed. Since that time, new technology may have emerged or new medical literature may have been published. This Medical Policy will be reviewed regularly and be updated as scientific and medical literature becomes available.

 

Description:

Prostate cancer is the most commonly diagnosed cancer and the second leading cause of cancer deaths in American men. In 2019, it is estimated that 174,650 men will be diagnosed with prostate cancer. Researchers have estimated that prostate cancer will account for 9.8% of male cancer deaths in 2018.

 

Localized prostate cancers may appear very similar clinically at diagnosis. However, they often exhibit diverse risk of progression that may not be captured by clinical risk categories or prognostic tools based on clinical findings, including PSA titers, Gleason grade, or tumor stage. In studies of conservative management, the risk of localized disease progression based on prostate cancer specific survival rates at 10 years may range from 15% to 20% to perhaps 27% at 20 year follow-up. Among older men (ages ≥ 70 years) with low risk disease, comorbidities typically result in the cause of death; these men will die with prostate cancer present, rather than from the cancer itself. Other very similar low risk tumors may progress unexpectedly rapidly, quickly disseminating and becoming incurable.

 

In the United States, most prostate cancers are clinically localized at diagnosis due in part to the widespread use of PSA testing. Clinicopathologic characteristics are used to stratify patients by risk based on the extent of the primary tumor (T category), nearby lymph node involvement (N category), metastasis (M category), PSA level and Gleason score. The National Comprehensive Cancer Network (NCCN) and American Urological Association (AUA) risk categories for clinically localized prostate cancer are similar, and broadly include very low, low, intermediate (favorable intermediate and unfavorable intermediate), high or very high-risk as follows as well as subcategories within these groups:

  • Very Low: T1c and Grade Group 1 and PSA <10 ng/mL and fewer than 3 prostate biopsy fragments/cores positive, ≤ 50% cancer in each fragment/core and PSA density <0.15 ng/mL/g;
  • Low: T1-T2a and Gleason score ≤ 6 grade group 1 and PSA level ≤ 10 ng/mL;
  • Intermediate: Has no high or very high risk features and has one or more intermediate risk factors (IRF): T2b-T2c or Gleason score 3+4/Gleason grade group 2 or Gleason score 4+3=7/Gleason grade group 3 or PSA level 10-20 ng/mL:
    • Favorable intermediate: 1 IRF and Grade Group 1 or 2 and < 50% biopsy cores positive.
    • Unfavorable intermediate: 2 or 3 IRFs and/or Grade Group 3 and/or ≥ 50% biopsy cores positive;
  • High: T3a or Gleason score 8/Gleason grade 4 or Gleason score 9-10/Gleason grade 5 or PSA level > 20 ng/mL;
  • Very High: T3b-T4 OR Primary Gleason Pattern 5 OR >4 cores with Grade Group 4 or 5.

 

Risk stratification is combined with patient age, life expectancy, and treatment preferences to make initial therapy decisions.

 

Monitoring after radical prostatectomy (RP), all normal prostate tissue and tumor tissue is theoretically removed during RP and the serum level of PSA should be undetectable following RP. Detectable PSA post RP indicates residual prostate tissue and presumably persistent or recurrent disease. PSA is serially measured following RP to detect early disease recurrence. The National Comprehensive Cancer Network (NCCN) recommends monitoring serum PSA every 6 to 12 months for the first 5 years and annually thereafter. Many recurrences following RP can be successfully treated. The American Urological Association (AUA) has recommended a biochemical recurrence be defined as a serum PSA of 0.2 ng/mL or higher, which is confirmed by a second determination with a PSA level of 0.2 ng/mL or higher.

 

Gene expression profile analysis and protein biomarkers have been proposed as a means to risk-stratify patients with prostate cancer to guide treatment decisions. These tests are intended to be used either on prostate needle-biopsy tissue to guide management decisions regarding active surveillance versus therapeutic intervention, or to guide radiotherapy use after radical prostatectomy (RP).

 

Commercially Available Tests

The following are commercially available gene expression profiling (GEP) tests and protein biomarkers:

  • Prolaris® (Myriad Genetics, Salt Lake City, UT) is used to directly measure tumor cell growth characteristics for stratifying the risk of disease progression in prostate cancer patients. The 46 gene expression profiling test which includes 31 cell cycle progression (CCP) genes and 15 housekeeper genes to generate a CCP score. The testing combines traditional risk factors (Gleason score, PSA, clinical stage) with a molecular assessment and the Prolaris score which denotes the level of risk of progression. Patients who are identified has having a low or intermediate risk of disease progression may be candidates for surveillance. Patients who are identified as having a high risk of progression may be candidates for active treatment. Therefore, this testing assists with individualized prostate cancer treatment/management decisions. Prolaris testing can be conducted on either biopsy samples collected for diagnosing prostate cancer or on postsurgical specimens obtained during radical prostatectomy. Adjuvant hormonal therapy and radiation treatment given before tissue sample collection to be tested using Prolaris interferes with the interpretation of tests results. Therefore, patients receiving these treatments before biopsy are not candidates for Prolaris testing.
  • OncotypeDx® Prostate Cancer Assay (Genomic Health, Redwood City, CA) is a prostate biopsy based gene expression profiling (GEP) test used to quantify expression levels of 12 cancer-related and 5 reference genes to generate a Genomic Prostate Score (GPS). In the final analysis, the cell cycle progression (CCP) score or GPS is combined in proprietary algorithms with clinical risk criteria (PSA, Gleason grade, tumor stage) that provides a biologic measure of cancer aggressiveness of individual lesions, and thus inform management decisions (decisions between active surveillance (AS) and immediate treatment).
  • Decipher® Prostate Cancer Assay/ Decipher® Prostate Cancer Classifier (GenomeDx Biosciences, Vancouver, BC) is a tissue based tumor 22-biomarker gene expression profile test is intended to serve as a prognostic marker of cancer tumor aggressiveness in patients newly diagnosed with localized prostate cancer, and to calculate the probability of clinical metastasis within 5 years of radical prostatectomy (RP) surgery. The gene expression classifier is a continuous risk score between 0 and 1, and a categorization of that score into low, average, or high risk at the time of biopsy to determine if a patient can be safely followed with active surveillance or should be considered for immediate treatment, or following radical prostatectomy with associated probabilities of high grade disease, 5 year metastatic risk, and 10 year prostate cancer specific mortality on final pathology.
  • ProMark™ Protein Biomarker Test/ProMark™ Risk Score (Metamark Genetics, Cambridge, MA) is a biopsy based prostate cancer prognostic test that utilizes an automated, quantitative protein based multiplex immunofluorescent in situ  imaging platform to evaluate standard formalin-fixed, paraffin-embedded prostate tissue to differentiate indolent from aggressive prostate cancer. The assay measures 8 protein biomarkers (DERL1, PDSS2, pS6, YBX1, HSPA9, FUS, SMAD4, and CUL2) to generate an algorithmically derived risk score that indicates the aggressiveness of the prostate cancer. The ProMark Score is between 1 and 100, a low ProMark Score is indicative of less aggressive prostate cancer and a high ProMark Score indicates the likelihood of a more aggressive prostate cancer.

 

Initial Management Decision: Active Surveillance and Therapeutic Intervention

In men newly diagnosed with clinically localized prostate cancer, the purpose of gene expression profiling (GEP) and protein biomarker testing is to inform a decision whether to undergo immediate therapy or to forgo immediate therapy and begin active surveillance (AS).

 

The divergent behavior of localized prostate cancers creates uncertainty whether to treat immediately or follow with active surveillance (AS). With active surveillance (AS) the patient will forgo immediate therapy and continue regular monitoring until signs or symptoms of disease progression are evident, at which point curative treatment is instituted. A patient may alternatively choose potentially curative treatment upfront. Surgery (i.e. radical prostatectomy [RP] or external beam radiotherapy [EBRT]) is most commonly used to treat patients with localized prostate cancer. Complications most commonly reported with RP or EBRT and with the greatest variability are incontinence (0%-73%) and other genitourinary toxicities (irritative and obstructive symptoms); hematuria (typically ≤ 5%); gastrointestinal and bowel toxicity, including nausea and loose stools (25%-50%); proctopathy, including rectal pain and bleeding (10%-39%); and erectile dysfunction, including impotence (50%-90%). A 2014 population based retrospective cohort study (Nam et.al.) using administrative hospital data, physician billing codes, and cancer registry data estimated the 5 year cumulative incidence of admission to hospital for a treatment related complication following RP or EBRT to be 22% (95% confidence interval [CI], 21.7% to 22.7%).

 

In the Prostate Testing for Cancer and Treatment (ProtecT) trial (2016 Hamdy et. al.), active surveillance, immediate radical prostatectomy (RP) and immediate external beam radiotherapy (EBRT) for the treatment of clinically localized prostate cancer were compared in 1643 men identified through prostate specific antigen (PSA) testing. About 90% of the participants had PSA level less than 10 ng/mL; two-thirds were Gleason score 6 and 20% were Gleason score 7; all were clinical stage T1c or T2. The mean age was 62 years. At a median of 10 year follow-up, prostate cancer specific survival was high and similar across the 3 treatment groups: 98.8% (95% CI, 97.4% to 99.5%) in active surveillance; 99.0% (95% CI, 97.2% to 99.6%) in the surgery group; and 99.6% (95% CI, 98.4% to 99.9%) in the radiotherapy (RT) group. Surgery and RT were associated with a lower incidence of disease progression and metastases compared with active surveillance. Approximately 55% of men in the active surveillance group had received a radical treatment by the end of follow-up.

 

Prostate Cancer Intervention Versus Observational Trial (PIVOT) (Wilt et. al. 2012 and 2017) randomized 731 men in the United States with localized prostate newly diagnosed cancer to radical prostatectomy (RP) or observation. The patients were 40% low risk, 34% intermediate risk and 21% high risk. Results from PIVOT also concluded that RP did not prolong survival compared with observation through 12 years and 19.5 years of follow-up in the primary analyses including all risk groups. However, among men with intermediate risk tumors, surgery was associated with a 31% relative reduction in all-cause mortality compared with observation (hazard ration [HR], 0.69; 95% CI, 0.49 to 0.98; absolute risk reduction 12.6%).

 

An observational study (2012 Van den Bergh et. al.) comparing sexual function of men with low risk prostate cancer who chose active surveillance with men who received radiation therapy (RT) or radical prostatectomy (RP) found those who chose active surveillance were more often sexually active than similar men who received RP. In a 2011 report (Johanssen et. al.) of quality of life for men in the Scandinavian Prostate Cancer Group Study Number 4 (SPCG-4), after a median follow-up of more than 12 years, distress caused by treatment-related side effects was reported significantly more often by men assigned to RP than by men assigned to watchful waiting.

 

The American Urological Association (AUA), in a joint guideline with ASTRO (American Society of Radiation Oncology) and SUO (Society of Urologic Oncology) (2017), have suggested that physicians recommend active surveillance for most men with low risk localized prostate cancer patients, and may offer definitive treatment (i.e. radical prostatectomy (RP) or radiotherapy (RT)) to select low risk localized prostate cancer patients who may have a high probability of progression on active surveillance. The guidelines also suggest that the physician should recommend radical prostatectomy (RP) or radiotherapy (RT) plus androgen deprivation therapy (ADT) as standard treatment options for patients with intermediate risk localized prostate cancer.

 

Clinical Context and Test Purpose

In men with newly diagnosed clinically localized prostate cancer, the purpose of gene expression profiling (GEP) and protein biomarker testing is to inform a decision whether to undergo immediate therapy or to forgo immediate therapy and begin active surveillance (AS).

 

Patients

The relevant population of interest is individuals with newly diagnosed low or intermediate risk localized prostate cancer, who have not undergone treatment for prostate cancer, and who are deciding between therapeutic intervention and active surveillance (AS).

 

Interventions

Gene expression profiling (GEP) refers to analysis of messenger RNA (mRNA) expression levels of many genes simultaneously in a tumor specimen and protein biomarkers. Two GEP tests and 1 protein biomarker test are intended to stratify biologically prostate cancers diagnosed on prostate needle biopsy: Prolaris and OncotypeDx Prostate Cancer Assay are GEP tests that use archived tumor specimens as the mRNA source, reverse transcriptase polymerase chain reaction amplification, and the TaqMan low density array platform. A protein biomarker test, ProMark is an automated quantitative imaging method to measure protein biomarkers by immunofluorescent staining in defined areas in intact formalin-fixed paraffin-embedded (FFPE) biopsy tissue to provide independent prognostic information to aid in the stratification of patients with prostate cancer to active surveillance or therapy.

 

Comparators

Clinicopathologic risk stratification along with age/life expectancy and patient preference are currently being used to make decisions about prostate cancer management. Clinical characteristics (e.g. stage, biopsy Gleason score, serum PSA level) and demographic characteristics (e.g. age, life expectancy) are combined to classify men according to risk. National Comprehensive Cancer Network (NCCN) and American Urological Association (AUA) have provided treatment recommendations based on risk stratification and life expectancy. The Kattan et. al. (2003) nomogram was developed to predict the risk of indolent cancer in a low-risk population considering active surveillance. The Cancer of the Prostate Risk Assessment (CAPRA) (Cooperberg et. al.) is a pretreatment nomogram that provides risk prediction of outcomes following radical prostatectomy (RP) developed from a cohort of RP patients.

 

Outcomes

Beneficial outcomes resulting from a true test result are prolonged survival, improved quality of life and reduction in unnecessary treatment related adverse events. Harmful outcomes resulting from a false test result are recurrence, metastases or death, and unnecessary treatments. The outcomes of interest are overall survival (OS) (10 year survival), disease specific survival (DSS) (10 year prostate cancer free survival; 10 year prostate cancer death rate; 10 year recurrence rate), quality of life (QOL) and treatment related morbidity (adverse events of radiotherapy or radical prostatectomy).

 

Timing

Ten year outcomes are of interest due to the prolonged natural history of localized prostate cancer.

 

Setting

To select a management strategy for localized prostate cancer clinicians should incorporate shared decision making with their patient by considering cancer severity (risk category), patient values and preferences, life expectancy, pre-treatment general functional and genitourinary symptoms, expected post treatment functional status, and potential for salvage treatment. Effective shared decision making in prostate cancer care requires clinicians to inform patients about immediate and long term morbidity or side effects of proposed treatment of care options.

 

Prolaris

The Prolaris gene expression profile test combines the RNA expression levels of 31 genes involved in cell cycle progression (CCP) and 15 housekeeping genes to generate a Prolaris score (CCP score). This information in conjunction with conventional measures such a Gleason score and prostate specific antigen (PSA) levels, is intended to assist the clinician in predicting the aggressiveness of a patients’ prostate cancer. Many prostate cancers are indolent, meaning they grow slowly and have a low risk of progression, but others are not. Accurately predicting the aggressiveness of prostate cancer and the risk of disease progression allows clinicians and patients to make more informed decisions about treatment options. This section will review Prolaris for initial management decisions in newly diagnosed, localized prostate cancer. Prolaris for the management after radical prostatectomy will be discussed in the following section.

 

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

 

Cuzick et. al. (2012) examined the Prolaris prognostic value for prostate cancer death in a conservatively managed needle biopsy cohort. Cell cycle expression data were read blind to all other data. Patients were identified from 6 cancer registries in Great Britain and were included if they had clinically localized prostate cancer diagnosed by needle biopsy through 1990 through 1996, were younger than 76 years at the time of diagnosis, had a baseline PSA measurement and were conservatively managed. Patients treated with radical prostatectomy or radiation therapy, within the first 6 months after diagnosis or who died or showed evidence of metastatic disease within 6 months of diagnosis were exclude. Men who had hormone therapy before the diagnostic biopsy were also excluded. The original biopsy specimens were retrieved and centrally reviewed by a panel of expert urologic pathologists to confirm the diagnosis, and where necessary to reassign Gleason scores. Of 776 patients diagnosed by needle biopsy and for which a sample was available to review histology, needle biopsies were retrieved for 527 (68%), 442 (84%) of which had adequate material to assay. From the 442 samples, 349 (79%) produced a CCP (cell cycle progression) score and had complete baseline and follow-up information, representing 45% of 776 patients initially identified. The median follow-up time was 11.8 years. A total of 90 deaths from prostate cancer occurred within the 2799 person-years of actual follow-up. In univariate analysis (n=349), the hazard ratio (HR) for death from prostate cancer was 2.02 (95% CI (1.62, 2.53), P<10-9) for a one unit increase in CCP score. The CCP score was only weakly correlated with standard prognostic factors and in a multivariate analysis. CCP score dominated (HR for one unit increase = 1.65, 95% CI (1.31, 2.09), P = 3 x 10-5), with Gleason score (P=5 x 10-4) and prostate specific antigen (PSA) (P=0.017) providing significant additional contributions. The authors concluded, based on exploratory analyses presented here there is evidence that the CCP score may have a non-linear impact on the predicted probability of prostate cancer death. This could either be due to a true non-linear relationship between the CCP score and risk of death from prostate cancer, or lack of proportional hazards in that the CCP is a better predictor of earlier deaths. Although the data set is not large enough to distinguish between these two possibilities, we think that the latter is likely to be at least a partial explanation. The most obvious clinical use of the CCP score is to help identify low risk patients who can be safely managed by surveillance. In this series, we were unable to identify a clinically significant subgroup with a 10 year risk of dying from prostate cancer of less than 5%. However, the CCP score increased the ability to identify men with a less than 10% risk of dying from prostate cancer within 10 years, from 7 to 14%. In addition, for patients with Gleason score of 6, where considerable uncertainty still exists as to appropriate treatment, the predicted 10 year prostate cancer death rate with the addition of the CCP score ranged from 3.5 to 41.0% (compared with 5.1 to 20.9% using clinical parameters only). We believe this is relevant information when considering appropriate care. However, as deaths from prostate cancer are rare in this group, larger cohorts are needed to fully characterize the value of the CCP score in identifying very low risk patients, and clearer relationship may emerge when more patients have been studied.

 

Measures that would suggest improved discriminatory ability (e.g. area under the curve (AUC) or reclassification) compared with an existing nomogram were not reported in Cuzick et. al. (2012). The authors did not provide evidence that the test could correctly reclassify men initially at high risk ot lower risk to avoid overtreatment, or conversely, correctly reclassify those initially at lwo risk to high risk to avoid undertreatment.

 

Cuzick et. al. (2015) examined 3 Great Britain cancer registries from 1990 to 2003 to identify men with prostate cancer who were conservatively managed following needle biopsy, with follow-up through December 2012. The authors stated that the samples did not overlap with Cuziek et. al. (2012). Men were included in this study if they were aged < 76 years at diagnosis and had clinically localized prostate cancer diagnosed by needle biopsy. Patients treated by radical prostatectomy or radiation therapy within 6 months of diagnosis were excluded. Additionally, those with objective evidence of metastatic disease (by bone scan, X-ray, radiograph, CT scan, MRI, bone biopsy, lymph node biopsy, pelvic lymph node dissection) or clinical indications of metastatic disease (including pathological fracture, soft tissue metastases, spinal compression or bone pain), or a PSA measurement > 100 ng ml-1 at or within 6 months of diagnosis were also excluded. Men who had hormone therapy prior ot the diagnostic biopsy were also excluded because of the influence of hormone treatment on interpreting Gleason score. Also, excluded were men who died within 6 months of diagnosis or had < 6 months of follow-up. Original histological specimens from the diagnostic procedure were requested and centrally reviewed by panel of urological pathologists to confirm diagnosis and reassign Gleason scores using a contemporary and consistent interpretation of the Gleason scoring system. The full cohort comprised of 989 men. A total of 145 (15%) samples had inadequate tumor and a further 83 (8%) failed CCP score quality assurance. For those with adequate amounts of tumor visible on the H&E (n=844), 90% produced a CCP score. One patient lacked information about extent of disease, two patients had missing baseline PSA information and a further 173 were missing clinical stage, leaving 585 with a CCP score and all clinical variables for analysis in the primary analysis cohort. In univariate analysis, the CCP score hazard ratio (HR) was 2.08 (95% CI (1.76, 2.46), P < 10-13) for one unit change of the score. In multivariate analysis including CAPRA (Cancer of the Prostate Risk Assessment), the CCP score hazard ratio was 1.76 (95% CI (1.44, 2.14), P < 10-6). The predefined CCR (clinical cell cycle risk) score was highly predictive, hazard ratio 2.17 (95% CI (1.83, 2.57), χ2=89.0, P < 10-20) and captured virtually all available prognostic information. The authors concluded, these results confirm our previous findings for the prognostic value of the CCP score measured in diagnostic needle biopsies. For conservatively managed patients, the CCP score was highly prognostic for death from prostate cancer and provided important independent information that could not be obtained from clinical data. In addition, this study provides a fully independent validation in a new data set of a predefined CCR score as a linear combination of the CCP score and clinical variables (combined in the CAPRA score), which almost completely accounted for all molecular and clinical prognostic information. Further work is needed to determine if DNA based or other markers can add useful information to our combined score.

 

In 2016, Sommariva et. al. performed a systematic review to assess the evidence on the value of the CCP (cell cycle progression) instrument in prostate cancer treatment by reviewing current publications and integrating the results via a meta-analysis supported by Myriad Genetics were reported. Published and unpublished studies of prognostic validity or clinical utility of CCP testing were eligible for inclusion. The results show that use of the CCP score is better than existing assessments at elucidating the aggressive potential of prostate cancer in an individual. The pooled hazard ratio for biochemical recurrence (BCR) per 1-unit increase in the CCP score was 1.88 in a univariate model and 1.63 in a multivariate model. Four studies showed that CCP testing can impact the decisions of physicians regarding treatment, and potentially lead to a decrease in surgical interventions for low-risk patients. The authors concluded, this review offers a comprehensive review of existing evidence on CCP testing and provides clinicians, patients and policy makers with a strong summary measure of its prognostic validity and clinical utility. It will be important to develop economic studies to measure the impact of such technology on health care systems.

 

Lin et. al. (2018), validated a clinical cell cycle risk (CCR) cutoff of 0.8 using a subset of 585 conservatively managed men from the Cuzick (2015) cohort. Of the 585 men, 60 had CCR scores of 0.8 or less. Among the 284 men who were at low or intermediate risk by NCCN criteria, 59 had CCR scores of 0.8 or less. The text reports that the estimated 10-year prostate cancer mortality risk was 2.7% for men with CCR scores below the threshold and 3.3% (95% CI, 1.9% to 5.7%) at the threshold in the full cohort, and 2.3% below the threshold and 2.9% (95% CI, 1.3% to 6.7%) at the threshold in the cohort that excluded high-risk men. However, the Kaplan-Meier curves show an estimated prostate cancer morality at 10 years of 0% for men with CCR of 0.8 or less in both cohorts. The Kaplan-Meier curve estimated prostate cancer mortality at 10 years for men with CCR greater than 0.8 was 20% in the full cohort and 9% in the cohort excluding high-risk men.

 

Lin et. al. (2018) also reported reclassification of men using the clinical cell cycle risk (CCR) score threshold (0.8) in a group of 19,215 consecutive patients whose biopsies were sent for Prolaris testing between 2013 and 2016. According to the table of clinicopathologic features of patients, 14,685 of the 19,215 men had low or favorable intermediate risk by NCCN risk classification. However, the authors said that only 8,177 of the 19,215 men met NCCN criteria for active surveillance based on low/favorable intermediate-risk clinicopathologic features. It is not clear why fewer men were categorized as meeting NCCN low/favorable intermediate criteria for the purposes of demonstrating reclassification and, therefore, it is not clear how many of the 14,685 men at low or intermediate risk by NCCN criteria would have been reclassified using the CCR threshold.

 

Clinically Useful

A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

 

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.

 

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

 

In 2014, Crawford et. al. completed a prospective study evaluating the impact of the cell cycle progression (CCP) test Prolaris on physician treatment recommendations for prostate cancer.  Physicians ordering the CCP test in clinical practice completed surveys regarding treatment recommendations before and after they received and discussed the test results with patients. Clinicians also rated the influence of the test result on treatment decisions. Treatment selections were confirmed via third-party audit of patient charts following final survey responses. Overall, 65% of cases showed a change between intended treatment pre and post-CCP test reporting. Pre-CCP testing, 164 of 305 cases received a recommendation for interventional treatment. Post-CCP test, interventional therapy was recommended for 103 of these cases, a reduction of 37.2%. Conversely, 141 of 305 cases were recommended pre-CCP testing for non-interventional treatment; 108 of these remained with non-interventional treatment while 33 shifted to interventional options, a 23.4% increase. There was a 49.5% reduction in surgical interventions and a 29.6% reduction in radiation treatment. A third-party audit identified 80.2% concordance between the post-CCP testing treatment recommendation and actual treatment. Re-assignment to intervention or non-intervention generally correlated with the result of the CCP report. Study limitations included physician selection of patients for testing, no evaluation of patient input in therapeutic choice, and other potential treatment decision factors not queried by the survey. The authors concluded based on responses of ordering physicians, the CCP report adds meaningful new information to risk assessment for localized prostate cancer patients. Test results led to changes in treatment with reductions and increases in interventional treatment that were directionally aligned with prostate cancer risk specified by the test.

 

In 2016, Shore et. al. reported on the results from PROCEDE – 1000, a large, prospective registry designed to evaluate the impact of the cell cycle progression test on shared treatment decision making for patients with newly diagnosed with prostate cancer. Untreated patients with newly diagnosed prostate adenocarcinoma were enrolled in the study and the cell cycle progression test was performed on the initial prostate biopsy tissue. A set of 4 sequential surveys tracked changes relative to initial therapy recommendations (before cell cycle progression) based on clinicopathological parameters following physician review of the cell cycle progression test result, physician/patient review of the cell cycle progression test results and a minimum of 3 months of clinical follow-up (actual treatment). Of the 1,596 patients enrolled in this registry 1,206 were eligible for analysis. There was a significant reduction in the treatment burden recorded at each successive evaluation (p <0.0001), with the mean number of treatments per patient decreasing from 1.72 before the cell cycle progression test to 1.16 in actual follow-up. The cell cycle progression test caused a change in actual treatment in 47.8% of patients. Of these changes 72.1% were reductions and 26.9% were increases in treatment. For each clinical risk category there was a significant change in treatment modality (intervention vs nonintervention) before versus after cell cycle progression testing (p=0.0002).

 

In 2017, Health Quality Ontario reported on a health technology assessment including a systematic review of the literature on the clinical utility, economic impact and patients’ perceptions of the value of Prolaris CCP (cell cycle progression) test in low and intermediate risk localized prostate cancer. The authors conducted a systematic review of the clinical and economic evidence of the CCP test in low and intermediate risk, localized prostate cancer. Medical and health economic databases were searched from 2010 to June or July 2016. The critical appraisal of the clinical evidence included risk of bias and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group criteria. We also analyzed the potential budget impact of adding the CCP test into current practice, from the perspective of the Ontario Ministry of Health and Long-Term Care. Qualitative interviews were conducted with men with prostate cancer, on the factors that influenced their treatment decision making. For the review of clinical effectiveness 3,021 citations were screened, and two before and after studies met inclusion criteria. In one study, the results of the CCP test appeared to change the treatment plan (from initial to final plan) in 64.9% of cases overall (GRADE rating of the quality of evidence: Very low). In the other study, the CCP test changed the treatment received in nearly half of cases overall, compared with the initial plan (GRADE: Very low). No evidence was available on clinical outcomes of patients who treatment was informed by CCP results. For the review of cost effectiveness, 100 citations were identified and screened. No studies met the inclusion criteria. In the economic evaluation, it was estimated that publicly funding the CCP test would result in a total net budget impact of $41.3 million in the first 5 years, mostly due to the cost of the CCP test. In the model, the relatively cost savings ($7.3 million) due to treatment change (increased use of active surveillance and decreasd use of interventional treatment) was not large enough to offset the high cost of the test. Patients viewed the test as potentially helpful but, due to the complexity of treatment decision making, the reviewers were unsure the test would ultimately change treatment choices. The authors concluded, that they found no evidence to demonstrate the impact of the Prolaris CCP test on patient important clinical outcomes. The limited evidence available shows that the test appears to provide information that, when considered in addition to the clinical risk stratification, may change the treatment plan or actual treatment for some low and intermediate risk prostate cancer patients. As a result, there is insufficient data to inform the cost-effectiveness of the CCP test.

 

Summary

Based on review of the peer reviewed medical literature the available evidence shows that the test appears to provide information that when considered in addition to the clinical risk stratification allows physicians to determine which patients with early prostate cancer are candidates for active surveillance or observation and are more likely to have a good outcome without needing to receive definitive treatment.

 

OncotypeDx Prostate

The OncotypeDx Prostate Assay includes 5 reference genes and 12 cancer genes that represent 4 molecular pathways of prostate cancer oncogenesis: androgen receptor, cellular organization, stromal response, and proliferation. The assay results are combined to produce a GPS (Genomic Prostate Score), which ranges from 0 to 100. Higher GPS scores indicated more risk.

 

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

 

Klein et. al. (2014) reported on a clinical validation study to identify and validate a biopsy based gene expression signature that predicts clinical recurrence, prostate cancer (PCa) death and adverse pathology. Gene expression was quantified by reverse transcription-polymerase chain reaction for three studies-a discovery prostatectomy study (n=441), a biopsy study (n=167), and a prospectively designed, independent clinical validation study (n=395)-testing retrospectively collected needle biopsies from contemporary (1997-2011) patients with low to intermediate clinical risk who were candidates for active surveillance (AS). The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatectomy. Cox proportional hazards regression models were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profiles were used together with clinical and pathologic characteristics to evaluate clinical utility. Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multi-focality, and 198 (27%) were predictive of aggressive disease after adjustment for prostate-specific antigen, Gleason score, and clinical stage. Further analysis identified 17 genes representing multiple biological pathways that were combined into the GPS algorithm. In the validation study, GPS predicted high-grade (odds ratio [OR] per 20 GPS units: 2.3; 95% confidence interval [CI], 1.5-3.7; p<0.001) and high-stage (OR per 20 GPS units: 1.9; 95% CI, 1.3-3.0; p=0.003) at surgical pathology. GPS predicted high-grade and/or high-stage disease after controlling for established clinical factors (p<0.005) such as an OR of 2.1 (95% CI, 1.4-3.2) when adjusting for Cancer of the Prostate Risk Assessment (CAPRA) score. A limitation of the validation study was the inclusion of men with low-volume intermediate-risk PCa (Gleason score 3+4), for whom some providers would not consider AS. The actual number of patients correctly or incorrectly reclassified across all 3 categories cannot be ascertained from the data provided. The results suggest that the combination of GPS plus clinical criteria can reclassify patients on an individual basis within established clinical risk categories. However, whether these findings support a conclusion that the GPS could predict the disease-specific survival based solely on the level of pathology in a biopsy specimen is unclear. Moreover, extrapolation of this evidence to a true active surveillance population, for which the majority in the study would be otherwise eligible, is difficult because all patients had elective RP within 6 months of diagnostic biopsy. Also, the data suggests the GPS can reclassify patient risk of recurrence based on a specimen obtained at biopsy. However, the findings do not necessarily reflect a clinical scenario of predicting disease progression in untreated patients under active surveillance.

 

A retrospective cohort study by Cullen et.al. (2015) included biopsies from 431 men treated for National Comprehensive Cancer Network (NCCN) very low, low, or intermediate risk prostate cancer (PCa) between 1990 and 2011 at two U.S. military medical centers and were tested to validate the association between GPS (Genomic Prostate Score) and biochemical recurrence (BCR) and to confirm the association with AP (adverse pathology). Metastatic recurrence (MR) was also evaluated. Cox proportional hazards models were used for BCR and MR, and logistic regression was used for AP. Central pathology review was performed by one uropatholgist. AP was defined as primary Gleason pattern 4 or any pattern 5 and/or pT3 disease. Selected patients were older (61.0 years vs 59.7 years, p=0.013) and had both higher Gleason scores (p<0.001) and NCCN risk classification (29.8% vs 32.9% intermediate, p=0.035). Median follow-up was 5.2 years and biochemical recurrence (BCR) occurred in 62 (15.4%). GPS results (scale: 0-100) were obtained in 402 cases (93%); 62 men (15%) experienced BCR, 5 developed metastases, and 163 had AP.

 

Estimates of 5 Year Biochemical Recurrence with OncotypeDx
Genomic Prostate Score (GPS)N5 year Biochemical Recurrence (BCR) (95% Confidence Interval), %
10 Not reported 5.1 (2.7 to 9.1)
20 Not reported 8.5 (5.8 to 13.4)
30 Not reported 14.2 (10.2 to 19.0)
40 Not reported 22.9 (18.0 to 28.8)
50 Not reported 35.2 (27.1 to 45.4)
60 Not reported 53.8 (38.6 to 65.6)
70 Not reported 71.8 (50.6 to 89.3)
80 Not reported 87.3 (64.2 to 98.0)

 

Adverse pathology was noted in 163 (34% of men). In an analysis adjusted for baseline characteristics, the GPS was associated with BCR-free survival and adverse pathology following radical prostatectomy (RP), see the below table:

 

Univariate and Multivariate Association Between GPS and Outcomes
Outcome N Univariate Ratio (95% confidence interval) Multivariate Ratio (95% confidence interval)
Biochemical Recurrence (BCR) 392 hazard ratio = 2.9 (2.0 to 4.2) 2.7 (1.8 to 3.8)
Adverse Pathology (AP) 392 hazard ratio = 3.2 (2.1 to 5.0) hazard ratio = 2.7 (1.8 to 4.4)

 

The Genomic Prostate Score (GPS) improved the C statistic (concordance statistic) for adverse pathology over NCCN risk alone from 0.63 to 0.72. Comparisons with other predictors such as CAPRA or Gleason score alone were not reported. Study implications were limited by the low proportion of eligible men in the analysis and difference between excluded and included men.

 

Whalen et. al. (2016) prospectively evaluated the correlation of Genomic Prostate Score (GPS) with final pathology at radical prostatectomy (RP) in a clinical practice setting. Eligible men were 50 years of age and older with more than 10 years life expectancy, PSA levels of 20 ng/mL or less, stage cT1c-cT2c newly diagnosed, untreated prostate cancer, and who met NCCN classifications as very low risk, low risk, or low-intermediate risk. Men were enrolled from May 2013 to August 2014 at an academic medical center. Genomic Health reclassified patients’ cancers as “less favorable,” “consistent with,” or “more favorable” than what would have been predicted by their NCCN risk group. The primary outcome was adverse pathology at radical prostatectomy (RP) defined as any pT3 stage and primary Gleason grade 4 or any pattern 5. ROC (receiver operating characteristics) analyses was used to determine the optimal cutoff point of likelihood of favorable pathology for each NCCN risk group. A total of 95 patients were enrolled and 50 patients (53%) underwent radical prostatectomy. Adverse pathology was found in 21 patients (42%), grouped as very low risk 0%, low risk 32.4% and low volume intermediate risk 71.4%. Among those with low risk disease, ROC analysis determined that a likelihood of favorable pathology cutoff of 76% or greater performed the best, correctly classifying 91.2% of patients with a sensitivity of 95.7% and specificity of 81.8% and AUC (area under the curve) 0.95. For intermediate risk patients the optimal likelihood of favorable pathology cutoff was 68% or greater, with 92.3% correct, sensitivity 75%, specificity 100% and AUC 0.95.

 

In 2018, Van Den Eeden et. al. completed a retrospective study using a stratified cohort sampling design performed in a cohort of men with localized prostate cancer treated with radical prostatectomy (RP). RNA from archival diagnostic biopsies was assayed to generate GPS (Genomic Prostate Score) results. They assessed the association between GPS and time to metastasis and PCD in prespecified uni- and multivariable statistical analyses, based on Cox proportional hazard models accounting for sampling weights. The final study population consisted of 279 men with low, intermediate, and high-risk prostate cancer (PCa) between 1995 and 2010 (median follow-up 9.8 yr), and included 64 PCD (prostate cancer death) and 79 metastases. Valid GPS results were obtained for 259 (93%). In univariable analysis, GPS was strongly associated with time to PCD, hazard ratio (HR)/20 GPS units=3.23 (95% confidence interval [CI] 1.84-5.65; p<0.001), and time to metastasis, HR/20 units=2.75 (95% CI 1.63-4.63; p<0.001). The association between GPS and both end points remained significant after adjusting for National Comprehensive Cancer Network, American Urological Association, and Cancer of the Prostate Risk Assessment (CAPRA) risks (p<0.001). No patient with low- or intermediate-risk disease and a GPS of<20 developed metastases or PCD (n=31). In receiver operating characteristic analysis of PCD at 10 yr, GPS improved the c-statistic from 0.78 (CAPRA alone) to 0.84 (GPS+CAPRA; p<0.001). A limitation of the study was that patients were treated during an era when definitive treatment was standard of care with little adoption of active surveillance. The authors concluded GPS is a strong independent predictor of long-term outcomes in clinically localized PCa in men treated with RP and may improve risk stratification for men with newly diagnosed disease.

 

Salmasi et.al.(2018), investigated the ability of the prostate score assay to predict adverse pathology findings in the setting of magnetic resonance imaging guided prostate biopsy. They identified men diagnosed with NCCN® (National Comprehensive Cancer Network®) very low, low or intermediate risk prostate cancer who underwent simultaneous multiparametric magnetic resonance imaging fusion targeted and systematic prostate biopsy with subsequent radical prostatectomy within 6 months. Prostate score assay testing was performed on biopsy tissue with the highest Gleason score. The primary outcome of the study was adverse pathology findings, defined as Gleason score 4 + 3 or greater disease and/or pT3+ at radical prostatectomy. Independent predictors of adverse pathology findings were determined in a multivariable model to adjust for clinical parameters. A total of 134 men were eligible for primary analysis. On univariable analysis the UCLA score, magnetic resonance imaging, prostate score assay results and biopsy Gleason score were significant predictors of adverse pathology findings. After multivariable adjustment prostate score assay values remained a significant predictor of adverse pathology results (prostate score assay per 20 U OR 3.28, 95% CI 1.74-6.62, p <0.001). A wide and overlapping distribution of prostate score assay results was seen across PI-RADS® (Prostate Imaging Reporting and Data System) version 2 scores. The authors concluded, the prostate score assay result is an independent predictor of adverse pathology findings in patients who were diagnosed with very low, low or intermediate risk prostate cancer in the setting of multiparametric magnetic resonance imaging fusion prostate biopsy. This assay can be useful as an independent technology or an adjunct technology to multiparametric magnetic resonance imaging to individualize risk stratification of low and intermediate risk prostate cancer.

 

Systematic Reviews

In 2016, Brand et. al. combined the Klein (2014) and Cullen (2015) studies using a patient specific meta-analysis (MA). The patient specific meta-analysis (MA) was performed on data from these 2 studies (732 patients) using the Genomic Prostate Score (GPS; scale 0 to 100) together with the Cancer of the Prostate Risk Assessment (CAPRA) score or National Comprehensive Cancer Network (NCCN) risk groups as predictors of the likelihood of favorable pathology (LFP). Risk profile curves associating GPS with LFP by CAPRA score and NCCN risk group were generated. Decision curves and receiver operating characteristics (ROC) curves were calculated using patient specific MA risk estimates. A model utilizing GPS and CAPRA provided the most risk discrimination. The area under the receiver operating characteristic curve (AUC) improved from 0.68 to 0.73 by adding the GPS to CAPRA score. The AUC improved from 0.64 to 0.70 by adding the GPS to the NCCN risk group. The improvements were reported to be significant but the confidence intervals (CIs) were not provided.

 

Clinically Useful

A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

 

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.

 

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

 

Decision impact studies have assessed the potential impact of OncotypeDx Prostate on physicians’ treatment decisions. Decision-impact studies have also indicated that men classified as low risk by guidelines criteria, and thus meeting guidelines criteria for active surveillance, are more likely to receive active surveillance if they are tested with the Oncotype DX Prostate test. These arguments would suggest that the test may be a useful behavioral modifier.

 

In 2014, Klein et. al. identified and validate a biopsy-based gene expression signature that predicts clinical recurrence, prostate cancer (PCa) death, and adverse pathology. Gene expression was quantified by reverse transcription-polymerase chain reaction for three studies-a discovery prostatectomy study (n=441), a biopsy study (n=167), and a prospectively designed, independent clinical validation study (n=395) testing retrospectively collected needle biopsies from contemporary (1997-2011) patients with low to intermediate clinical risk who were candidates for active surveillance (AS). The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatectomy. Cox proportional hazards regression models were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profiles were used together with clinical and pathologic characteristics to evaluate clinical utility. Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were predictive of aggressive disease after adjustment for prostate-specific antigen, Gleason score, and clinical stage. Further analysis identified 17 genes representing multiple biological pathways that were combined into the GPS algorithm. In the validation study, GPS predicted high-grade (odds ratio [OR] per 20 GPS units: 2.3; 95% confidence interval [CI], 1.5-3.7; p<0.001) and high-stage (OR per 20 GPS units: 1.9; 95% CI, 1.3-3.0; p=0.003) at surgical pathology. GPS predicted high-grade and/or high-stage disease after controlling for established clinical factors (p<0.005) such as an OR of 2.1 (95% CI, 1.4-3.2) when adjusting for Cancer of the Prostate Risk Assessment score. A limitation of the validation study was the inclusion of men with low-volume intermediate-risk PCa (Gleason score 3+4), for whom some providers would not consider AS. The authors concluded, Genes representing multiple biological pathways discriminate PCa aggressiveness in biopsy tissue despite tumor heterogeneity, multifocality, and limited sampling at time of biopsy. The biopsy-based 17-gene GPS improves prediction of the presence or absence of adverse pathology and may help men with PCa make more informed decisions between AS and immediate treatment.

 

Prostate cancer (PCa) is often present in multiple locations within the prostate and has variable characteristics. We identified genes with expression associated with aggressive PCa to develop a biopsy-based, multigene signature, the Genomic Prostate Score (GPS). GPS was validated for its ability to predict men who have high-grade or high-stage PCa at diagnosis and may help men diagnosed with PCa decide between active surveillance and immediate definitive treatment.

 

Badani et. al. (2015) prospectively evaluated the decision impact of obtaining a Genomic Prostate Score (GPS) in men with National Comprehensive Cancer Network (NCCN) defined very low, low and low – intermediate risk prostate cancer. Following test results, recommendations for active surveillance increased from 41% to 51%. Actual treatments received and accuracy of predicted outcomes were not assessed, thereby limiting implications of the study. The study was supported by Genomic Health and all authors reported financial or other relationships with the funder.

 

Summary

The evidence from 3 studies on clinical validity (Klein et. al. 2014; Cullen et. al. 2015; Whalen et. al. 2016) for OncotypeDx Prostate has suggested the Genomic Prostate Score (GPS) can reclassify a patient’s risk of recurrence or risk of adverse pathology at radical prostatectomy (RP) based on a biopsy specimen. Also a decision curve analysis suggested the potential for the combined Genomic Prostate Score (GPS) and CAPRA (Cancer of the Prostate Risk Assessment) score data to help patients make decisions based on relative risks associated with immediate treatment or deferred treatment (i.e. active surveillance). This would reflect clinical utility of the test.

 

ProMark Protein Biomarker Test

The ProMark Protein Biomarker test includes 8 protein biomarkers (DERL1, PDSS2, pS6, YBX1, HSPA9, FUS, SMAD4, and CUL2) that predict prostate pathology aggressiveness. The ProMark Score is between 1 and 100, a low ProMark Score is indicative of less aggressive prostate cancer and a high ProMark Score indicates the likelihood of a more aggressive prostate cancer.

 

In 2015, Roth et. al. conducted a study to evaluate the cost effectiveness of using the 8-protein prostate cancer prognostic assay to inform treatment decisions compared with usual care. They developed a simulation model to estimate quality adjusted life year (QALY) and cost outcomes for the 8-protein assay and usual care strategies. Risk classification outcomes, treatment distributions, costs, health state utilities, and mortality rates were derived from the assay’s validation study and the peer reviewed literature. Outcomes included incremental QALYs, costs, and cost effectiveness ratios. They conducted one-way and probabilistic sensitivity analyses to evaluate the most influential inputs and to explore joint uncertainty in outcomes, respectively. The 8-protein assay strategy resulted in 0.04 more QALY and $700 less in costs compared with usual care (and thus was “dominant”). The cost effectiveness of the assay strategy was most sensitive to the assay cost, the active surveillance health state utility, and the proportion of low risk patients receiving active surveillance versus treatment in usual care. In the probabilistic sensitivity analyses, the assays strategy decreased cost and increased QALYs in 86.9% and 58.3% of simulations, respectively. The authors concluded, assuming that ongoing prospective studies support the results of retrospective validation studies, the 8-protein prognostic assay strategy for prostate cancer is likely to be cost effective alternative to usual guideline- based care in biopsy Gleason 3+3 and 3+4 early stage prostate cancer.

 

Implications for practice: Prostate cancer prognostic assays such as the 8-protein assay can provided information about disease aggressiveness that may improve decisions about use of active surveillance versus invasive treatment in Gleason 3 + 3 and 3 + 4 disease. This study, the first cost-effectiveness evaluation of this type of assay reported in the peer-reviewed literature, found that the assay strategy is expected to result in increased quality-adjusted survival and decreased cost compared with usual care. The findings demonstrate the potential for prognostic assays to be dominant strategies in this clinical setting, in which many patients currently receive invasive treatment but derive limited clinical benefit.

 

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

 

In 2014, Shipitsin et. al. developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy sampling error, a core from a high and low Gleason area from each patient sample was used to generate a high or low tumor microarray retrospectively. Using a quantitative proteomics approach, they identified from 160 candidates 12 biomakers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high and low Gleason areas. Conversely, a previously reported lethal outcome predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sample error. The authors concluded, our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

 

Blume-Jensen et. al. (2015) reported on a study of 381 biopsies matched to prostatectomy used to develop an 8-biomarker proteomic assay to predict prostate final pathology on prostatectomy specimen using risk scores. A second blinded study of 276 cases validated this assay’s ability to distinguish “favorable” versus “non-favorable” pathology independently and relative to current risk classification systems National Comprehensive Cancer Network (NCCN and D’Amico). A favorable biomarker risk score of ≤0.33, and a non-favorable risk score of >0.80 (possible range between 0 and 1) were defined on "false-negative" and "false-positive" rates of 10% and 5%, respectively. Results from the study showed that, at a risk score of less than or equal to 0.33, predictive values for favorable pathology in very low-risk and low-risk NCCN and low-risk D'Amico groups were 95%, 81.5%, and 87.2%, respectively, higher than for these current risk classification groups themselves (80.3%, 63.8%, and 70.6%, respectively). The predictive value for non-favorable pathology was 76.9% at biomarker risk scores >0.8 across all risk groups. Increased biomarker risk scores correlated with decreased frequency of favorable cases across all risk groups. The validation study met its two co-primary endpoints, separating favorable from non-favorable pathology (AUC, 0.68; P < 0.0001; OR, 20.9) and GS-6 versus non-GS-6 pathology (AUC, 0.65; P < 0.0001; OR, 12.95). The authors concluded this study supports further evaluation of this biopsy based prognostic biomarkers assay for personalized prognostication of prostate cancer and its impact on therapeutic choice. The ability to provide differential information for the individual patient relative to current risk stratification systems, in which prognostic values are more limited, makes it a potentially useful addition in practice to improve accuracy of clinical decision.

 

Clinically Useful

A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

 

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.

 

No published studies on the clinical utility of ProMark Protein Biomarker test were identified.

 

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

 

Summary

Based on the review of the peer reviewed medical literature one clinical validity study suggests that ProMark Protein Biomarker test offers additional prognostic information for patients compared with NCCN risk categories alone.

 

Decipher Prostate Cancer Test/Decipher Prostate Cancer Classifier

Decipher® Prostate Cancer Assay/ Decipher® Prostate Cancer Classifier is a tissue-based tumor 22-biomarker gene expression profile test is intended to serve as a prognostic marker of cancer tumor aggressiveness in patients newly diagnosed with localized prostate cancer. The gene expression classifier is a continuous risk score between 0 and 1, and a categorization of that score into low, average, or high risk at the time of biopsy to determine if a patient can be safely followed with active surveillance or should be considered for immediate treatment.

 

Clinically Valid

In 2015, Tomlins et. al. conducted a retrospective study to determine if prostate cancer molecular subtyping could be performed from the “extra” data generated by a clinically available prognostic assay (Decipher), which genome-wide microarray expression profiling from formalin fixed paraffin embedded (FFPE) tissue to determine a prognostic score using the expression of 22 genes. Clinical assessment may aid in disease stratification, complementing available prognostic tests. They analyzed Affymetrix Gene Chip expression profiles for 1577 patients from eight radical prostatectomy cohorts, including 1351 cases assessed using the Decipher prognostic assay (GenomeDx Biosciences, San Diego, CA, USA) performed in a laboratory with Clinical Laboratory Improvements Amendment certification. A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non-ERG ETS gene rearrangements (ETS(+)) or SPINK1 overexpression (SPINK1(+)). Outcome measurements were associations with clinical features and outcomes by multivariate logistic regression analysis and receiver operating curves. The m-ERG classifier showed 95% accuracy in an independent validation subset (155 samples). Across cohorts, 45% of prostate cancers were classified as m-ERG(+), 9% as m-ETS(+), 8% as m-SPINK1(+), and 38% as triple negative (m-ERG(-)/m-ETS(-)/m-SPINK1(-)). Gene expression profiling supports three underlying molecularly defined groups: m-ERG(+), m-ETS(+), and m-SPINK1(+)/triple negative. On multivariate analysis, m-ERG(+) tumors were associated with lower preoperative serum prostate-specific antigen and Gleason scores, but greater extraprostatic extension (p<0.001). m-ETS(+) tumors were associated with seminal vesicle invasion (p=0.01), while m-SPINK1(+)/triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients (p<0.001). Clinical outcomes were not significantly different among subtypes. The authors concluded, although we demonstrate that molecular subtypes are not prognostic in the post-prostatectomy setting (nor impact the performance of currently available prognostic signatures), we anticipate that molecular subtyping will complement prognostic based tests in several areas of prostate cancer management including non-radical prostatectomy patients.

 

In 2018, Kim et. al. conducted a study validating the Decipher test for predicting adverse pathology in candidates for prostate cancer active surveillance. Many men diagnosed with prostate cancer are active surveillance (AS) candidates. However, AS may be associated with increased risk of disease progression and metastasis due to delayed therapy. Genomic classifiers, e.g., Decipher may allow better risk stratify newly diagnosed prostate cancers for AS.  Decipher was initially assessed in a prospective cohort of prostatectomies to explore the correlation with clinically meaningful biologic characteristics and then assessed in diagnostic biopsies from a retrospective multicenter cohort of 266 men with National Comprehensive Cancer Network (NCCN) very low/low and favorable-intermediate risk prostate cancer. Decipher and Cancer of the Prostate Risk Assessment (CAPRA) were compared as predictors of adverse pathology (AP) for which there is universal agreement that patients with long life-expectancy are not suitable candidates for AS (primary pattern 4 or 5, advanced local stage [pT3b or greater] or lymph node involvement). Decipher from prostatectomies was significantly associated with adverse pathologic features (p-values < 0.001). Decipher from the 266 diagnostic biopsies (64.7% NCCN-very-low/low and 35.3% favorable-intermediate) was an independent predictor of AP (odds ratio 1.29 per 10% increase, 95% confidence interval [CI] 1.03-1.61, p-value 0.025) when adjusting for CAPRA. CAPRA area under curve (AUC) was 0.57, (95% CI 0.47-0.68). Adding Decipher to CAPRA increased the AUC to 0.65 (95% CI 0.58-0.70). NPV, which determines the degree of confidence in the absence of AP for patients, was 91% (95% CI 87-94%) and 96% (95% CI 90-99%) for Decipher thresholds of 0.45 and 0.2, respectively. Using a threshold of 0.2, Decipher was a significant predictor of AP when adjusting for CAPRA (p-value 0.016). The authors concluded, Decipher can be applied to prostate biopsies from NCCN-very-low/low and favorable-intermediate risk patients to predict absence of adverse pathologic features. These patients are predicted to be good candidates for active surveillance.

 

Clinically Useful

A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

 

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.

 

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

 

In 2018, Spratt et. al. aimed to develop a novel clinical-genomic risk grouping system that can readily be incorporated into treatment guidelines for localized prostate cancer. Two multicenter retrospective cohorts (n=991) were used for training and validation of the clinical genomic risk groups (radical prostatectomy [RP] samples), and two additional cohorts (n= 5,937) were used for reclassification analysis (prospective cohort I, 4,960 RP samples) and (prospective cohort II, 977 pretreatment biopsy samples) that included demographic and baseline clinical and pathologic information. These patients were deidentified and aggregated from routine clinical use of the Decipher prostate cancer classifier test. Competing risks analysis was used to estimate the risk of distant metastasis. Time-dependent c-indices were constructed to compare clinicopathologic risk models with the clinical-genomic risk groups. Results With a median follow-up of 8 years for patients in the training cohort, 10-year distant metastasis rates for National Comprehensive Cancer Network (NCCN) low, favorable-intermediate, unfavorable-intermediate, and high-risk were 7.3%, 9.2%, 38.0%, and 39.5%, respectively. In contrast, the three-tier clinical-genomic risk groups had 10-year distant metastasis rates of 3.5%, 29.4%, and 54.6%, for low-, intermediate-, and high-risk, respectively, which were consistent in the validation cohort (0%, 25.9%, and 55.2%, respectively). C-indices for the clinical-genomic risk grouping system (0.84; 95% CI, 0.61 to 0.93) were improved over NCCN (0.73; 95% CI, 0.60 to 0.86) and Cancer of the Prostate Risk Assessment (0.74; 95% CI, 0.65 to 0.84), and 30% of patients using NCCN low/intermediate/high would be reclassified by the new three-tier system and 67% of patients would be reclassified from NCCN six-tier (very-low- to very-high-risk) by the new six-tier system. The authors concluded, a commercially available genomic classifier in combination with standard clinicopathologic variables can generate a simple-to-use clinical genomic risk grouping that more accurately identifies patients at low, intermediate, and high-risk for metastasis and can be easily incorporated into current guidelines to better risk-stratify patients.

 

Summary

Based on review of the peer reviewed medical literature the potential usefulness of this test is that it allows physicians to determine which patients with early prostate cancer are candidates for active surveillance (AS), and are more likely to have a good outcome without needing to receive definitive treatment.

 

Management Decision After Radical Prostatectomy (RP)

Clinical Context and Test Purpose

The purpose of gene expression profiling and protein biomarkers tests in patients who have prostate cancer and who have undergone radical prostatectomy is to inform management decisions.

 

For example, the optimal timing of radiation therapy (RT) after radical prostatectomy (RP) is debated. Adjuvant radiation therapy (RT) may maximize cancer control outcomes; however, early salvage radiation therapy (RT) (at first evidence of rising serym PSA level) can minimize overtreatment and still lead to acceptable oncologic outcomes. Adjuvant RT in men with pT3 or margin positive cancer has been compared with observation in randomized controlled trials (RCTs); such comparisons have shown that adjuvant RT improves the biochemical and local control rates among patients with adverse pathology at RP. Although the observation arms in these trials included men who received adjuvant therapy, the trials did not directly compare early salvage RT with immediate adjuvant RT because they included varying or unspecified thresholds for the initiation of salvage therapy RT.

 

Several observational analyses have shown conflicting conclusions whether adjuvant RT is favored over salvage RT. RCTs comparing adjuvant with early stage RT are underway. American Urological Association (AUA) has recommended that adjuvant RT should be offered to patients with adverse pathologic findings at RP, and salvage RT should be offered to patients with PSA or local recurrence after RP.

 

Patients

The relevant population of interest is individuals who have undergone radical prostatectomy (RP) for prostate cancer, and who are deciding on subsequent management such as adjuvant radiation therapy (RT) versus no adjuvant RT.

 

Interventions

Prolaris is also intended to classify individuals who have undergone radical prostatectomy (RP).

 

Decipher is a tissue based tumor 22-biomarker gene expression profiling (GEP) test intended to classify high risk individuals who have undergone RP.  The gene expression classifier is a continuous risk score between 0 and 1, and a categorization of that score following radical prostatectomy shows the associated probabilities of high-grade disease, 5 year metastatic risk, and 10 year prostate cancer specific mortality on final pathology.

 

Comparators

Clinicopathologic risk stratification is currently being used to make decisions about prostate cancer management following radical prostatectomy (RP). Clinical characteristics (e.g. stage, biopsy Gleason grade, serum PSA level, surgical margin, disease involvement) and demographic characteristics (e.g. age, life expectancy) are combined to classify men according to risk. The National Comprehensive Cancer Network (NCCN) and the American Urological Association (AUA) provide risk stratification guidelines. The Stephenson nomogram and the Cancer of the Prostate Risk Assessment-Surgical (CAPRA-S) nomogram can be used to predict outcomes after RP.

 

Outcomes

Beneficial outcomes resulting from a true test are prolonged survival, improved quality of life and reduction in unnecessary treatment related adverse effects. Harmful outcomes resulting from false test result are recurrence, metastases or death, and unnecessary treatments. Outcomes of interest are overall survival (10 year survival), disease specific survival (10 year prostate cancer free survival; 10 year prostate cancer death rate; 10 year recurrence rate), quality of life and treatment related morbidity (adverse events of radiotherapy or radical prostatectomy).

 

Timing

Ten year outcomes are of interest due to the prolonged nature of prostate cancer.

 

Setting

Decisions about management of prostate cancer following radical prostatectomy (RP) are typically made by patients and urologists in the secondary or tertiary care setting.

 

Prolaris

Prolaris used for initial management decisions was described in the previous section. This section reviews Prolaris for management after radical prostatectomy (RP).

 

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

 

Cuzick et. al. (2011) examined the potential use of the Prolaris CCP (cell cycle progression) test combined with a clinical score following radical prostatectomy (RP), using a retrospective cohort of archived samples from a tumor registry. The study also included a cohort of men with localized prostate cancer detected from specimens obtained during transurethral resection of the prostate (TURP), which is not a population of interest here, and so it is not described. Men conservatively managed after RP between 1985 and 1995 were identified from a tumor registry (n=366 with CCP scores, Scott and White Clinic, in Texas). The primary end point was time to BCR (biochemical recurrence), and the secondary end point was prostate cancer death. Myriad Genetics assessed CCP scores blindly. The median age of patients was 68 years and median follow-up 9.4 years. Cancers were clinically staged as T3 in 34%; following RP, 64 was judged pathologic stage T3. After prostatectomy, the CCP score was useful for predicting biochemical recurrence in the univariate analysis (hazard ratio for a 1-unit change [doubling] in CCP 1·89; 95% CI 1·54-2·31; p=5·6×10-9)) and the best multivariate analysis (1·77, 1·40-2·22; p=4·3×10-6). In the best predictive model (final multivariate analysis), the CCP score and prostate-specific antigen (PSA) concentration were the most important variables and were more significant than any other clinical variable. Analyses of prostate cancer deaths in the RP cohort was problematic, owing to only 12 (3%) deaths. The AUC (area under the curve) for BCR within 5 years of the RP cohort as 0.825 for the clinical score and 0.842 for the combined score including the CCP score. Although the CCP score increased the AUC by 2%, whether that improvement is clinically useful is unclear because of the lack of reclassification data and analysis of net benefit.

 

Cooperberg et. al. (2013) evaluated the cell cycle progression (CCP) score, in predicting radical prostatectomy (RP) outcomes. RNA was quantified from paraffin embedded RP specimens. The CCP score was calculated as average expression of 31 CCP genes, normalized to 15 housekeeper genes. Recurrence was defined as two prostate specific antigen (PSA) levels ≥ 0.2 ng/mL or any salvage treatment. Associations between CCP score and recurrence were examined, with adjustment for clinical and pathologic variables using Cox proportional hazards regression and partial likelihood ratio tests. The CCP score was assessed for independent prognostic utility beyond a standard postoperative risk assessment, Cancer of the Prostate Risk Assessment post-Surgical (CAPRA-S) score, and a score combining CAPRA-S and CCP was validated. The validation cohort was obtained from patients identified from the UCSF Urologic Oncology Database. Tissue sufficient to obtain a CCP score was available for 413 men (69% of the 600 eligible samples). Both UCSF and Myriad Genetics performed statistical analyses. In the validation cohort, 95% had Gleason scores of 7 or lower, 16% of samples had positive margins, 4% had seminal vesicle invasion, and 23% had extracapsular extension. Eighty-two (19.9%) of 413 men experienced recurrence. The hazard ratio (HR) for each unit increase in CCP score (range, -1.62 to 2.16) was 2.1 (95% CI, 1.6 to 2.9); with adjustment for CAPRA-S, the HR was 1.7 (95% CI, 1.3 to 2.4). The score was able to substratify patients with low clinical risk as defined by CAPRA-S ≤ 2 (HR, 2.3; 95% CI, 1.4 to 3.7). Combining the CCP and CAPRA-S improved the concordance index for both the overall cohort and low-risk subset; the combined CAPRA-S + CCP score consistently predicted outcomes across the range of clinical risk. This combined score outperformed both individual scores on decision curve analysis. The authors concluded the CCP score was validated to have significant prognostic accuracy after controlling for all available clinical and pathologic data. The score may improve accuracy of risk stratification for men with clinically localized prostate cancer, including those with low risk disease. Future studies will include explicit heterogeneity studies to compare CCP score findings between biopsy and prostatectomy tissues and from different samples taken from the same tumor. Although heterogeneity may have been a potential source of misclassification in our study, it would tend, if anything to bias the results toward null. The real world effectiveness of this assay depends on its applicability in the community setting. Also, postoperative risk prediction models may perform differently in academic and community based settings, so future validation in nonacademic cohorts will also be important.

 

Bisoff et. al. (2014) evaluated the prognostic usefulness of the cell cycle progression (CCP) score derived from biopsy specimens in men treated with radical prostatectomy (RP). The study included 3 cohorts: the Martini Clinic (283), Durham Veterans Affairs Medical Center (176) and Intermountain Healthcare (123). The score was derived from simulated biopsy (Martini Clinic) or diagnostic biopsy (Durham Veterans Affairs Medical Center and Intermountain Healthcare) and evaluated for an association with biochemical recurrence and metastatic disease. The combined analysis included 582 patients. Univariate analysis (HR per score unit 1.60, 95% CI 1.35-1.90, p=2.4×10-7) and multivariate analysis (HR per score unit 1.47, 95% CI 1.23-1.76, p=4.7×10-5). Metastatic events (n=12) were too few to draw conclusions.

 

Koch et. al. (2016) evaluated whether the CCP (cell cycle progression) score could discriminate between systemic disease and local recurrence in patients with biochemical recurrence (BCR) after radical prostatectomy (RP). All 60 patients given RP as primary therapy at an academic medical center between 1995 and 2010 for whom samples were available and who had a BCR and either developed metastatic disease or received salvage EBRT with at least 2 years of follow-up were eligible for retrospective analysis. Data from 5 patients were excluded for failing to meet clinical eligibility requirements (no clarification provided) or because data were incomplete; sample blocks from 3 patients contained insufficient tumor for assay and data from 6 patients were excluded due to lack of “passing” CCP score. Forty-seven patients were included in the analysis. Outcomes were classified into 3 categories: (1) metastatic disease (n=22); (2) nonresponse to salvage EBRT (n=14); and (3) durable response to salvage EBRT (n=11). Analyses were performed with a binary outcome (categories 1 and 2 combined). For each 1-unit change in the CCP score, the univariate odds ratio (OR) for metastatic disease or nonresponse was 3.72 (95% CI, 1.29 to 10.7). Multivariate analysis was performed; however, due to the very small number of participants in the durable response group, CIs (confidence intervals) were very wide. The authors concluded this study is limited by its retrospective nature and small patient cohort size. Nonetheless, this is the largest population of prostate cancer patients with metastatic disease evaluated for the role of CCP score thus far in this setting. Larger studies are necessary to validate these results and prove that the score adds prognostic information after adjusting for clinical variables.

 

Clinically Useful

A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

 

No studies were identified that directly supported the clinical utility of Prolaris for management after radical prostatectomy (RP).

 

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

 

Summary

Four identified studies examined the clinical validity of Prolaris in men after radical prostatectomy (RP) using a biochemical recurrence (BCR) or systemic disease end point. Cuzieck et. al. (2011) found that the CCP (cell cycle progression) score offered little improvement in the AUC (area under the curve) (2%) over clinicopathologic predictors and did not examine reclassification. Cooperberg et. al. (2013) found the AUC for BCR improved from 0.73 CAPRA-S alone to 0.77 by adding CCP score. Bishoff et. al. (2014) and Koch et. al. (2016) did not report any classification or discrimination measures. Koch et. al. study was performed in patients who had a BCR following RP.

 

No direct evidence is available to support the clinical utility of Prolaris for improving net health outcomes of patients with localized prostate cancer following radical prostatectomy (RP). The chain of evidence is also incomplete. Decision curve analysis did not provide convincing evidence of meaningful improvement in net benefit by incorporating the CCP (cell cycle progression) score. Proloaris CCP score may have an association with biochemical recurrence (BCR), but disease-specific survival outcomes were not reported. A larger number of disease-specific survival events and precision estimates for discrimination measures are needed.

 

Decipher Prostate Cancer Test/Decipher Prostate Cancer Classifier

The Decipher Prostate Cancer Test/Decipher Prostate Cancer Classifier uses the expression of the biomarkers (22 RNA biomarkers) associated with the aggressive prostate cancer, and calculates the probability of clinical metastasis within 5 years of radical prostatectomy (RP) surgery. This gene expression profiling (GEP) test is a continuous risk score between 0 and 1, with higher risk scores indicating a greater probability of developing metastasis.

 

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

 

The clinical validity of the Decipher Prostate Cancer Test/Decipher Prostate Cancer Classifier has been reported in studies to predict metastasis, mortality, or biochemical recurrence (BCR) after radical prostatectomy (RP) in patients with postoperative high-risk features like pathologic state T2 with positive margins, pathologic stage T3 disease, or rising PSA level.

 

Validation Studies: Observation and RT Samples

Cooperberg et. al. (2015) and Karnes et. al. (2017) evaluated the prognostic accuracy of the test for prostate cancer mortality; the others, for the development of metastasis. Karnes et. al. (2013) reported a 2.4% five year cumulative incidence of metastasis in 338 men with genomic classifier (GC) scores of less than 0.4, but 22.5% in the 77 men with scores 0.6 or more. In men wo had developed biochemical recurrence (BCR), Ross et. al. (2014) found the GC score was associated with a 5 year cumulative incidence of metastasis in 10% of men with scores of 0.4 or lower versus 54.0% in those with higher scores. The GC and AUCs (area under the curve) for predicting metastasis ranged from 0.75 to 0.82. The AUC for the comparators ranged from 0.66 to 0.75. Among the 69 men developing mestatasis in Karnes et. al. (2013), of the 29 Gleason scores of 7 or lower, 10 were correctly reclassified to the highs GC risk (score > 0.6), but of the 40 men with Gleason scores of 8 or higher, 10 were incorrectly reclassified to the lowest GC risk group (score < 0.4). For prostate cancer mortality, compared with CAPRA-S (Cancer of the Prostate Risk Assessment-Surgical score), Cooperberg et. al. (2015) found that the GC improved reclassification somewhat of the 19 men with CAPRA-S scores of 5 or lower, 12 were correctly reclassified to the highest GC risk, and 1 was incorrectly reclassified with a CAPRA-S score greater than 6 to low risk; all men had CAPRA-S scores of 3 or more. Similarly, Karnes et. al. (2017) found that adding the GC to CAPRA-S improved the AUC from 0.73 to 0.77 with highly overlapping CIs (confidence intervals).

 

Validation Studies: Observation-Only Samples

Three validation studies reported in 4 publications, Klein et. al. (2015), Klein et. al. (2016), Ross et. al. (2016) and Glass et. al. (2016) excluded men receiving any adjuvant therapy following radical prostatectomy (RP) over median follow-up periods ranging from 7.8 to 9 years. The Klein and Ross studies assessed the prognostic accuracy for metastasis through 5 or 10 years. Glass assessed the prognostic accuracy for clinical recurrence, defined as local, regional or distant recurrence or metastasis confirmed by clinical or radiologic evidence. Ross reported on the basis of previously defined CAPRA-S (Cancer of the Prostate Risk Assessment-Surgical score) risk categories, 6, 58 and 36% of men were classified as low (0–2), intermediate (3–5) and high risk (6-12), respectively and the cumulative incidence of metastasis at 10 years post RP was 11.3, 3.3 and 21.4%, respectively. In contrast, Decipher score classified 57, 27 and 16% as low (< 0.45), intermediate (0.45–0.60) and high risk (> 0.60), respectively. Cumulative incidence of metastasis at 10 years post RP was 6.8, 10.3 and 21.9% for these risk groups. The AUCs (area under the curve) are shown in the above table. Glass reported a 2.6% clinical recurrence rate by 10 years among patients with low Decipher scores but 13.6% among those with high Decipher scores (p=0.02). Ross et. al reported 10 year cumulative incidence of metastasis stratified by GC (genomic classifier) and CAPRA-S. The GC appeared to discriminate within intermediate CAPRA-S categories.

 

Validation Studies: RT Only samples

Three analyses of overlapping retrospectively assembled cohorts of men undergoing either adjuvant or salvage RT (radiation therapy). One study examined the prognostic ability of the genomic classifier (GC) for BCR (biochemical recurrence), while the others examined its prognostic ability for metastasis. Median follow-up in Den et. al. (2014) and Den et. al (2015) exceeded 10 years; the medial follow-up in Freedland et. al. (2016) was 7.4 years. Just over three-quarters of the men in the studies had positive surgical margins. Den et. al. (2014) found that the GCs AUC (area under the curve) for BCR was 0.75 compared with 0.70 for the Stephenson nomogram. The AUCs for the clinical outcomes are in the above table. In Den (2015), 7 (21.2%) of men with high GC scores (> 0.6) developed metastasis compared with 12 (15.2%) men with CAPRA-S (Cancer of the Prostate Risk Assessment-Surgical) scores exceeding 5. However, overall 19 (10.1%) men had developed metastasis. Among the 160 men who did not, the GC reclassified 27 of 67 men with high CAPRA-S scores into a low risk group, but given the small number of men developing metastasis the reclassifications were somewhat uncertain.  The authors also explored whether the classifier might identify men likely to benefit from adjuvant RT over salvage therapy, suggesting that adjuvant therapy might be preferred in men with a GC score greater than 0.4. However, that result was based on only 14 men with GC scores of 0.4 and 3 men with lower values. In Freedland (2016), 20 men developed metastasis. In reclassification analysis, 31 (39%) of patients in the upper 2 tertiles of risk by Briganti were classified as low risk by the GC, and one of them developed metastases during follow-up. Sevently-three (49%) of patients who were categorized as intermediate or high risk using CAPRA-S were classified as GC low risk; three developed metastasis during follow-up.

 

Clinically Useful

A test is clinically useful if the use of the results informs management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

 

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from RCTs.

 

No studies reporting direct evidence of clinical utility were identified.

 

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

 

Decision Curves

Studies have included decision curves comparing the net benefit of different strategies using metastases or survival as the outcome. In observational and RT samples from Karnes et al (2013) and Ross et al (2014), over a 15% to 25% range of thresholds for decision making (i.e, suspected probability of developing metastases) would be expected to identify correctly as few as no men or as many as 4 per 100 likely to experience metastases. This range of thresholds makes several assumptions: it assumes those making the decisions are relying on the genomic classifier (GC) result for adjuvant RT decisions, compared with treating based on the best comparator test and it assumes no increase in false positives. No CIs (confidence intervals) were provided for the net benefit estimates and uncertainty cannot be evaluated. In the 2 observation-only samples, although the GC improved the net benefit over a “treat none” strategy over 15% to 25% thresholds, it appeared to offer little over the comparator test (e.g, about 1 additional patient would be likely to experience metastases without an increase in false positives). In Ross, the net benefit for CAPRA-S (Cancer of the Prostate Risk Assessment-Surgical) score exceeded that of the GC, with the net benefit of the GC plus CAPRA-S score being slightly better than the CAPRA-S score alone. Finally, among men undergoing RT, decision curves suggested that the test would identify 3 or 4 men developing metastases per 100 tested at a fixed false-positive rate. Lobo et al (2015) reported an individualized decision analysis comparing the GC with “usual care” using data from the cohorts in Karnes et al (2013) and Den et al (2014). The usual care probabilities of receiving each treatment were derived from the published literature. A 6% threshold for the GC score was used for GC-based treatment. Using the cohort from Karnes (2013), the estimated 10-year probability of metastasis or death was 0.32 (95% CI, 0.32 to 0.33) for usual care compared with 0.31 (95% CI, 0.30 to 0.32) for GC-based treatment. In the cohort from Den (2014), the estimated 10-year probability of metastasis or death was 0.28 (95% CI, 0.27 to 0.29) for usual care compared with 0.26 (95% CI, 0.25 to 0.27) for GC-based treatment.

 

Spratt et. al. (2018), evaluated if a 22-gene genomic classifier can independently predict development of metastasis in men with PSA persistence postoperatively. A multi-institutional study of 477 men who underwent radical prostatectomy (RP) between 1990 and 2015 from three academic centers. Patients were categorized as detectable PSA (n=150) or undetectable (n=327) based on post-RP PSA nadir ≥0.1 ng/ml. Cumulative incidence curves for metastasis were constructed using Fine-Gray competing risks analysis. Penalized Cox univariable and multivariable (MVA) proportional hazards models were performed to evaluate the association of the genomic classifier with metastasis. The median follow-up for censored patients was 57 mo. The median time from RP to first postoperative PSA was 1.4 mo. Detectable PSA patients were more likely to have higher adverse pathologic features compared with undetectable PSA patients. On MVA, only genomic high-risk (hazard ratio [HR]: 5.95, 95% confidence interval [CI]: 2.02-19.41, p=0.001), detectable PSA (HR: 4.26, 95% CI: 1.16-21.8, p=0.03), and lymph node invasion (HR: 12.2, 95% CI: 2.46-70.7, p=0.003) remained prognostic factors for metastasis. Among detectable PSA patients, the 5-yr metastasis rate was 0.90% for genomic low/intermediate and 18% for genomic high risk (p<0.001). Genomic high risk remained independently prognostic on MVA (HR: 5.61, 95% CI: 1.48-22.7, p=0.01) among detectable PSA patients. C-index for Cancer of the Prostate Risk Assessment Postsurgical score, Gandaglia nomogram, and the genomic classifier plus either Cancer of the Prostate Risk Assessment Postsurgical score or Gandaglia were 0.69, 0.68, and 0.82 or 0.81, respectively. Sample size was a limitation. The authors concluded, despite patients with a detectable PSA harboring significantly higher rates of aggressive clinicopathologic features, Decipher independently predicts for metastasis. Prospective validation of these findings is warranted and will be collected as part of the ongoing randomized trial NRG GU-002.

 

In 2018, Karnes et. al. validated the 22 gene Decipher genomic classifier (GC) to predict prostate cancer-specific mortality (PCSM) in men with adverse pathologic features after radical prostatectomy (RP). Men with adverse pathologic features: pT3, pN1, positive margins, or Gleason score >7 who underwent RP in 1987-2010 at Johns Hopkins, Cleveland Clinic, Mayo Clinic, and Durham Veteran's Affairs Hospital. We also analyzed subgroups at high risk (prostate-specific antigen >20 ng/ml, RP Gleason score 8-10, or stage >pT3b), or very high risk of PCSM (biochemical recurrence in<2 yr [BCR2], or men who developed metastasis after RP [MET]). Logistic regression evaluated the association of GC with PCSM within 10 yr of RP (PCSM10), adjusted for the Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S). GC performance was evaluated with area under the receiver operating characteristic curve (AUC) and decision curves. Five hundred and sixty-one men (112 with PCSM10), median follow-up 13.0 yr (patients without PCSM10). For high GC score (> 0.6) versus low-intermediate (≤ 0.6), the odds ratio for PCSM10 adjusted for CAPRA-S was 3.91 (95% confidence interval: 2.43-6.29), with AUC=0.77, an increase of 0.04 compared with CAPRA-S. Subgroup odds ratios were 3.96, 3.06, and 1.95 for high risk, BCR2, or MET, respectively (all p<0.05), with AUCs 0.64-0.72. GC stratified cumulative PCSM10 incidence from 2.8% to 30%. Combined use of case-control and cohort data is a potential limitation. In a large cohort with the longest follow-up to date, Decipher GC demonstrated clinically important prediction of PCSM at 10 yr, independent of CAPRA-S, in men with adverse pathologic features, BCR2, or MET after RP.

 

Changes in Management

Several studies have compared physician’s treatment recommendations before and after receiving genomic classifier (GC) results.

 

Ross et al (2016) reported on results of a retrospective, comparative study of radiation therapy (RT) after radical prostatectomy (RP) for 422 men with pT3 disease or positive margins. The men were from 4 cohorts previously described (Karnes et al, 2013; Den et al, 2014; Ross et al, 2016; Freedland et al, 2016). The 4 treatment groups were adjuvant RT (n=111), minimal residual disease salvage RT (n=70), salvage RT (n=83), and no RT (n=157). The primary end point was metastasis. Thirty-seven men developed metastasis, and the median follow-up was 8 years. Both CAPRA-S (Cancer of the Prostate Risk Assessment-Surgical score) (HR=1.39; 95% CI, 1.18 to 1.62) and Decipher (HR=1.28; 95% CI, 1.08 to 1.52) were independently associated with metastasis in multivariable analysis. There was no evidence that treatment effect was dependent on genomic risk (interaction p=0.16 for CAPRA-S, p=0.39 for Decipher). Men with low CAPRA-S or low Decipher scores had a low risk of metastatic events regardless of treatment selection and men with high CAPRA-S or Decipher scores benefitted from adjuvant RT compared with the other treatments.

 

Summary

Clinical validity has been evaluated in overlapping validation samples (including the development test set). The validation studies consisted of observational data obtained from registries or medical records with archived samples. Although each study evaluated different outcomes (i.e., metastasis, prostate cancer‒specific mortality [PCSM], biochemical recurrence [BCR]) in samples with different populations, all studies reported some incremental improvement in discrimination and determining subsequent management such as adjuvant radiation therapy (RT) versus no adjuvant RT following radical prostatectomy.

 

Summary of Evidence

Treatment paradigms for men with prostate cancer have been developed, and they are based on assessing the risk of a patient having an unfavorable outcome due to prostate cancer within the patient’s expected lifetime. Patients at higher risk are recommended to have a greater intensity of treatment. Within the favorable intermediate risk stratum, active surveillance is a recommended treatment approach, though it likely remains underutilized, and selecting patients who are likely to have poor prostate cancer related mortality in the absence of higher intensity treatment is imprecise based on clinical and pathological risk classification. While there are no randomized controlled trials, numerous retrospective and prospective clinical validity studies have all had similar and consistent findings, providing evidence that these tests can accurately risk stratify patients based on genetic information. While research has not definitively shown that such risk stratification improves outcomes in terms of either better prostate cancer outcomes or overall reductions in treatment related adverse events, there is sufficient evidence these tests are able to better inform patient and clinician decisions that must presently be made in a state of significant uncertainty. As such, these tests provide clinically actionable incremental information that fits into existing evidence based or consensus recommended prostate cancer treatment paradigms. The National Comprehensive Cancer Network (NCCN) guideline for prostate cancer version 4.2019 states the following regarding tumor multigene molecular testing: Although full assessment of their clinical utility requires prospective randomized clinical trials, which are unlikely to be done, the panel believes that men with low or favorable intermediate disease may consider the use of Decipher, Oncotype DX Prostate, Prolaris or ProMark during initial risk stratification. Indirect evidence of clinical utility rests on clinical validity, therefore, based on review of the peer reviewed medical literature, the evidence is sufficient to determine that the technology results in meaningful improvement in net health outcomes for Decipher, Oncotype DX Prostate, Prolaris or ProMark on biopsy specimens for prostate cancer risk stratification/prognosis to inform initial management decisions, either active surveillance or immediate therapy in men newly diagnosed with clinically localized untreated prostate cancer who have an estimated life expectancy of ≥ 10 years and meet the medically necessity criteria outlined below in the Policy section of this medical policy.

 

For individuals who have localized prostate cancer who are treated with radical prostatectomy (RP) and who receive the Decipher prostate cancer classifier, the evidence includes prospective and retrospective studies of clinical validity using overlapping archived samples, decision-curve analyses examining indirect evidence of clinical utility, and prospective decision-impact studies without pathology or clinical outcomes. The clinical validity of the Decipher genomic classifier (GC) has been evaluated in samples of patients with high-risk prostate cancer undergoing different interventions following RP. Studies reported incremental improvement in discrimination and determining subsequent management such as adjuvant radiation therapy (RT) versus no adjuvant RT following radical prostatectomy. Indirect evidence of clinical utility rests on clinical validity.  The National Comprehensive Cancer Network (NCCN) guideline for prostate cancer version 4.2019 states the following: Decipher may be considered post radical prostatectomy for pT2 with positive margins; any pT3 disease; rising PSA (above nadir) (category 2B). Based on review of the peer reviewed medical literature the evidence is sufficient to determine that the technology results in meaningful improvement in net health outcomes for individuals that meet the medical necessity criteria outlined below in the Policy section of this medical policy.

 

For individuals who have localized prostate cancer who are treated with radical prostatectomy (RP) who receive Prolaris, the evidence includes retrospective cohort studies of clinical validity using archived samples. Evidence of improved clinical validity or prognostic accuracy for prostate cancer death using the Prolaris Cell Cycle Progression score in patients after prostatectomy has shown some improvement. However, no direct evidence is available to support the clinical utility of Prolaris for improving net health outcomes of patients with localized prostate cancer following radical prostatectomy (RP). The decision curve analysis did not provide convincing evidence of meaningful improvement in net benefit by incorporating the CCP (cell cycle progression) score. Proloaris CCP score may have an association with biochemical recurrence (BCR), but disease-specific survival outcomes were not reported. A larger number of disease-specific survival events and precision estimates for discrimination measures are needed. The National Comprehensive Cancer Network (NCCN) guideline for prostate cancer version 4.2019 does not recommend the use of Prolaris tissue- based testing post radical prostatectomy (RP) to inform management decisions. The evidence is insufficient to determine the effects of the technology on net health outcomes.

 

Practice Guidelines and Position Statements

National Comprehensive Cancer Network (NCCN) Prostate Cancer Version 1.2020

Tumor Multigene Testing

Personalized or precision medicine is a goal for many translational and clinical investigators. The National Academy of Medicine has described several lessons that should accelerate the development of useful biomarkers to inform men and their physicians about proper choices for treatment of clinically localized prostate cancer. Dr. Hayes has warned that a "bad tumor marker is as bad as a bad drug." The NCCN Prostate Cancer Guidelines Panel strongly advocates for use of expectancy estimation, use of nomograms, and active surveillance as the only option for men with low-risk prostate cancer and life expectancy less than 10 years or very low risk prostate cancer and life expectancy less than 20 years. Although risk groups, life expectancy estimates, and nomograms help inform decisions, uncertainty about the risk of disease progression persists. American men continue to under-select active surveillance and their physicians may under-recommend it, likely as a result of this uncertainty.

 

Several tissue based molecular assays have been developed in an effort to improve decision making in newly diagnosed men considering active surveillance and in treated men considering adjuvant therapy or treatment for recurrence. Uncertainty about the risk of disease progression can be reduced if such molecular assays can provide accurate and reproducible prognostic or predictive information beyond NCCN risk group assignment and currently available life expectancy tables and nomograms. Retrospective case cohort studies have shown that these assays provide prognostic information dependent of NCCN or CAPRA risk groups, which include likelihood of death with conservative management, likelihood of biochemical recurrence after radical prostatectomy or EBRT, likelihood of adverse pathologic features after radical prostatectomy, and likelihood of developing metastasis after operation or salvage EBRT. A prospective, clinical utility study of 3966 patients newly diagnosed with localized prostate cancer found that the rates of active surveillance localized prostate cancer found that the rates of active surveillance increased with use of a tissue-based gene expression classifier. Active surveillance rates were 46.2%, 759% and 57.9% for those whose classifier results were above the specified threshold, below the threshold, and those who did not undergo genomic testing, respectively (P < .001). The authors estimate 1 additional patient may chose active surveillance for every 9 men with favorable risk prostate cancer who undergo genomic testing.

 

No randomized controlled trials have studied the utility of these tests. Several of these assays are available, and 4 have received positive reviews by the Molecular Diagnostic Services Program (MoIDX) and are likely to be covered by CMS (Centers for Medicare & Medicaid Services). Several other tests are under development, and the use of these assays is likely to increase in the coming years.

 

Table 1 lists provides on overview of each test, populations where each test independently predicts outcome, and supporting references. These molecular biomarker tests have been developed with extensive industry support, guidance, and involvement and have been marketed under the less rigorous FDA regulatory pathway for biomarkers. Although full assessment of their clinical utility requires prospective randomized clinical trials, which are unlikely to be done, the panel believes that men with low or favorable intermediate disease may consider the use of Decipher, Oncotype DX Prostate, Prolaris or ProMark during initial risk stratification. In addition, Decipher may be considered during workup for radical prostatectomy PSA persistence or recurrence (category 2B). Future comparative effectiveness research may allow these tests and others like them to gain additional evidence regarding their utility for better risk stratification of men with prostate cancer.

 

Table 1 Available Tissue Based Tests for Prostate Cancer Prognosis
TestPlatform Populations Studied Outcome(s) Reported (Test Independently Predicts)Molecular Diagnostic Services Program (MoIDX) Recommendations
Decipher Whole transcriptome 1.4M RNA expression (44,000 genes) oligonucleotide microarray optimized for FFPE tissue Post radical prostatectomy (RP), adverse pathology high risk features
  • Metastasis
  • Prostate cancer specific mortality
  • Postoperative radiation sensitivity (PORTOS)

 

Cover post-biopsy for NCCN very low and low risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy

 

Cover post RP for 1) pT2 with positive margins; 2) any pT3 disease; 3) rising PSA (above nadir)

Decipher Whole transcriptome 1.4M RNA expression (44,000 genes) oligonucleotide microarray optimized for FFPE tissue Post RP, biochemical recurrence
  • Metastasis
  • Prostate cancer specific mortality
  • Postoperative radiation sensitivity (PORTOS)

Cover post-biopsy for NCCN very low and low risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy

 

Cover post RP for 1) pT2 with positive margins; 2) any pT3 disease; 3) rising PSA (above nadir)

Decipher Whole transcriptome 1.4M RNA expression (44,000 genes) oligonucleotide microarray optimized for FFPE tissue Post RP, adjuvant, or salvage radiation
  • Metastasis
  • Prostate cancer specific mortality
  • Postoperative radiation sensitivity (PORTOS)

Cover post-biopsy for NCCN very low and low risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy

 

Cover post RP for 1) pT2 with positive margins; 2) any pT3 disease; 3) rising PSA (above nadir)

Decipher Whole transcriptome 1.4M RNA expression (44,000 genes) oligonucleotide microarray optimized for FFPE tissue Biopsy, localized prostate cancer post RP or EBRT
  • Metastasis
  • Prostate cancer specific mortality
  • Gleason grade ≥4 disease RP
  • Adverse pathologic features at RP

Cover post-biopsy for NCCN very low and low risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy

 

Cover post RP for 1) pT2 with positive margins; 2) any pT3 disease; 3) rising PSA (above nadir)

Ki-67

IHC

Biopsy intermediate to high risk treated with EBRT

 

  • Metastasis

 

Not recommended
Ki-67 IHC

Biopsy conservatively managed (active surveillance

  • Prostate cancer specific mortality
Not recommended
OncotypeDx Prostate Quantitative RT-PCR for 12 prostate cancer related genes and 5 housekeeping controls Biopsy, low to intermediate risk treated with radical prostatectomy (RP)
  • Non-organ confined pT3 or Gleason grade 4 disease on RP
Cover post-biopsy for NCCN very low, low risk and favorable intermediate risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy
Prolaris Quantitative RT-PCR for 31 cell cycle related genes and 15 housekeeping controls Transurethral resection of the prostate (TURP), conservatively managed (active surveillance)
  • Prostate cancer specific mortality
Cover post-biopsy for NCCN very low, low risk and favorable intermediate risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy
Prolaris Quantitative RT-PCR for 31 cell cycle related genes and 15 housekeeping controls Biopsy conservatively managed (active surveillance)
  • Prostate cancer specific mortality
Cover post-biopsy for NCCN very low, low risk and favorable intermediate risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy
Prolaris Quantitative RT-PCR for 31 cell cycle related genes and 15 housekeeping controls Biopsy localized prostate cancer
  • Biochemical recurrence
  • Metastasis
Cover post-biopsy for NCCN very low, low risk and favorable intermediate risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy
Prolaris Quantitative RT-PCR for 31 cell cycle related genes and 15 housekeeping controls Biopsy intermediate risk treated with EBRT
  • Biochemical recurrence
Cover post-biopsy for NCCN very low, low risk and favorable intermediate risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy
Prolaris Quantitative RT-PCR for 31 cell cycle related genes and 15 housekeeping controls

RP, node negative localized prostate cancer

  • Biochemical recurrence
Cover post-biopsy for NCCN very low, low risk and favorable intermediate risk prostate cancer in patients with at least 10 years life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy
ProMark Multiplex immunofluorescent staining of 8 proteins Biopsy, Gleason grade 3+3 or 3+4
  • Non-organ confined pT3 or Gleason pattern 4 disease on RP (radical prostatectomy)
Cover post biopsy for NCCN very low and low risk prostate cancer in patients with at least 10 year life expectancy who have not received treatment for prostate cancer and are candidates for active surveillance or definitive therapy
PTEN Fluorescent in situ hybridization or IHC TURP conservatively managed
  • Prostate cancer specific mortality
Not recommended
PTEN Fluorescent in situ hybridization or IHC Biopsy, Gleason grade 3+3 or 3+4
  • Upgrading to Gleason pattern 4 on RP
Not recommended
PTEN Fluorescent in situ hybridization or IHC RP, high risk localized disease
  • Biochemical recurrence
Not recommended

 

Initial Risk Stratification and Staging Workup for Clinically Localized Disease
Risk GroupClinical/Pathologic FeaturesImagingGermline TestingMolecular and Biomarker Analysis of Tumor
Very low
  • T1c AND
  • Grade Group 1 AND
  • PSA<10 ng/mL AND
  • Fewer than 3 prostate biopsy fragments/cores positive, < 50% cancer in each fragment/core AND
  • PSA density < 0.15 ng/mL/g
Not indicated Recommended if family history positive or intraductal histology Not indicated
Low
  • T1-T2a AND
  • Grade Group 1 AND
  • PSA < 10ng/mL
Not indicated Recommended if family history positive or intraductal histology Consider if life expectancy > 10 years
Intermediate Has no high or very risk features and has one or more intermediate risk factors (IRF):
  • T2b-T2c
  • Grade Group 2 or 3
  • PSA10-20 ng/mL
- - -
Favorable Intermediate
  • 1 IRF and
  • Grade Group 1 or 2 and
  • < 50% biopsy cores positive
  • Bone imaging not recommended for staging
  • Pelvic +/-abdominal imaging recommended if nomogram predicts > 10% probability of pelvic lymph node involvement
Recommended if family history positive or intraductal histology Consider if life expectancy > 10 years
Unfavorable Intermediate
  • 2 or 3 IRFs and/or
  • Grade Group 3 and/or
  • > 50% biopsy cores positive
  • Bone imaging: recommended if T2 and PSA > 10 ng/mL
  • Pelvic +/- abdominal imaging recommended if nomogram pedicts > 10% probability of pelvic lymph node involvement
Recommended if family history positive or intraductal histology Not routinely recommended
High
  • T3a OR
  • Grade Group 4 or Grade Group 5 OR
  • PSA > 20 ng/mL
  • Bone imaging recommended
  • Pelvic +/- abdominal imaging recommended if nomogram predicts > 10% probability of pelvic lymph node involvement
Recommended Not routinely recommended
Very High
  • T3b-T4 OR
  • Primary Gleason pattern 5 OR
  • >4 cores with Grade Group 4 or 5
  • Bone imaging recommended
  • Pelvic +/- abdominal imaging recommended if nomogram predicts > 10% probability of pelvic lymph node involvement
Recommended Not routinely recommended

 

American Society of Clinical Oncology (ASCO)

In 2019, the American Society of Clinical Oncology (ASCO) issued a guideline on molecular biomarkers in localized prostate cancer which included the following recommendations:

  • Commercially available molecular biomarkers (ie, Oncotype Dx Prostate, Prolaris, Decipher, and ProMark) may be offered in situations in which the assay result, when considered as a whole with routine clinical factors, is likely to affect management. Routine ordering of molecular biomarkers is not recommended (Type: Evidence based; Evidence quality: Intermediate; Strength of recommendation: Moderate).
    • Example clinical scenario: These may be considered, for instance, in select men with NCCN low- or favorable intermediate-risk prostate cancer who might benefit from refined risk classification when considering active surveillance (eg, high-volume Grade Group 1; Grade Group 1 with abnormal DRE or high PSA density; low-volume Grade Group 2).
  • The Expert Panel recommends consideration of a commercially available molecular biomarker (eg, Decipher Genomic Classifier)  in situations in which the assay result, when considered as a whole with routine clinical factors, is likely to affect management. In the absence of prospective clinical trial data, routine use of genomic biomarkers in the postprostatectomy setting to determine adjuvant versus salvage radiation or to initiate systemic therapies should not be offered (Type: Evidence based; Evidence quality: intermediate; Strength of recommendation: Moderate).

 

American Urological Association (AUA)

In 2017, American Urological Association (AUA)/American Society of Radiation Oncology (ASTRO) and Society Urologic Oncology (SUO) issued a guideline for clinically localized prostate cancer, which includes the following recommendations:

  • Very Low/Low Risk Disease
    • Clinicians should recommend active surveillance as the best available care option for very low-risk localized prostate cancer patients (Strong Recommendation; Evidence Level: Grade A)
    • Clinicians should recommend active surveillance as the preferable care option for most low-risk localized prostate cancer patients (Moderate Recommendation; Evidence Level: Grade B)
    • Clinicians may offer definitive treatment (i.e. radical prostatectomy or radiotherapy) to select low-risk localized prostate cancer patients who may have a high probability of progression on active surveillance (Conditional Recommendation; Evidence Level: Grade B)
    • Among most low-risk localized prostate cancer patients, tissue based genomic biomarkers have not shown a clear role in the selection of candidates for active surveillance (Expert Opinion)
  • Intermediate Risk Disease
    • Clinicians should recommend radical prostatectomy or radiotherapy plus androgen deprivation therapy (ADT) as standard treatment options for patients with intermediate risk localized prostate cancer (Strong Recommendation; Evidence Level: Grade A)
    • Active surveillance may be offered to select patients with favorable intermediate-risk localized prostate cancer; however, patients should be informed that this comes with a higher risk of developing metastases compared to definitive treatment (Conditional Recommendation; Evidence Level: Grade C)
  • Active Surveillance
    • Localized prostate cancer patients who elect active surveillance should have accurate disease staging including systemic biopsy with ultrasound or MRI guided imaging (Clinical Principle)
    • Localized prostate cancer patients undergoing active surveillance should have routine surveillance PSA testing and digital rectal exams (Strong Recommendation; Evidence Level: Grade B)
    • Localized prostate cancer patients undergoing surveillance should be encouraged to have a confirmatory biopsy within the initial two years and surveillance biopsies thereafter (Clinical Principle)
    • Clinicians may consider multiparametric prostate MRI as a component of active surveillance for localized prostate cancer patients (Expert Opinion)
    • Tissue based genomic biomarkers have not shown a clear role in active surveillance for localized prostate cancer and are not necessary for following up. (Expert Opinion)
    • Clinicians should offer definitive treatment to localized prostate cancer patients undergoing active surveillance who develop adverse reclassification (Moderate Recommendation; Evidence Level: Grade B)
  • Post-Treatment Follow-Up
    • Clinicians should monitor localized prostate cancer patients post therapy with PSA, even though not all PSA recurrences are associated with metastatic disease and prostate cancer specific death. (Clinical Principle) 

 

Regulatory Status

Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests (LDTs) must meet the general regulatory standards of the Clinical Laboratory Improvement Act (CLIA). Prolaris®, Oncotype DX® Prostate Cancer Assay and Decipher® gene expression profiling, and the Promark™ protein biomarker test are available under the auspices of CLIA. Laboratories that offer LDTs must be licensed by CLIA for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

 

In November 2015, the FDA’s Office of Public Health Strategy and Analysis published a document on public health evidence for FDA oversight of LDTs. FDA argued that many tests need more FDA oversight that the regulatory requirements of CLIA. CLIA standards relate to laboratory operations, but do not address inaccuracies or unreliability of specific tests. Prolaris is among the 20 case studies in the document cited as needing FDA oversight. The document asserted that patients are potentially receiving inappropriate prostate cancer care because there is no evidence that results from the test meaningfully improve clinical outcomes.

 

Prior Approval:

Not applicable

 

Policy:

See Related Medical Policies

  • 02.04.56 Genetic and Protein Biomarkers for the Diagnosis and Cancer Risk Assessment of Prostate Cancer
  • 02.04.25 Prostate Specific Antigen Screening for Prostate Cancer

 

Use of gene expression profiling (GEP) analysis Oncotype DX Prostate, Prolaris, Decipher or use of protein biomarker ProMark performed on prostate biopsy specimen to guide management of prostate cancer may be considered medically necessary if ALL of the follow criteria are met:

  • Needle biopsy with localized adenocarcinoma of prostate (no clinical evidence of metastasis or lymph node involvement); and
  • The patient has not received pelvic radiation or androgen deprivation therapy (ADT) prior to the biopsy; and
  • The patient’s stage and risk stratification is defined as the following:
    • Low risk disease defined by NCCN (National Comprehensive Cancer Network):
      • T1-T2a; and
      • Grade Group 1/Gleason Score 6 or less; and
      • PSA < 10 ng/mL; OR
  • Favorable intermediate risk defined by NCCN (National Comprehensive Cancer Network):
    • T2b-T2c; and
    • PSA 10-20 ng/mL; and
    • Grade Group 1 (Gleason Score 6 or less) or Grade Group 2 (Gleason Score 3+4=7); and
    • < 50% biopsy cores positive; and
  • The patient has an estimated life expectancy of ≥ 10 years; and
  • The patient is a candidate for and is considering conservative therapy (active surveillance) and yet would be eligible for definitive therapy (radical prostatectomy, radiation therapy or brachytherapy).

 

Use of gene expression profiling (GEP) analysis or use of protein biomarker testing performed on prostate biopsy specimen is considered investigational when the above criteria are not met due to the lack of evidence demonstrating an impact on improved health outcomes. Also, the current NCCN guidelines for prostate cancer (version 1.2020) does not support the use of this tumor based molecular testing outside of the criteria indicated above.

 

Use of gene expression profiling (GEP) analysis Decipher after radical prostatectomy (RP) using the patient’s radical prostatectomy (RP) specimen to guide subsequent management of prostate cancer may be considered medically necessary if ALL of the following criteria are met:

  • Patient with localized prostate cancer who has undergone a radical prostatectomy (RP) within the previous 60 months; and
  • The patient is being considered for postoperative secondary therapy (i.e. radiation therapy) due to one or more cancer-recurrence risk factors (pre-PSA serum levels [4 or greater] and Gleason score [7 or greater]/Grade Group [2 or greater]; and
  • The patient must have achieved initial PSA nadir (defined as PSA at or below 0.2 ng/ml) within 120 days of radical prostatectomy (RP) surgery; and
  • The patient does not have any evidence of distant metastasis; and
  • The patient has not received any neo-adjuvant treatment prior to radical prostatectomy (RP); and
  • The patient’s surgical pathology report or medical records must have documented presence of adverse pathology for one of the following:
    • Pathological stage pT2 disease with a positive surgical margin; or
    • Pathological state pT3 disease (e.g. extraprostatic extension, seminal vesicle invasion, bladder neck invasion); or
    • Rising PSA after initial PSA nadir; and
  • The patient has an estimated life expectancy of ≥ 10 years. 

 

Use of gene expression profiling (GEP) analysis or use of protein biomarker testing after radical prostatectomy (RP) is considered investigational when the above criteria are not met due to the lack of evidence demonstrating an impact on improved health outcomes. Also, the current NCCN guidelines for prostate cancer (version 1.2020) does not support the use of this testing except for the gene expression profiling test indicated above.

 

Policy Guidelines

International Society of Urological Pathologists

Risk GroupISUP Grade GroupGleason Score
Low Grade Group 1 Gleason Score ≤ 6
Intermediate Favorable Grade Group 2 Gleason Score 7 (3+4)
Intermediate Unfavorable Grade Group 3 Gleason Score 7 (4+3)
High Grade Group 4 Gleason Score 8
Very High Grade Group 5 Gleason Score 9-10

 

Procedure Codes and Billing Guidelines:

To report provider services, use appropriate CPT* codes, Alpha Numeric (HCPCS level 2) codes, Revenue codes and / or diagnosis codes.

  • 81541 Oncology (prostate), mRNA gene expression profiling by real-time RT-PCR of 46 genes (31 content and 15 housekeeping), utilizing formalin-fixed paraffin-embedded tissue, algorithm reported as a disease-specific mortality risk (Prolaris®)
  • 81542 Oncology (prostate), mRNA , microarray gene expression profiling of 22 content genes, utilizing formalin-fixed paraffin-embedded tissue, algorithm reported as metastasis risk score (Decipher®, Decipher® Prostate Cancer Assay or Decipher® Prostate Cancer Classifier)
  • 81479 Unlisted molecular pathology procedures (when specified as Promark™/Promark™ Protein Biomarker Test/Promark™ Risk Score)
  • 81599 Unlisted multianalyte assay with algorithmic analysis (when specified as Promark™/Promark™ Protein Biomarker Test/Promark™ Risk Score)
  • 84999 Unlisted chemistry procedure(when specified as Promark™/Promark™ Protein Biomarker Test/Promark™ Risk Score)
  • 0047U Oncology (prostate), mRNA, gene expression profiling by real-time RT-PCR of 17 genes (12 content and 5 housekeeping), utilizing formalin-fixed paraffin-embedded tissue, algorithm reported as a risk score (Oncotype DX Prostate or Oncotype DX Prostate Cancer Assay)

 

Selected References:

  • Dall'Era MA, Cooperberg MR, Chan JM, et al. Active surveillance for early-stage prostate cancer: review of the current literature. Cancer. Apr 15 2008;112(8):1650-1659. PMID 18306379
  • Brawley OW. Prostate cancer epidemiology in the United States. World J Urol. Apr 2012;30(2):195-200. PMID 22476558
  • Bangma CH, Roemeling S, Schroder FH. Overdiagnosis and overtreatment of early detected prostate cancer. World J Urol. Mar 2007;25(1):3-9. PMID 17364211
  • Johansson JE, Andren O, Andersson SO, et al. Natural history of early, localized prostate cancer. JAMA. Jun 9 2004;291(22):2713-2719. PMID 15187052
  • Ploussard G, Epstein JI, Montironi R, et al. The contemporary concept of significant versus insignificant prostate cancer. Eur Urol. Aug 2011;60(2):291-303. PMID 21601982
  • Harnden P, Naylor B, Shelley MD, et al. The clinical management of patients with a small volume of prostatic cancer on biopsy: what are the risks of progression? A systematic review and meta-analysis. Cancer. Mar 1 2008;112(5):971-981. PMID 18186496
  • Brimo F, Montironi R, Egevad L, et al. Contemporary grading for prostate cancer: implications for patient care. Eur Urol. May 2013;63(5):892-901. PMID 23092544
  • Eastham JA, Kattan MW, Fearn P, et al. Local progression among men with conservatively treated localized prostate cancer: results from the Transatlantic Prostate Group. Eur Urol. Feb 2008;53(2):347-354. PMID 17544572
  • Bill-Axelson A, Holmberg L, Ruutu M, et al. Radical prostatectomy versus watchful waiting in early prostate cancer. N Engl J Med. May 12 2005;352(19):1977-1984. PMID 15888698
  • Thompson IM, Jr., Goodman PJ, Tangen CM, et al. Long-term survival of participants in the prostate cancer prevention trial. N Engl J Med. Aug 15 2013;369(7):603-610. PMID 23944298
  • Albertsen PC, Hanley JA, Fine J. 20-year outcomes following conservative management of clinically localized prostate cancer. JAMA. May 4 2005;293(17):2095-2101. PMID 15870412
  • Freedland SJ. Screening, risk assessment, and the approach to therapy in patients with prostate cancer. Cancer. Mar 15 2011;117(6):1123-1135. PMID 20960523
  • Ip S, Dahabreh IJ, Chung M, et al. An evidence review of active surveillance in men with localized prostate cancer. Evid Rep Technol Assess (Full Rep). Dec 2011;AHRQ Publication No. 12-E003-EF, Rockville, MD: Agency for Research and Quality.(204):1-341. PMID 23126653
  • Thompson I, JB T, Aus G ea. American Urological Association guideline for management of clinically localized prostate cancer 2007 update.
  • Whitson JM, Carroll PR. Active surveillance for early-stage prostate cancer: defining the triggers for intervention.J Clin Oncol. Jun 10 2010;28(17):2807-2809. PMID 20439633
  • Albertsen PC. Treatment of localized prostate cancer: when is active surveillance appropriate? Nat Rev Clin Oncol. Jul 2010;7(7):394-400. PMID 20440282
  • Wu CL, Schroeder BE, Ma XJ, et al. Development and validation of a 32-gene prognostic index for prostate cancer progression. Proc Natl Acad Sci U S A. Apr 9 2013;110(15):6121-6126. PMID 23533275
  • Spans L, Clinckemalie L, Helsen C, et al. The genomic landscape of prostate cancer. Int J Mol Sci. 2013;14(6):10822-10851. PMID 23708091
  • Schoenborn JR, Nelson P, Fang M. Genomic profiling defines subtypes of prostate cancer with the potential for therapeutic stratification. Clin Cancer Res. Aug 1 2013;19(15):4058-4066. PMID 23704282
  • Huang J, Wang JK, Sun Y. Molecular pathology of prostate cancer revealed by next-generation sequencing: opportunities for genome-based personalized therapy. Curr Opin Urol. May 2013;23(3):189-193. PMID 23385974
  • Yu YP, Song C, Tseng G, et al. Genome abnormalities precede prostate cancer and predict clinical relapse. Am J Pathol. Jun 2012;180(6):2240-2248. PMID 22569189
  • Agell L, Hernandez S, Nonell L, et al. A 12-gene expression signature is associated with aggressive histological in prostate cancer: SEC14L1 and TCEB1 genes are potential markers of progression. Am J Pathol. Nov 2012;181(5):1585-1594. PMID 23083832
  • Klein EA, Yousefi K, Haddad Z, et al. A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. Eur Urol. Apr 2015;67(4):778-786. PMID 25466945
  • Den RB, Yousefi K, Trabulsi EJ, et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. Mar 10 2015;33(8):944-951. PMID 25667284
  • Blue Cross and Blue Shield Association Technology Evaluation Center (TEC). Gene Expression Profiling for High-Risk Prostate Cancer Management Post-Radical Prostatectomy TEC Assessments 2015.
  • Warf MB, Reid JE, Brown KL, et al. Analytical validation of a cell cycle progression signature used as a prognostic marker in prostate cancer. J Mol Biomark Diagn. 2015;6(4).
  • Cuzick J, Stone S, Fisher G, et al. Validation of an RNA cell cycle progression score for predicting death from prostate cancer in a conservatively managed needle biopsy cohort. Br J Cancer. Jul 28 2015;113(3):382-389. PMID 26103570
  • Cuzick J, Berney DM, Fisher G, et al. Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort. Br J Cancer. Mar 13 2012;106(6):1095-1099. PMID 22361632
  • Pepe MS, Feng Z, Janes H, et al. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J Natl Cancer Inst. Oct 15 2008;100(20):1432-1438. PMID 18840817
  • Cuzick J, Swanson GP, Fisher G, et al. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol. Mar 2011;12(3):245-255. PMID 21310658
  • Cooperberg MR, Simko JP, Cowan JE, et al. Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort. J Clin Oncol. Apr 10 2013;31(11):1428-1434. PMID 23460710
  • Bishoff JT, Freedland SJ, Gerber L, et al. Prognostic utility of the cell cycle progression score generated from biopsy in men treated with prostatectomy. J Urol. Aug 2014;192(2):409-414. PMID 24508632
  • Crawford ED, Scholz MC, Kar AJ, et al. Cell cycle progression score and treatment decisions in prostate cancer: results from an ongoing registry. Curr Med Res Opin. Jun 2014;30(6):1025-1031. PMID 24576172
  • Shore N, Concepcion R, Saltzstein D, et al. Clinical utility of a biopsy-based cell cycle gene expression assay in localized prostate cancer. Curr Med Res Opin. Apr 2014;30(4):547-553. PMID 24320750
  • Knezevic D, Goddard AD, Natraj N, et al. Analytical validation of the Oncotype DX prostate cancer assay - a clinical RT-PCR assay optimized for prostate needle biopsies. BMC Genomics. 2013;14:690. PMID 24103217
  • Klein EA, Cooperberg MR, Magi-Galluzzi C, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol. Sep 2014;66(3):550-560. PMID 24836057
  • Cullen J, Rosner IL, Brand TC, et al. A Biopsy-based 17-gene Genomic Prostate Score Predicts Recurrence After Radical Prostatectomy and Adverse Surgical Pathology in a Racially Diverse Population of Men with Clinically Low- and Intermediate-risk Prostate Cancer. Eur Urol. Jul 2015;68(1):123-131. PMID 25465337
  • Badani KK, Kemeter MJ, Febbo PG. The Impact of a Biopsy Based 17-Gene Genomic Prostate Score on Treatment Recommendations in Men with Newly Diagnosed Clinically Prostate Cancer Who are Candidates For Active Surveillance. Urology Practice. 2015;2:181-189.
  • Shipitsin M, Small C, Giladi E, et al. Automated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality. Proteome Sci. 2014;12:40. PMID 25075204
  • Blume-Jensen P, Berman DM, Rimm DL, et al. Development and clinical validation of an in situ biopsy-based multimarker assay for risk stratification in prostate cancer. Clin Cancer Res. Jun 1 2015;21(11):2591-2600. PMID 25733599
  • Abdueva D, Wing M, Schaub B, et al. Quantitative expression profiling in formalin-fixed paraffin-embedded samples by affymetrix microarrays. J Mol Diagn. Jul 2010;12(4):409-417. PMID 20522636
  • Den RB, Feng FY, Showalter TN, et al. Genomic prostate cancer classifier predicts biochemical failure and  metastases in patients after postoperative radiation therapy. Int J Radiat Oncol Biol Phys. Aug 1 2014;89(5):1038-1046. PMID 25035207
  • Cooperberg MR, Davicioni E, Crisan A, et al. Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort. Eur Urol. Feb 2015;67(2):326-333. PMID 24998118
  • Ross AE, Feng FY, Ghadessi M, et al. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. Mar 2014;17(1):64-69. PMID 24145624
  • Karnes RJ, Bergstralh EJ, Davicioni E, et al. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. J Urol. Dec 2013;190(6):2047-2053. PMID 23770138
  • Erho N, Crisan A, Vergara IA, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS One. 2013;8(6):e66855. PMID 23826159
  • Ross AE, Johnson MH, Yousefi K, et al. Tissue-based Genomics Augments Post-prostatectomy Risk Stratification in a Natural History Cohort of Intermediate- and High-Risk Men. Eur Urol. Jun 6 2015. PMID 26058959
  • Michalopoulos SN, Kella N, Payne R, et al. Influence of a genomic classifier on post-operative treatment decisions in high-risk prostate cancer patients: results from the PRO-ACT study. Curr Med Res Opin. Aug 2014;30(8):1547-1556. PMID 24803160
  • Thompson IM, Valicenti RK, Albertsen P, et al. Adjuvant and salvage radiotherapy after prostatectomy: AUA/ASTRO Guideline. J Urol. Aug 2013;190(2):441-449. PMID 23707439
  • Simon RM, Paik S, Hayes DF. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst. Nov 4 2009;101(21):1446-1452. PMID 19815849
  • Cooperberg M, Sinko J, Cowan J. et. al. Validation of Cell-Cycle Progression Gene Panel to Improve Risk Stratification in a Contemporary Prostatectomy Cohort. Journal of Clinical Oncology Volume 31 Number 11 April 10 2013
  • Shipitsin M, Small C, Choudhury S. et. al. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. British Journal of Cancer 2014 111. 1201-1212
  • National Comprehensive Cancer Network (NCCN) Version 1.2020 Prostate Cancer
  • Prolaris Prostate Cancer Testing (Myriad Genetics).
  • Oncotype DX Prostate Cancer Assay (Genomic Health).
  • ProMark Protein Biomarker Metamark Genetics). 
  • Decipher (GenomeDX Biosciences).
  • Sanda M, Chen R, Crispino T, et. al. Clinically Localized Prostate Cancer AUA/ASTRO/SUO Guideline. April 2017
  • American Cancer Society. Key Statistics for Prostate Cancer. January 2017.
  • ECRI. Technology Trend News. Half of Laboratory-Developed Tests on FDA’s Hit List are for Cancer. Published December 2015.
  • UpToDate. Molecular Prognostic Tests for Prostate Cancer. Ashely Ross M.D., PhD, Anthony V D’Amico M.D., PhD, Stephen Freeland M.D. Topic last updated April 20, 2017.
  • Hamdy FC, Donovan JL, Lane JA, et. al. 10-year outcomes after monitoring, surgery, or radiotherapy for localized prostate cancer. N Engl J Med 2016 Oct 13;375(15):1415-1424. PMID 27626136
  • Sommariva S, Tarricone R, Lazzeri M, et. al. Prognostic value of the cell cycle progression score in patients with prostate cancer: a systematic review and meta-analysis. Eur Urol 2016 Jan 69(1):107-15. PMID 25481455
  • Shore ND, Kella N, Moran B, et. al. Impact of the cell cycle progression test on physician and patient treatment selection for localized prostate cancer. J Urol 2016 Mar 195(3):612-8. PMID 26403586
  • Brand TC, Zhang N, Crager MR, et. al. Patient-specific meta-analysis of 2 clinical validation studies to predict pathologic outcomes in prostate cancer using the 17 gene genomic prostate score. PMID 26723180
  • Koch MO, Cho JS, Kaimakliotis HZ, et. al. Use of the cell cycle progression (CCP) score for predicting systemic disease and response to radiation of biochemical recurrence. Cancer Biomark 2016 Jun 7;17(1):83-8. PMID 27314296
  • Klein EA, Yousefi K, Haddad Z, et. al. A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. PMID 25466945
  • Freeland SJ, Choeumg V, Howard L, et. al. Utilization of a genomic classifier for prediction of metastasis following salvage radiation therapy after radical prostatectomy. Eur Urol 2016 Oct;70(4):588-596. PMID 26806658
  • Glass AG, Leo MC, Haddad Z, et.al. Validation of a genomic classifier for predicting post-prostatectomy recurrence in a community based health care setting. J Urol 2016 Jun;195(6):1748-53. PMID 26626216
  • Klein EA, Haddad Z, Yousefi K, et. al. Decipher genomic classifier measured on prostate biopsy predicts metastasis risk. Urology 2016 Apr 90:148-52. PMID 26809071
  • Lobo JM, Dicker AP, Buerki C, et.al. Evaluating the clinical impact of a genomic classifier in prostate cancer using individualized decision analysis. PLoS One 2015 Apr 2;10(3):e0116866. PMID 25837660
  • Nguyen PL, Shin H, Yousefi K, et. al. Impact of a genomic classifier of metastatic risk on post-prostatectomy treatment recommendations by radiation oncologists and urologists. Urology 2015 Jul;86(1):35-40. PMID 26142578
  • Badani KK, Thompson DJ, Brown G, et. al. Effect of genomic classifer test on clinical practice decision for patients with high risk prostate cancer after surgery. BJU Int 2015 Mar;115(3):419-29. PMID 24784420
  • Ross AE, Den RB, Yousefi K, et. al. Efficacy of post-operative radiation in prostatectomy cohort adjusted for clinical and genomic risk. Prostate Cancer Prostatic Dis 2016 Sep;19(3):277-82. PMID 27136742
  • Yamoah K, Johnson MH, Choeurng V, et. al. Novel biomarker signature that may predict aggressive disease in African American men with prostate cancer. J Clin Oncol 2015 Sep 1;33(25):2789-96. PMID 26195723
  • Whalen M, Hackert V, Rothberg M, et. al. Prospective correlation between likelihood of favorable pathology on the 17 gene genomic prostate score and actual pathological outcomes at radical prostatectomy. Urology Practice September 2016 Volume 3, Issue 5, Pages 379-386
  • Dall’Era M, Maddala T, Polychronopoulos L, et. al. Utility of the Oncotype DX Prostate Cancer Assay in clinical practice for treatment selection in men newly diagnosed with prostate cancer: A retrospective chart review analysis. Urology Practice November 2015 Volume 2,Issue 6,Pages 343-348
  • Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin. Jan 2017;67(1):7-30. PMID 28055103       
  • Brimo F, Montironi R, Egevad L, et al. Contemporary grading for prostate cancer: implications for patient care. Eur Urol. May 2013;63(5):892-901. PMID 23092544
  • Eylert MF, Persad R. Management of prostate cancer. Br J Hosp Med (Lond). Feb 2012;73(2):95-99. PMID 22504752      
  • Thompson IM, Jr., Goodman PJ, Tangen CM, et al. Long-term survival of participants in the prostate cancer prevention trial. N Engl J Med. Aug 15 2013;369(7):603-610. PMID 23944298
  • Simon RM, Paik S, Hayes DF. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst. Nov 4 2009;101(21):1446-1452. PMID 19815849
  • Borley N, Feneley MR. Prostate cancer: diagnosis and staging. Asian J Androl. Jan 2009;11(1):74-80. PMID 19050692
  • Nam RK, Cheung P, Herschorn S, et al. Incidence of complications other than urinary incontinence or erectile dysfunction after radical prostatectomy or radiotherapy for prostate cancer: a population-based cohort study. Lancet Oncol. Feb 2014;15(2):223-231. PMID 24440474 
  • Wilt TJ, Brawer MK, Jones KM, et al. Radical prostatectomy versus observation for localized prostate cancer. N Engl J Med. Jul 19 2012;367(3):203-213. PMID 22808955
  • Wilt TJ, Jones KM, Barry MJ, et al. Follow-up of prostatectomy versus observation for early prostate cancer. N Engl J Med. Jul 13 2017;377(2):132-142. PMID 28700844
  • van den Bergh RC, Korfage IJ, Roobol MJ, et al. Sexual function with localized prostate cancer: active surveillance vs radical therapy. BJU Int. Oct 2012;110(7):1032-1039. PMID 22260273
  • Johansson E, Steineck G, Holmberg L, et al. Long-term quality-of-life outcomes after radical prostatectomy or watchful waiting: the Scandinavian Prostate Cancer Group-4 randomised trial. Lancet Oncol. Sep 2011;12(9):891-899. PMID 21821474
  • Kattan MW, Eastham JA, Wheeler TM, et al. Counseling men with prostate cancer: a nomogram for predicting the presence of small, moderately differentiated, confined tumors. J Urol. Nov 2003;170(5):1792-1797. PMID 14532778
  • Cooperberg MR, Freedland SJ, Pasta DJ, et al. Multiinstitutional validation of the UCSF cancer of the prostate risk assessment for prediction of recurrence after radical prostatectomy. Cancer. Nov 15 2006;107(10):2384-2391. PMID 17039503
  • Chen RC, Chang P, Vetter RJ, et al. Recommended patient-reported core set of symptoms to measure in prostate cancer treatment trials. J Natl Cancer Inst. Jul 2014;106(7). PMID 25006192
  • Sommariva S, Tarricone R, Lazzeri M, et al. Prognostic value of the Cell Cycle Progression Score in patients with prostate cancer: a systematic review and meta-analysis. Eur Urol. Jan 2016;69(1):107-115. PMID 25481455
  • Cuzick J, Swanson GP, Fisher G, et al. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol. Mar 2011;12(3):245-255. PMID 21310658
  • Shore N, Concepcion R, Saltzstein D, et al. Clinical utility of a biopsy-based cell cycle gene expression assay in localized prostate cancer. Curr Med Res Opin. Apr 2014;30(4):547-553. PMID 24320750
  • Albala D, Kemeter MJ, Febbo PG, et al. Health Economic Impact and Prospective Clinical Utility of Oncotype DX(R) Genomic Prostate Score. Rev Urol. Nov 2016;18(3):123-132. PMID 27833462
  • Eure G, Germany R, Given R, et al. Use of a 17-Gene Prognostic Assay in Contemporary Urologic Practice: Results of an Interim Analysis in an Observational Cohort. Urology. Sep 2017;107:67-75. PMID 28454985
  • Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. Nov-Dec 2006;26(6):565-574. PMID 17099194
  • Den RB, Yousefi K, Trabulsi EJ, et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. Mar 10 2015;33(8):944-951. PMID 25667284
  • Thompson IM, Jr., Tangen CM, Paradelo J, et al. Adjuvant radiotherapy for pathologically advanced prostate cancer: a randomized clinical trial. Jama. Nov 15 2006;296(19):2329-2335. PMID 17105795
  • Bolla M, van Poppel H, Tombal B, et al. Postoperative radiotherapy after radical prostatectomy for high-risk prostate cancer: long-term results of a randomised controlled trial (EORTC trial 22911). Lancet. Dec 08 2012;380(9858):2018-2027. PMID 23084481
  • Wiegel T, Bottke D, Steiner U, et al. Phase III postoperative adjuvant radiotherapy after radical prostatectomy compared with radical prostatectomy alone in pT3 prostate cancer with postoperative undetectable prostate-specific antigen: ARO 96-02/AUO AP 09/95. J Clin Oncol. Jun 20 2009;27(18):2924-2930. PMID 19433689
  • Stephenson AJ, Scardino PT, Kattan MW, et al. Predicting the outcome of salvage radiation therapy for recurrent prostate cancer after radical prostatectomy. J Clin Oncol. May 20 2007;25(15):2035-2041. PMID 17513807
  • Stephenson AJ, Scardino PT, Eastman JA, et. al. Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy. J Clin Oncol 2005 October 1; 23(28):7005-7012  
  • Cooperberg MR, Hilton JF, Carroll PR. The CAPRA-S score: A straightforward tool for improved prediction of outcomes after radical prostatectomy. Cancer. Nov 15 2011;117(22):5039-5046. PMID 21647869
  • Freedland SJ, Gerber L, Reid J, et al. Prognostic utility of cell cycle progression score in men with prostate cancer after primary external beam radiation therapy. Int J Radiat Oncol Biol Phys. Aug 1 2013;86(5):848-853. PMID 23755923
  • Karnes RJ, Choeurng V, Ross AE, et al. Validation of a Genomic Risk Classifier to Predict Prostate Cancer-specific Mortality in Men with Adverse Pathologic Features. Eur Urol. Apr 08 2017. PMID 28400167
  • Ross AE, Den RB, Yousefi K, et al. Efficacy of post-operative radiation in a prostatectomy cohort adjusted for clinical and genomic risk. Prostate Cancer Prostatic Dis. Sep 2016;19(3):277-282. PMID 27136742
  • Spratt DE, Yousefi K, Deheshi S, et al. Individual patient-level meta-analysis of the performance of the decipher genomic classifier in high-risk men after prostatectomy to predict development of metastatic disease. J Clin Oncol. Jun 20 2017;35(18):1991-1998. PMID 28358655
  • Badani K, Thompson DJ, Buerki C, et al. Impact of a genomic classifier of metastatic risk on postoperative treatment recommendations for prostate cancer patients: a report from the DECIDE study group. Oncotarget. Apr 2013;4(4):600-609. PMID 23592338
  • Gore JL, du Plessis M, Santiago-Jimenez M, et al. Decipher test impacts decision making among patients considering adjuvant and salvage treatment after radical prostatectomy: Interim results from the Multicenter Prospective PRO-IMPACT study. Cancer. Aug 01 2017;123(15):2850-2859. PMID 28422278
  • Prensner JR, Zhao S, Erho N, et al. RNA biomarkers associated with metastatic progression in prostate cancer: a multi-institutional high-throughput analysis of SChLAP1. Lancet Oncol. Dec 2014;15(13):1469-1480. PMID 25456366
  • Tomlins SA, Alshalalfa M, Davicioni E, et al. Characterization of 1577 primary prostate cancers reveals novel biological and clinicopathologic insights into molecular subtypes. Eur Urol. Oct 2015;68(4):555-567. PMID 25964175
  • Barocas D. Alverez J, Resnick M, et. al. Association between radiation therapy, surgery or observation for localized prostate cancer and patient reported outcomes after 3 years. JAMA 2017;317(1):1126-1140
  • Chen R, Ramsanker B, Meyer AM, et. al. Association between choice of radical prostatectomy, external beam radiotherapy, brachytherapy, or active surveillance and patient reported quality of life among men with localized prostate cancer. JAM 2017;317(11):1141-1150
  • Cooperberg M, Pasta D, Elkin E, et. al. The University of California, San Francisco Cancer of the Prostate Risk Assessment Score: A straightforward and reliable preoperative predictor of disease recurrence after radical prostatectomy. The Journal of Urology Vol. 173 1938-1942 June 2005
  • Donavan JL, Hamdy FC, Lane JA, et. al. Patient reported outcomes after monitoring, surgery, or radiotherapy for prostate cancer. N Engl J Med October 2016 375;15
  • Draisma F, Etzioni R, Tsodikov A, et. al. Lead time and over diagnosis in prostate specific antigen screening: importance of methods and context. Journal of the National Cancer Institute Vol. 101 Issue 6 March 18, 2009
  • Garzotto M. Is low-risk prostate cancer more indolent in younger patients? Journal of Clinical Oncology Volume 35 Number 17 June 2017
  • Jeldres C, Cullen J, Hurwitz L, et.al. Prospective quality of life outcomes for low-risk prostate cancer: active surveillance versus radical prostatectomy. Cancer July 15; 121(14):2465-2473
  • Leapman M, Cowan J, Nguyen H, et. al. Active surveillance in younger men with prostate cancer. Journal of Clinical Oncology Volume 35 Number 17 June 2017   
  • Tosoian J, Mamawala M, Epstein J, et. al. Intermediate and longer-term outcomes from a prospective active surveillance program for favorable risk prostate cancer. Journal of Clinical Oncology Volume 33 2015
  • MoIDX: Oncotype Dx Genomic Prostate Score for Men with Favorable Intermediate Risk Prostate Cancer. Local Coverage Determination (L37262)
  • MoIDX Oncotype DX Prostate Cancer Assay Genomic Health (L36153)
  • MoIDX: ProMark Risk Score. Local Coverage Determination (L36665)
  • MoIDX: Decipher Prostate Cancer Classifier Assay. Local Coverage Determination (L35868) 
  • MoIDX Decipher Biopsy Prostate Cancer Classifier Assay for Men with Very Low and Low Risk Disease (L37785)
  • MoIDX Decipher Biopsy Prostate Cancer Classifier Assay for Men with Favorable Intermediate Risk Disease: Proposed LCD (DL38035) 
  • MoIDX: Prolaris Prostate Cancer Genomic Assay. Local Coverage Determination (L35869)
  • MoIDX: Prolaris Prostate Cancer Genomic Assay for Men with Favorable Intermediate Risk Disease (L37043)
  • Lin DW, Crawford ED, Keane T, et al. Identification of men with low-risk biopsy-confirmed prostate cancer as candidates for active surveillance. Urol Oncol. Jun 2018;36(6):310.e317-310.e313. PMID 29655620
  • Van Den Eeden SK, Lu R, Zhang N, et al. A biopsy-based 17-gene Genomic Prostate Score as a predictor of metastases and prostate cancer death in surgically treated men with clinically localized disease. Eur Urol. Jan 2018;73(1):129-138. PMID 28988753
  • Salmasi A, Said J, Shindel AW, et al. A 17-gene genomic prostate score assay provides independent information on adverse pathology in the setting of combined multiparametric magnetic resonance imaging fusion targeted and systematic prostate biopsy. J Urol. Mar 7 2018. PMID 29524506
  • Hwang WL, Tendulkar RD, Niemierko A, et al. Comparison between adjuvant and early-salvage postprostatectomy radiotherapy for prostate cancer with adverse pathological features. JAMA Oncol. May 10 2018;4(5):e175230. PMID 29372236
  • Karnes RJ, Choeurng V, Ross AE, et al. Validation of a genomic risk classifier to predict prostate cancer-specific mortality in men with adverse pathologic features. Eur Urol. Feb 2018;73(2):168-175. PMID 28400167
  • Spratt DE, Dai DLY, Den RB, et al. Performance of a prostate cancer genomic classifier in predicting metastasis in men with prostate-specific antigen persistence postprostatectomy. Eur Urol. Jul 2018;74(1):107-114. PMID 29233664
  • Sanda MG, Cadeddu JA, Kirkby E, et al. Clinically Localized Prostate Cancer: AUA/ASTRO/SUO Guideline. Part I: Risk Stratification, Shared Decision Making, and Care Options. J Urol. Dec 15 2017. PMID 29203269
  • Sanda MG, Cadeddu JA, Kirkby E, et al. Clinically Localized Prostate Cancer: AUA/ASTRO/SUO Guideline. Part II: Recommended Approaches and Details of Specific Care Options. J Urol. Apr 2018;199(4):990-997. PMID 29331546
  • Gore JL, du Plessis M, Santiago-Jimenez M, et al. Decipher test impacts decision making among patients considering adjuvant and salvage treatment after radical prostatectomy: Interim results from the Multicenter Prospective PRO-IMPACT study. Cancer. Aug 01 2017;123(15):2850-2859. PMID 28422278
  • Nguyen PL, Haddad Z, Ross AE, et. al. Ability of a genomic classifier to predict metastasis and prostate cancer-specific mortality after radiation or surgery base don needle biopsy specimens. Eur Urol 2017;72(5):845-852
  • Nguyen PL, Martin NE, Choeurng V, et. al. Utilization of biopsy based genomic classifier to predict distant metastasis after definitive radiation and short course ADT for intermediate and high risk prostate cancer. Prostate Cancer Prostatic Dis 2017 Jun;20(2):186-192
  • Roth JA, Ramsey SD, Carlson JJ. Cost effectiveness of a biopsy based 8 – protein prostate cancer prognostic assay to optimize treatment decision making in Gleason 3+3 and 3+4 early stage prostate cancer. The Oncologist 2015;20:1-10
  • Tomlins SA, Alshalalfa M, Davicioni E, et. al. Characterization of 1,577 primary prostate cancers reveals novel biological and clinicopathological insights into molecular subtypes. Eur Ruol 2015 October; 68(4):555-567
  • Kim HL, Li P, Huang HC, et. al. Validation of the Decipher Test for predicting adverse pathology in candidates for prostate cancer active surveillance. Prostate Cancer and Prostatic Diseases (2019) 22:399-405
  • Spratt DE, Zhang J, Santiago-Jimenez M, et. al. Development and validation of a novel integrated clinical-genomic risk group classification for localized prostate cancer. Journal of Clinical Oncology Volume 36, Number 6, February 20, 2018
  • Moschini M, Spahn M, Mattei A, et. al. Incorporation of tissue-based genomic biomarkers into localized prostate cancer clinics. BMC Medicine 2016 14:67
  • Bostrom PJ, Bjartell AS, Catto JWF, et. al. Genomic predictors of outcome in prostate cancer. European Urology 68 (6) pp 1033-1044
  • Eggener S, Rumble RB, Armstrong A, et.al. Molecular Biomarkers in Localized Prostate Cancer: ASCO Guidelines. J Clin Oncol 38:1474-1494 2019

 

Policy History:

  • May 2020 - Annual Review, Policy Renewed
  • December 2019 - Interim Review, Policy Revised
  • May 2019 - Annual Review, Policy Revised
  • May 2018 - Annual Review, Policy Revised
  • May 2017 - Annual Review, Policy Revised
  • June 2016 - New medical policy

Wellmark medical policies address the complex issue of technology assessment of new and emerging treatments, devices, drugs, etc.   They are developed to assist in administering plan benefits and constitute neither offers of coverage nor medical advice. Wellmark medical policies contain only a partial, general description of plan or program benefits and do not constitute a contract. Wellmark does not provide health care services and, therefore, cannot guarantee any results or outcomes. Participating providers are independent contractors in private practice and are neither employees nor agents of Wellmark or its affiliates. Treating providers are solely responsible for medical advice and treatment of members. Our medical policies may be updated and therefore are subject to change without notice.

 

*CPT® is a registered trademark of the American Medical Association.