Gene Expression Analysis for Prostate Cancer

Original Issue Date (Created): 10/1/2014 Most Recent Review Date (Revised): 6/2/2015

Effective Date: 8/1/2015

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Gene expression analysis to guide management of prostate cancer is considered

investigational in all situations. There is insufficient evidence to support a conclusion concerning the health outcomes or benefits associated with this procedure.

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[N] = No product variation, policy applies as stated

[Y] = Standard product coverage varies from application of this policy, see below

Note: Medicare National Coverage

The Prolaris test will be denied as not reasonable and necessary regardless of the diagnosis billed

(http://www.findacode.com/medicare/policies-guidelines/display-medicare-info.php?type=ARTICLE&type_id=52156

No national coverage determination for the Oncotype Dx® Prostate test was identified. * Refer to FEP Medical Policy Manual MP-2.04.111 Microarray-based Gene Expression Profile Analysis for Prostate Cancer Management. The FEP Medical Policy manual can be found at: www.fepblue.org

POLICY PRODUCT VARIATIONS DESCRIPTION/BACKGROUND

RATIONALE DEFINITIONS BENEFIT VARIATIONS

DISCLAIMER CODING INFORMATION REFERENCES

POLICY HISTORY

[N] Capital Cares 4 Kids [N] Indemnity

[N] PPO [N] SpecialCare

[N] HMO [N] POS

[N] SeniorBlue HMO [Y] FEP PPO*

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Gene expression profile analysis has been proposed as a means to risk-stratify patients with low-risk prostate cancer, diagnosed by needle biopsy, to guide treatment decisions.

Prostate cancer is the second most common cancer diagnosed among men in the U.S.

According to the National Cancer Institute (NCI), nearly 240,000 new cases are expected to be diagnosed in the U.S. in 2013, and associated with around 30,000 deaths. Autopsy studies in the pre-prostate-specific antigen (PSA) screening era have identified incidental cancerous foci in 30% of men 50 years of age, with incidence reaching 75% at age 80 years. (1) However, NCI Surveillance Epidemiology and End Results data show age-adjusted cancer-specific mortality rates for men with prostate cancer have declined from 40 per 100,000 in 1992 to 22 per 100,000 in 2010. This decline has been attributed to a combination of earlier detection via PSA screening and improved therapies.

Localized prostate cancers may appear very similar clinically at diagnosis.(2) However, they often exhibit diverse risk of progression that may not be captured by accepted clinical risk categories (eg, D’Amico criteria) or prognostic tools that are based on clinical findings, including PSA titers, Gleason grade, or tumor stage.(3-7) 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%(8,9) to 20%(10) to perhaps 27% at 20-year follow-up.(11) Among elderly men (70 years or more) with this type of low-risk disease, comorbidities typically supervene as a cause of death; these men will die with prostate cancer present, rather than from the cancer. Other very similar-appearing low-risk tumors may progress unexpectedly rapidly, quickly disseminating and becoming incurable.

The divergent behavior of localized prostate cancers creates uncertainty whether or not to treat immediately.(12,13) A patient may choose definitive treatment upfront.(14) Surgery (radical prostatectomy), external-beam radiation therapy (EBRT), brachytherapy, high-intensity-focused ultrasound, systemic chemotherapy, hormonal therapy, cryosurgery, or combinations are used to treat patients with prostate cancer.(13,15) Complications associated with those treatments most commonly reported (radical prostatectomy, EBRT) and with the greatest variability were incontinence (0-73%) and other genitourinary toxicities (irritative and obstructive symptoms); hematuria (typically 5% or less); 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%).(15)

American Urological Association (AUA) Guidelines suggest patients with low- and

intermediate-risk disease have the option of “active surveillance”, taking into account patient age, patient preferences, and health conditions related to urinary, sexual, and bowel

function.(15) With this approach 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.(16,17)

Given the unpredictable behavior of early prostate cancer, additional prognostic methods to biologically stratify this disease are under investigation. These include microarray-based gene expression profiling, which refers to analysis of mRNA expression levels of many genes simultaneously in a tumor specimen.(18-23) Two microarray-based gene expression profiling tests are now offered, intended to biologically stratify prostate cancers: Prolaris® (Myriad Genetics, Salt Lake City, UT) and Oncotype Dx® Prostate Cancer Assay (Genomic Health, Redwood City, CA). Both use archived tumor specimens as the mRNA source, reverse transcriptase polymerase chain reaction amplification, and the TaqMan low-density array platform (Applied Biosystems, Foster City, CA). Prolaris® is used to quantify expression levels of 31 cell cycle progression (CCP) genes and 15 housekeeper genes to generate a CCP score. Oncotype Dx® Prostate is 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 CCP score or GPS are combined in proprietary algorithms with clinical risk criteria (PSA, Gleason grade, tumor stage) to generate new risk categories (ie, reclassification) intended to reflect biological indolence or aggressiveness of individual lesions, and thus inform management decisions.

Regulatory Status

Neither Prolaris® nor Oncotype Dx® Prostate Cancer Assay is cleared for marketing by the U.S. Food and Drug Administration (FDA). Each is available under the auspices of the Clinical Laboratory Improvement Act (CLIA). Clinical laboratories may develop and validate tests in-house (laboratory-developed tests [LDTs]) and market them as a laboratory service; LDTs must meet the general regulatory standards of the CLIA. Laboratories that offer LDTs must be licensed by CLIA for high-complexity testing.

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This policy was based initially on a 2013 TEC Assessment.24 The most recent literature review is through September 30, 2014. Full-length publications were sought that described the analytic validity, clinical validity, and clinical utility of either Prolaris® or Oncotype Dx® Prostate gene expression profiling. We reviewed evidence on the use of either test to predict the aggressiveness (or indolence) of newly diagnosed (by needle biopsy), localized prostate cancer

.

Analytic Validity

Analytic validity is the technical accuracy of a test in detecting a mutation that is present or in excluding a mutation that is absent. Prolaris® Published data on the analytic validity of Prolaris® was not identified. Information is available on the performance of the TaqMan array platform (Applied Biosystems, Foster City, CA) used in Prolaris® and Oncotype Dx® Prostate through the MicroArray Quality Control (MAQC) project.25 In the MAQC project,

initiated and led by FDA scientists, expression data on 4 titration pools from 2 distinct reference RNA samples were generated at multiple test sites on 7 microarray-based and 3 alternative

technology platforms, including TaqMan. According to the investigators, the results provide a framework to assess the potential of array technologies as a tool to provide reliable gene expression data for clinical and regulatory purposes. The results showed very similar performance across platforms, with a median coefficient of variation of 5% to 15% for the quantitative signal and 80% to 95% concordance for the qualitative detection call between sample replicates.

Oncotype Dx® Prostate

Knezevic et al reported on the analytic validity of Oncotype Dx® Prostate.26 Estimates of analytic precision and reproducibility were derived from analysis of RNA prepared from 10 microdissected prostate tumor samples obtained by needle biopsy. Individual Gleason scores were assigned using the 2005 International Society of Urological Pathology Consensus

guidelines.27 The results showed that the assay could accurately measure expression of the 12 cancer-related and 5 reference genes over a range of absolute RNA inputs (0.005-320 ng); the limit of detection in a sample was 0.5 ng/L. The analytic accuracy showed average variation of less than 9.7% across all samples at RNA inputs typical of needle biopsy specimens. The

amplification efficiency for the 17 genes in the test ranged from 88% to 100%, with a median of 93% (SD=6%) for all 17 genes in the assay. Analytic precision was assessed by examining variability between replicate results obtained using the same mRNA input. Reproducibility was measured by calculating both within and between mRNA input variation.

A low input level of 5 ng mRNA was used to reflect the lowest 2.5 percentile of a tumor sample of 0.023 cm3. When converted to GPS units (unit measure for reporting test results), the standard deviation for analytic precision was 1.86 GPS units (95% confidence interval [CI], 1.60 to 2.20) on the 100-unit scale. The standard deviation for reproducibility was 2.11 GPS units (95% CI, 1.83 to 2.50) on the 100-point scale.

Section Summary

The analytic validity of gene expression analysis for prostate cancer management using Prolaris® is indirectly suggested by results from the MAQC project, but remains to be

specifically established. The study by Knezevic et al provides sufficient evidence to establish the analytic validity of Oncotype Dx® Prostate.26

Clinical Validity

Clinical validity reflects the diagnostic performance of a test (sensitivity, specificity, positive and negative predictive values) in detecting clinical disease.

Prolaris®

One full-length, peer-reviewed article reports results of a validation study of Prolaris® to determine its prognostic value for prostate cancer death in a conservatively managed needle biopsy cohort.28 Cuzick et al did not state whether this study adheres to the PRoBE

al for an adequate biomarker validation study.29 Cuzick et al note that the cell cycle expression data were read blind to all other data, which conforms to the criteria; however, patients were identified retrospectively from tumor registries, and there were no case control subjects, which does not conform.

Patients were identified from 6 cancer registries in Great Britain and were included if they had clinically localized prostate cancer that was diagnosed by needle biopsy between 1990 through 1996; were younger than 76 years at diagnosis; had a baseline prostate-specific antigen (PSA) measurement; and were conservatively managed. Potentially eligible patients who underwent radical prostatectomy, died, or showed evidence of metastatic disease within 6 months of diagnosis were excluded. Those who received hormone therapy before diagnostic biopsy also were excluded. The original biopsy specimens were retrieved and centrally reviewed by a panel of expert urological pathologists to confirm the diagnosis and, where necessary, to reassign Gleason scores by use of a contemporary and consistent interpretation of the Gleason scoring system.30 Tumor cells were microdissected from needle biopsy blocks, the amount determined by the length of the cancer available in the core and to enable preservation of any remaining cancer tissue for profiling studies. A Cell Cycle Progression (CCP) score, consisting of

expression levels of 31 predefined cell cycle progression genes and 15 housekeeper genes, was generated using TaqMan low-density arrays. The values of each of the 31 CCP genes were normalized by subtraction of the average of up to 15 nonfailed housekeeper genes for that replicate.

Of 776 patients diagnosed by needle biopsy and for which a section was available to review histology, needle biopsies were retrieved for 527 (68%), 442 (84%) of which had adequate material to assay. Among the 442, a proportion, 349 (79%), produced a CCP score and had complete baseline and follow-up information. The median potential follow-up time was 11.8 years, during which a total 90 deaths from prostate cancer occurred within 2799 person-years of actual follow-up. The main assessment of the study was a univariate analysis of the association between death from prostate cancer and the CCP score.28 A further predefined assessment of the added prognostic information after adjustment for the baseline variables was also undertaken. The primary end point was time to death from prostate cancer. A number of covariates were evaluated: centrally reviewed Gleason primary grade and score; baseline PSA value; clinical stage; extent of disease (percent of positive cores); age at diagnosis; Ki-67

The median CCP score was 1.03 (interquartile range, 0.41-1.74). The primary univariate analysis suggests that a 1-unit increase in CCP score was associated with a 2-fold increase in the risk of dying from prostate cancer. In preplanned multivariate analyses, extent of disease, age, clinical stage, and use of hormones had no statistically significant effect on risk; only the Gleason score and PSA remained in the final model. Further exploratory multivariate modeling to produce a combined score, including CCP, Gleason score, and PSA level, suggested a strong, predominant nonlinear influence of the CCP score in predicting the risk of death from prostate cancer

(p=0.008). Cuzick et al suggest this combined score provides additional discriminatory information to help identify low-risk patients who could be safely managed by active surveillance. For example, among patients with a Gleason score of 6, for whom uncertainty exists as to the appropriate management approach, the predicted 10-year prostate cancer The median CCP score was 1.03 (interquartile range, 0.41-1.74). The primary univariate analysis suggests that a 1-unit increase in CCP score was associated with a 2-fold increase in the risk of dying from prostate cancer. In preplanned multivariate analyses, extent of disease, age, clinical stage, and use of hormones had no statistically significant effect on risk; only the Gleason score and PSA remained in the final model. Further exploratory multivariate modeling to produce a combined score, including CCP, Gleason score, and PSA level, suggested a strong, predominant nonlinear influence of the CCP score in predicting the risk of death from prostate cancer

(p=0.008). Cuzick et al suggest this combined score provides additional discriminatory information to help identify low-risk patients who could be safely managed by active surveillance. For example, among patients with a Gleason score of 6, for whom uncertainty exists as to the appropriate management approach, the predicted 10-year prostate cancer

Oncotype Dx® Prostate

One publication compiled results of 3 cohorts of contemporary (1997-2011) patients in a prostatectomy study (N=441; Cleveland Clinic database, 1987-2004), a biopsy study (N=167; Cleveland Clinic database, 1998-2007), and an independent clinical validation study cohort (N=395; mean age, 58 years; University of California, San Francisco Urologic Oncology Data Base, 1998-2011).31

Results from the clinical validation study and prostatectomy study provide information on the potential clinical validity of this test. The cohorts had a mix of low to low-intermediate clinical risk characteristics using National Comprehensive Cancer Network (NCCN) or American Urological Association (AUA) criteria. Patients included in the validation and prostatectomy studies would be considered (a) eligible for active surveillance based on clinical and pathologic findings and (b) representative of patients in contemporary clinical practice. However, all patients elected radical prostatectomy within 6 months of their initial diagnostic biopsies. The clinical validation study was designed to evaluate the ability of Oncotype Dx® Prostate to predict tumor pathology in needle biopsy specimens. It was prospectively designed, used masked review of prostatectomy pathology results, and as such met the REMARK (Reporting

Recommendations for Tumor Marker Prognostic Studies) guidelines for biomarker validation.32 In the prostatectomy study, all patients with clinical recurrence (local recurrence or distant metastasis) were selected, together with a random sample of those who did not recur, using a stratified cohort sampling method to construct a 1:3 ratio of recurrent to nonrecurrent patients. The prespecified primary end point of the validation study was the ability of the Genomic Prostate Score (GPS) to predict the likelihood of favorable pathology in the needle biopsy specimen. Favorable pathology was defined as freedom from high-grade or non-organ-confined disease. In the prostatectomy study, the ability of the GPS to further stratify patients within AUA groupings was related to clinical recurrence-free interval in regression-to-the-mean estimated survival curves.

The validation study results show that the GPS could refine stratification of patients within specific NCCN criteria groupings, as summarized in Table 3. The proportions in Table 3 were estimated from a plot of GPS versus the percent likelihood of favorable pathology.33 These findings suggest that a lower GPS would reclassify the likelihood of favorable pathology (ie, less biologically aggressive disease) upward (ie, a potentially lower risk of progression), and vice versa within each clinical stratum. For example, among patients in the cohort classified by

NCCN criteria as low risk, the mean likelihood of favorable pathology in a tumor biopsy was about 76%, with 24% then having unfavorable pathology. With the GPS, the estimated

likelihood of favorable tumor pathology was broadened, ranging from 55% to 86%, conversely reflecting a 45% to 14% likelihood of adverse pathology, respectively.

In effect, the risk of adverse tumor pathology indicated by the GPS could be nearly halved (24%-14%) at 1 extreme, or nearly doubled (24%-45%) at the other, but the actual number of patients correctly or incorrectly reclassified between 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 biological aggressiveness of a tumor—hence its propensity to progress— 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 radical prostatectomy within 6 months of diagnostic biopsy.

The prostatectomy study provides estimates of clinical recurrence rates stratified by AUA criteria (Epstein et al), compared with rates after further stratification according to the GPS from the validation study. The survival curves for clinical recurrence reached a duration of nearly 18 years based on the dates individuals in the cohort were entered into the database (1987-2004). The restratifications are summarized in Table 4. The GPS groups are defined by tertiles defined in the overall study.

In the NCCN intermediate group, for example, the 10-year recurrence rate among radical

prostatectomy patients was 9.6%. When the GPS was used in the analysis, the 10-year recurrence rate fell to as low as 2.8% (71% reduction) among patients in the low GPS group and 5.1% (47% reduction) in the intermediate GPS group, but rose to 14.3% (49% increase) in the high GPS group. These data suggest the GPS can reclassify a patient’s 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.

Section Summary

Peer-reviewed evidence on the clinical validity of Prolaris® comprises a retrospective cohort (N=349) culled from 6 cancer registries in Great Britain. The investigators assert the CCP score alone was more prognostic than either PSA titer or Gleason score for tumor-specific mortality at 10-year follow-up.

Although the patients may be similar to those of a modern U.S. cohort, comparability is unclear from the single publication that is available. Furthermore, the study is limited by the use of archived biopsy specimens, with attendant issues of reproducibility and test reliability.

The evidence from the Klein paper on clinical validity for Oncotype Dx® Prostate suggests the GPS can reclassify a patient’s risk of recurrence based on a specimen obtained at biopsy.33 However, whether these findings support a conclusion that the GPS could predict the biological aggressiveness of a tumor— hence its propensity to progress—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 most in the study would be otherwise eligible, is difficult because all patients had elective radical prostatectomy within 6 months of diagnostic biopsy. Thus the findings do not reflect a clinical scenario of predicting disease progression in untreated patients under active surveillance.

Clinical Utility

Clinical utility reflects how the results of a diagnostic test will be used to change management of the patient and whether these changes in management lead to clinically important improvements in health outcomes.

Prolaris®

We identified no studies to directly support the clinical utility of Prolaris®. However, we identified 2 retrospective survey studies that assessed the potential impact of Prolaris® on physicians’ treatment decisions.34,35 The authors of each study have suggested their findings support the “clinical utility” of the test, based on whether the results would lead to a change in treatment. Although this information may be useful in assessing the potential test uptake by urologists, it does not demonstrate clinical utility in clinical

settings.

Oncotype Dx® Prostate

Klein et al also reported a decision-curve analysis36 that they have proposed reflects the clinical utility of Oncotype Dx® Prostate.33 In this analysis, they investigated the predictive impact of the GPS in combination with the Cancer of the Prostate Risk Assessment (CAPRA) validated tool37 versus the CAPRA score alone on the net benefit for the outcomes of patients with high-grade disease (Gleason >4+3), high-stage disease, and combined high-high-grade and high-stage

disease. They reported that, over a range of threshold probabilities for implementing treatment, “incorporation of the GPS would be expected to lead to fewer treatments of patients who have favorable pathology at prostatectomy without increasing the number of patients with adverse pathology left untreated.” Thus, an individual patient could use the findings to assess his balance of benefits and harms (net benefit) when weighing the choice to proceed immediately to curative radical prostatectomy with its attendant adverse sequelae, or deciding to enter an active

surveillance program. The latter would have an immediate benefit realized by forgoing radical prostatectomy, but perhaps would be associated with greater downstream risks of disease progression and subsequent therapies.

Section Summary

No evidence is available to support the clinical utility of Prolaris® to guide management of patients with localized prostate cancer.

Klein’s decision-curve analyses suggest a potential ability of the combined GPS and CAPRA data to help patients make decisions based on relative risks associated with immediate treatment or deferred treatment (ie, active surveillance). This would reflect the clinical utility of the test. However, it is difficult to ascribe possible clinical utility of Oncotype Dx® Prostate in active surveillance because all patients regardless of clinical criteria elected radical prostatectomy within 6 months of diagnostic biopsy. Moreover, the validity of using different degrees of tumor pathology as “markers” to extrapolate the risk of progression of a tumor in vivo is unclear.

Ongoing and Unpublished Clinical Trials

No active clinical trials were identified in a search of the ClinicalTrials.gov website as of September 30, 2014.

Summary of Evidence

Two reverse transcriptase-polymerase chain reaction (RTPCR)-based gene expression tests— Prolaris® and Oncotype Dx® Prostate—are commercially available in the United States. They are used in combination with current clinical criteria (Gleason score, prostate-specific antigen serum levels, clinical stage) to further stratify biopsy-diagnosed, localized prostate cancer according to expression levels of discrete sets of genes that, when overexpressed, are considered to reflect increased biological aggressiveness of a lesion. Such information would be used to assist in initial clinical disease management, specifically to decide whether a patient should proceed to definitive therapy (ie, surgery), or could safely proceed to active surveillance. Published evidence is sparse and insufficient to draw conclusions on the analytic validity, clinical validity, or clinical utility of Prolaris®, and is insufficient to determine the clinical validity or utility of Oncotype Dx® Prostate in patients contemplating entry into an active surveillance program.

Practice Guidelines and Position Statements

U.S. Preventive Services Task Force Recommendations

No U.S. Preventive Services Task Force recommendations for Prolaris® or Oncotype Dx® Prostate have been identified.

Medicare National Coverage

The Prolaris test will be denied as not reasonable and necessary regardless of the diagnosis billed (http://www.findacode.com/medicare/policies-guidelines/display-medicareinfo.

php?type=ARTICLE&type_id=52156). No national coverage determination for the Oncotype Dx® Prostate test was identified.

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The existence of this medical policy does not mean that this service is a covered benefit under the member's contract. Benefit determinations should be based in all cases on the applicable contract language. Medical policies do not constitute a description of benefits. A member’s individual or group customer benefits govern which services are covered, which are excluded, and which are subject to benefit limits and which require preauthorization. Members and providers should consult the member’s benefit information or contact Capital for benefit information.

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Capital’s medical policies are developed to assist in administering a member’s benefits, do not constitute medical advice and are subject to change. Treating providers are solely responsible for medical advice and treatment of members. Members should discuss any medical policy related to their coverage or condition with their provider and consult their benefit information to determine if the service is covered. If there is a discrepancy between this medical policy and a member’s benefit information, the benefit information will govern. Capital considers the information contained in this medical policy to be proprietary and it may only be disseminated as permitted by law.

Note: This list of codes may not be all-inclusive, and codes are subject to change at any time. The identification of a code in this section does not denote coverage as coverage is determined by the terms of member benefit information. In addition, not all covered services are eligible for separate reimbursement.

Investigational when used to report Gene Expression Profile Analysis for Prostate Cancer CPT Codes®

81599

Current Procedural Terminology (CPT) copyrighted by American Medical Association. All Rights Reserved.

There is no specific CPT code for this testing. Both of the currently available tests utilize analysis of the results of testing for multiple genes with an algorithm and with the results reported as a type of score. Therefore, the unlisted multianalyte assay with algorithmic analysis (MAAA) unlisted code 81599 should be reported.

*Investigational for all diagnoses

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2. 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 3. 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

4. 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

5. 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

6. 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

7. Eylert MF, Persad R. Management of prostate cancer. Br J Hosp Med (Lond). Feb 2012;73(2):95-99. PMID 22504752

8. 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

9. 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

10. 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

11. 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

12. Borley N, Feneley MR. Prostate cancer: diagnosis and staging. Asian J Androl. Jan 2009;11(1):74-80. PMID 19050692

13. 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

14. Ip S, IJ D, Chung M ea. An evidence review of active surveillance in men with localized prostate cancer. Evidence report/Technology assessment no. 204 (Prepared by Tufts Evidence-based Practice Center under Contract No. HHSA 290-2007-10055-I). 2011;AHRQ Publication No. 12-E003-EF, Rockville, MD: Agency for Research and Quality.(Available at: www.effectivehealthcare.ahrq.gov/reports/final.cfm.). PMID. Accessed October 21, 2014.

15. Thompson I, JB T, Aus G ea. American Urological Association guideline for management of clinically localized prostate cancer: 2007 update. 2007; http://www.auanet.org/common/pdf/education/clinical-guidance/Prostate-Cancer.pdf.Accessed October 21, 2014.

16. 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

17. Albertsen PC. Treatment of localized prostate cancer: when is active surveillance appropriate? Nat Rev Clin Oncol. Jul 2010;7(7):394-400. PMID 20440282 18. 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

19. 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

20. Schoenborn JR, Nelson PS, Fang M. Genomic profiling defines subtypes of prostate cancer with the potential for therapeutic stratification. Clin Cancer Res. May 23 2013. PMID 23704282

21. 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

22. 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 23. 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

24. Blue Cross and Blue Shield Association Technology Evaluation Center (TEC). Microarray-based Gene Expression Analysis for Prostate Cancer Management. TEC Assessments 2013; Volume 28, Tab 11. PMID

25. Shi L, Reid LH, Jones WD, et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol. Sep 2006;24(9):1151-1161. PMID 16964229

26. 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

27. Epstein JI, Allsbrook WC, Jr., Amin MB, et al. The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma. Am J Surg Pathol. Sep 2005;29(9):1228- 1242. PMID 16096414

28. 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

29. 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

30. Montironi R, Mazzuccheli R, Scarpelli M, et al. Gleason grading of prostate cancer in needle biopsies or radical prostatectomy specimens: contemporary approach, current clinical significance and sources of pathology discrepancies. BJU Int. Jun

2005;95(8):1146-1152. PMID 15877724

31. 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

32. McShane LM, Altman DG, Sauerbrei W, et al. Reporting recommendations for tumor marker prognostic studies. J Clin Oncol. Dec 20 2005;23(36):9067-9072. PMID 16172462

33. 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. May 16 2014. PMID 24836057 34. 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. 2014;30(6):1025-1031. PMID

35. 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

36. 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 37. Cooperberg MR, Broering JM, Carroll PR. Risk assessment for prostate cancer

metastasis and mortality at the time of diagnosis. J Natl Cancer Inst. Jun 16 2009;101(12):878-887. PMID 19509351

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MP -2.263 CAC 5/20/14 New policy. BCBSA adopted.Gene expression analysis to guide management of prostate cancer is considered investigational in all situations. Policy coded.

CAC 6/2/15 Consensus review. No changes to the policy statements. References and rationale updated. FEP variation added. No coding changes.

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Health care benefit programs issued or administered by Capital BlueCross and/or its subsidiaries, Capital Advantage Insurance

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