BlueCross BlueShield of Tennessee Medical Policy Manual

Gene Expression Profile Analysis for Prostate Cancer Management

DESCRIPTION

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 (e.g. Oncotype Dx® Prostate Cancer Assay) regarding active surveillance versus therapeutic intervention, or after radical prostatectomy (e.g. Prolaris®, Decipher® Prostate Cancer Classifier, ProMark®) to guide radiotherapy decisions.

Prostate cancers may appear clinically very similar at diagnosis. However, they often exhibit diverse risk of progression that may not be captured by current clinical risk categories or prognostic tools such as PSA titers, Gleason grade or tumor stage. Given the unpredictable behavior of early prostate cancer, additional prognostic methods to biologically stratify this disease based on genetic analysis is being investigated in clinical trials.

POLICY

See also:  Genetic and Protein Biomarkers for the Diagnosis and Cancer Risk Assessment of Prostate Cancer

IMPORTANT REMINDERS

ADDITIONAL INFORMATION  

There is insufficient information to establish the clinical validity or clinical utility to guide management decision in prostate cancer care at this time, Therefore, these tests remain investigational.

SOURCES 

Badani, K., Kemeter, M., Febbo, P., Lawrence, J., Denes, B., Rothney, M., et al. (2015, July) 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, Vol. 2, 181-189. (Level 4 evidence)

BlueCross BlueShield Association. Medical Policy Reference Manual. (11:2016). Gene expression profiling and protein biomarkers for prostate cancer management (2.04.111). Retrieved August 7, 2017 from BlueWeb. (100 articles and/or guidelines reviewed)

Cullen, J.,  Rosner, I.,  Brand, T.,  Zhang, N., Tsiatis, A.,  Moncur, J., et al. (2015, July) 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. European Urology, 68 (1):123-31. (Level 4 evidence)

Cuzick, J., Berney,D., Fisher, G., Mesher, D., Møller, H., Reid, J., et al. (2012). Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort. British Journal of Cancer, 106, 1095-1099. (Level 4 evidence)

Cuzick, J., Stone, S., Fisher, G., Yang, Z., North, B., Berney, D., et al. (2015). Validation of an RNA cell cycle progression score for predicting death from prostate cancer in a conservatively managed needle biopsy cohort. British Journal of Cancer, 113, 382-389. (Level 4 evidence)

Koch, M., Cho, J., Kaimakliotis, Z., Cheng, L., Sangale, Z., Brawer, M., et al. (2016). Use of the cell cycle progression (CCP) score for predicting systemic disease and response to radiation of biochemical recurrence. Cancer Biomarkers, 17 (2016), 83-88. (Level 4 evidence)

Moschini, M., Spahn, M., Mattei, A., Cheville, J., and Karnes, J. (2016) Incorporation of tissue-based genomic biomarkers into localized prostate cancer clinics. BMC Medicine, 14:67. (Level 2 evidence)

National Comprehensive Cancer Network. (2016). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). Prostate cancer (V.2.2017). Retrieved August 7, 2017 from www.nccn.org.

Rubicz, R., Zhao, S., April, C., Wright, J., Kolb, S., Coleman, I., et al. Expression of cell cycle-regulated genes and prostate cancer prognosis in a population-based cohort. Prostate, 75 (13), 1354-1362. Abstract retrieved August 30, 2016 from PubMed database.

Sommariva, S., Tarricone, R., Lazzeiri, M., Ricciardi, W., & Montorsi, F. (2016). Prognostic value of the cell cycle progression score in patients with prostate cancer: a systematic review and meta-analysis. European Urology, 69 (1), 107-115. Abstract retrieved August 30, 2016 from PubMed database.

Technology Evaluation Center. (2015, January). Gene expression analysis for prostate cancer management. (Volume 29, No. 9). Retrieved August 30, 2016 from http://bluewebportal.bcbs.com.  (59 articles and/or guidelines reviewed)

ORIGINAL EFFECTIVE DATE:  8/9/2014

MOST RECENT REVIEW DATE:  9/14/2017

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