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Michael J Kemeter

All articles from this author are listed below.

Volume 16, Number 4 Review Articles

A Guide for Clinicians in the Evaluation of Emerging Molecular Diagnostics for Newly Diagnosed Prostate Cancer

Diagnosis Update

Judd W Moul H Jeffrey Lawrence Adam S Kibel Steven E Canfield Phillip G Febbo Michael J Kemeter

Prostate-specific antigen (PSA) screening is associated with a decline in prostate cancerrelated mortality. However, screening has also led to overdiagnosis and overtreatment of clinically insignificant tumors. Recently, certain national guidelines (eg, US Preventive Services Task Force) have recommended against PSA screening, which may lead to a reverse-stage migration. Although many prostate tumors are indolent at presentation, others are aggressive and are appropriate targets for treatment interventions. Utilization of molecular markers may improve our ability to measure tumor biology and allow better discrimination of indolent and aggressive tumors at diagnosis. Many emerging commercial molecular diagnostic assays have been designed to provide more accurate risk stratification for newly diagnosed prostate cancer. Unfamiliarity with molecular diagnostics may make it challenging for some clinicians to navigate and interpret the medical literature to ascertain whether particular assays are appropriately developed and validated for clinical use. Herein, the authors provide a framework for practitioners to use when assessing new tissue-based molecular assays. This review outlines aspects of assay development, clinical and analytic validation and clinical utility studies, and regulatory issues, which collectively determine whether tests (1) are actionable for specific clinical indications, (2) measurably influence treatment decisions, and (3) are sufficiently validated to warrant incorporation into clinical practice. [Rev Urol. 2014;16(4):172-180 doi: 10.3909/riu0644] © 2014 MedReviews®, LLC

Prostate cancer Biomarker Clinical utility Genomic prostate score Adverse pathology Clinical validation Molecular diagnostics

Volume 18, Number 3 Original Research

Health Economic Impact and Prospective Clinical Utility of Oncotype DX® Genomic Prostate Score

David Albala Frank Dubeck Alan W Shindel Marybeth McCall Bela Denes Dylan Stoy Vincy John Ruixiao Lu Phillip G Febbo Michael J Kemeter

Prostate cancer (CaP) will be diagnosed in approximately 181,000 American men in 2016. Despite the high number of deaths from CaP in the United States, the disease has a protracted natural history and many men diagnosed with CaP will not die of the disease regardless of treatment. Unfortunately, identification of men with truly indolent/nonaggressive CaP is challenging; limitations of conventional diagnostic modalities diminish the ability of physicians to accurately stage every case of CaP based on biopsy results alone. The resulting uncertainty in prognosis may prompt men with low-risk CaP to proceed to morbid and expensive treatments for an unclear survival benefit. Incorporation of the Genomic Prostate Score (GPS) as part of the decision algorithm for patients with National Comprehensive Cancer Network very low-risk and low-risk cancer led to a substantial increase in uptake of active surveillance and substantial cost savings. GPS provides physicians and patients with an additional tool in assessing personalized risk and helps guide individual decision making. [Rev Urol. 2016;18(3):123-132 doi: 10.3909/riu0725] © 2016 MedReviews®, LLC

Prostate cancer Oncotype DX® GPS Genomic testing Health economics Clinical utility

Volume 19, Number 4 Review Articles

Active Surveillance Use Among a Low-risk Prostate Cancer Population in a Large US Payer System: 17-Gene Genomic Prostate Score Versus Other Risk Stratification Methods

Original Research

John Hornberger Steven Canfield Phillip G Febbo Michael J Kemeter

Many men with low-risk prostate cancer (PCa) receive definitive treatment despite recommendations that have been informed by two large, randomized trials encouraging active surveillance (AS). We conducted a retrospective cohort study using the Optum™ Research Database (Eden Prairie, MN) of electronic health records and administrative claims data to assess AS use for patients tested with a 17-gene Genomic Prostate Score™ (GPS; Genomic Health, Redwood City, CA) assay and/or prostate magnetic resonance imaging (MRI). De-identified records were extracted on health plan members enrolled from June 2013 to June 2016 who had ≥1 record of PCa (n = 291,876). Inclusion criteria included age ≥18 years, new diagnosis, American Urological Association low-risk PCa (stage T1-T2a, prostate-specific antigen ≥10 ng/mL, Gleason score = 6), and clinical activity for at least 12 months before and after diagnosis. Data included baseline characteristics, use of GPS testing and/or MRI, and definitive procedures. GPS or MRI testing was performed in 17% of men (GPS, n = 375, 4%; MRI, n = 1174, 13%). AS use varied from a low of 43% for men who only underwent MRI to 89% for GPS-tested men who did not undergo MRI (P<001). At 6-month follow-up, AS use was 31.0% higher (95% CI, 27.6%-34.5%; P<001) for men receiving the GPS test only versus men who did not undergo GPS testing or MRI; the difference was 30.5% at 12-month follow-up. In a large US payer system, the GPS assay was associated with significantly higher AS use at 6 and 12 months compared with men who had MRI only, or no GPS or MRI testing. [Rev Urol. 2017;19(4):203–212 doi: 10.3909/riu0786] © 2018 MedReviews®, LLC

Prostate cancer Active surveillance Evidence-based practice Comparative effectiveness research Genomic biomarker Magnetic resonance imaging

Volume 20, Number 2 Original Research

Balancing Confounding and Generalizability Using Observational, Real-world Data: 17-gene Genomic Prostate Score Assay Effect on Active Surveillance

Michael J Kemeter John Hornberger Steven Canfield Phillip G Febbo

Randomized, controlled trials can provide high-quality, unbiased evidence for therapeutic interventions but are not always a practical or viable study design for certain healthcare decisions, such as those involving prognostic or predictive testing. Studies using large, real-world databases may be more appropriate and more generalizable to the intended target population of physicians and patients to answer these questions but carry potential for hidden bias. We illustrate several emerging methods of analyzing observational studies using propensity score matching (PSM) and coarsened exact matching (CEM). These advanced statistical methods are intended to reveal a “hidden experiment” within an observational database, and so refute or confirm a potential causal effect of assignment to an intervention and study outcome. We applied these methods to the Optum™ Research Database (ORD; Eden Prairie, MN) of electronic health records and administrative claims data to assess the effect of the 17-gene Genomic Prostate Score® (GPS™; Genomic Health, Redwood City, CA) assay on use of active surveillance (AS). In a traditional multivariable logistic regression, the GPS assay increased the use of AS by 29% (95% CI, 24%-33%). Upon applying the matching methods, the effect of the GPS assay on AS use varied between 27% and 80% and the matched data were significant among all algorithms. All matching algorithms performed well in identifying matched data that improved the imbalance in baseline covariates. By using different matching methods to assess causal inference in an observational database, we provide further confidence that the effect of the GPS assay on AS use is statistically significant and unlikely to be a result of confounding due to differences in baseline characteristics of the patients or the settings in which they were seen. [Rev Urol. 2018;20(2):69–76 doi: 10.3909/riu0799] © 2018 MedReviews, LLC®

Prostate cancer Active surveillance Evidence-based practice Comparative effectiveness research Genomic biomarker Propensity score Matching