Gene Expression Analysis for Prostate Cancer
Management
EXECUTIVE SUMMARY
Background
Prostate cancer is the second most common cancer diagnosed among men in the United States.
According to the National Cancer Institute, nearly 240,000 new cases were expected to be diagnosed in
the United States in 2013, and associated with an estimated 30,000 deaths. Localized prostate cancers
1
may appear clinically very similar at diagnosis. However, they often exhibit diverse risk of progression
that may not be fully captured by accepted clinical risk categories (eg, D’Amico criteria) or prognostic
tools that are based on clinical findings, including prostate-specific antigen (PSA) titers, Gleason grade, or
2-6
tumor stage. Evidence suggests high-grade (Gleason grade 8-10) and most moderate-grade (Gleason
4+3) cancers will progress. There is most uncertainty over the likelihood of progression among Gleason
3+3 and small volume Gleason 7 tumors. This variation in tumor behavior creates uncertainty in the latter
7,8
categories of whether to treat immediately or defer therapy. A patient may choose definitive treatment,
which for localized cancers usually comprises either radiotherapy or radical prostatectomy (RP).
Alternatively, a patient may forgo immediate therapy and continue regular monitoring pending signs or
symptoms of disease progression, at which point curative treatment is instituted. This approach is referred
9,10
to as “active surveillance.”
Given the unpredictable behavior of localized prostate cancer, prognostic tests to guide patient
management are under investigation, eg, gene expression profiling. Gene expression profiling refers to
11-14
analysis of mRNA expression levels of many genes simultaneously in a tumor specimen.
Two gene expression profiling tests are commercially available, 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 formalin-fixed paraffin-embedded (FFPE) tumor
specimens as the mRNA source and real-time polymerase chain reaction (RTPCR) technology. Prolaris®
quantifies expression levels of 31 cell cycle progression (CCP) genes and 15 housekeeper genes to
generate a CCP score. Oncotype Dx® Prostate quantifies expression levels of 12 cancer-related and 5
reference genes to generate a Genomic Prostate Score (GPS). A proprietary algorithm is then used to
combine the CCP score or GPS with a patient’s clinical risk factors (PSA serum levels, Gleason grade,
tumor stage) to generate a new risk category (ie, reclassification) intended to reflect the potential
biological aggressiveness of his lesion, and thus inform management decisions.
Objective
To evaluate evidence on gene expression profiling tests, specifically Prolaris® (Myriad Genetics, Salt
Lake City, UT) and Oncotype Dx® Prostate (Genomic Health, Redwood City, CA).
We formulated this Assessment to address 1 key question: What is the incremental value of gene
expression testing compared with clinical criteria for discriminating men with aggressive cancer from
those with indolent disease to guide treatment decisions that improve overall net health outcomes?
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Notice of Purpose: TEC Assessments and Special Reports are scientific opinions, provided solely for informational purposes. TEC Assessments and
Special Reports should not be construed to suggest that Blue Cross Blue Shield Association or the TEC Program recommends, advocates, requires,
encourages, or discourages any particular treatment, procedure, or service; any particular course of treatment, procedure, or service; or the payment
or nonpayment of the technology or technologies evaluated.
Blue Cross Blue Shield Association is an association of independent Blue Cross and Blue Shield companies.
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
Search Strategy
We performed an electronic search of the National Library of Medicine MEDLINE® database (via
PubMed) through June 24, 2014, updated September 30, 2014, to identify literature published on the use
of Prolaris® and Oncotype Dx® Prostate.
The search included primary studies, review articles, systematic reviews, and editorials published in
English. We reviewed the websites of the test manufacturers for background and clinical information, as
well as the U.S. Food and Drug Administration’s (FDA) website for regulatory information. We also
contacted test developers for additional information not identified in the search.
Selection Criteria
In the evidence assessment, we sought only full-length publications that reported on the analytic validity,
clinical validity, or clinical utility of either test, using human prostate tumor FFPE specimens obtained by
needle biopsy according to the patient indications and specific assessment question formulation. Review
articles, systematic reviews, and other materials were also reviewed.
Main Results
Analytic Validity
Prolaris®
We found no direct evidence on the analytic validity of Prolaris®. However, the MicroArray Quality Control
(MAQC) project (sponsored by FDA) has evaluated the performance of gene expression analysis
platforms, including the TaqMan assay (Applied Biosystems, Foster City, CA), a version of which is used
15
in Prolaris®. The MAQC investigators gathered expression data for 4 titration pools from 2 distinct
reference RNA samples generated at multiple test sites on 7 microarray-based and 3 alternative
technology platforms. They found 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
16
We identified 1 report, by Knezevic et al, on the analytic validity of Oncotype Dx® Prostate. Estimates of
analytical precision and reproducibility were derived from analysis of RNA prepared from 10
microdissected prostate tumor samples obtained by needle biopsy. Individual Gleason scores were
17
assigned using the 2005 International Society of Urological Pathology Consensus guidelines. Test
parameters of interest included analytic accuracy, amplification efficiency, and precision.
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.
3
A low input level of 5 ng mRNA was used to reflect the lowest 2.5 percentile (0.0225 cm ) of a tumor
sample. When converted to GPS units (the unit measure for reporting test results), the SD for analytic
precision was 1.86 GPS units (95% confidence interval [CI], 1.60 to 2.20) on the 100-unit scale. The SD
for reproducibility was 2.11 GPS units (95% CI, 1.83 to 2.50) on the 100-point scale.
Clinical Validity
Prolaris®
A retrospective clinical validation study on Prolaris®, by Cuzick et al, included patients (N=349) culled
18
from 6 cancer registries in Great Britain. The study examined whether a combined risk score based on a
tumor CCP score and clinical risk factors (PSA serum level, Gleason score) would better predict risk of
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
death from prostate cancer at 10 years postdiagnosis than would clinical risk factors alone. The test was
performed on RNA isolated from tumor cells that were microdissected from archived prostate specimens
obtained by needle biopsy. A primary univariate analysis suggested that a 1-unit increase in CCP score is
associated with a 2-fold increase in the hazard ratio (HR) for death from prostate cancer (HR=2.02; 95%
CI, 1.62 to 2.53).
We identified 4 other full-length studies of the Prolaris® CCP gene expression test. Three of them used
archived pathologic specimens obtained from patients who underwent RP or transurethral resection of the
19-21
prostate.
CCP analysis was used to prognosticate for biochemical recurrence or prostate-specific
mortality after treatment or watchful waiting, respectively. A fourth study reported results of CCP analysis
as an adjunct to clinical criteria to predict biochemical recurrence in men who underwent external-beam
22
radiotherapy. The patients and management approaches in these 4 studies do not represent the
population of interest for or address the primary question of interest of this Assessment.
Oncotype Dx® Prostate
We found 1 publication that 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
23
years; University of California, San Francisco Urologic Oncology Data Base, 1998-2011). In this
Assessment, we included the results of the clinical validation study and prostatectomy study because
they provide information on the potential clinical validity of this test. The cohorts had a mix of low to lowintermediate 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 pathological findings
and (b) representative of patients in contemporary clinical practice. However, all patients elected RP
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
24
Marker Prognostic Studies) guidelines for biomarker validation. In the prostatectomy study, all patients
with clinical recurrence (local recurrence or distant metastasis) were selected, together with a random
sample of those whose cancer 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 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 A. The proportions in Table A were estimated from a plot of
23
GPS versus the percent likelihood of favorable pathology. 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.
Table A. Reclassification of Prostate Cancer Risk Categories With Oncotype Dx® Prostate
NCCN Risk
Level
Very low
Low
Estimated Mean Likelihood of Favorable Tumor Pathology
NCCN Criteria, %
84
76
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GPS + NCCN Criteria, % Range
63-91
55-86
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Estimated Corresponding
GPS, Range
60-6
53-1
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
56
Intermediate
29-75
GPS: Genomic Prostate Score; NCCN: National Comprehensive Cancer Network.
66-4
In effect, the risk of adverse tumor pathology indicated by the GPS could be nearly halved (24% to 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 could not 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 RP within 6 months of diagnostic biopsy.
The prostatectomy study provides estimates of clinical recurrence rates stratified by AUA criteria (Epstein
17
et al ), compared with rates after further stratification using 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 reclassifications are
summarized in Table B. The GPS groups are defined by tertiles defined in the overall study.
Table B. Reclassification of Prostate Cancer 10-Year Clinical Recurrence Risk With Oncotype Dx®
Prostate
Overall 10-Year Risk, %
10-Year Risk, %
10-Year Risk, %
(AUA Risk Level)
(GPS Low Group)
(GPS Intermediate Group)
3.4 (low)
2.0
3.4
9.6 (intermediate)
2.8
5.1
18.2 (high)
6.2
9.2
AUA: American Urological Association; GPS: Genomic Prostate Score.
10-Year Risk, %
(GPS High Group)
7.0
14.3
28.6
In the AUA intermediate group, eg, the 10-year recurrence rate among RP 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 for predicting disease progression in untreated patients under active surveillance.
Clinical Utility
Prolaris®
We found 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
25,26
decisions.
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 potential test uptake by urologists, it does not demonstrate clinical utility in clinical
settings.
Oncotype Dx® Prostate
27
Klein et al also reported a decision-curve analysis that they have proposed reflects the clinical utility of
23
Oncotype Dx® Prostate. In this analysis, they investigated the predictive impact of the GPS in
28
combination with the Cancer of the Prostate Risk Assessment (CAPRA) validated tool 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-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 RP with its attendant adverse sequelae, or deciding to enter an active
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
surveillance program. The latter would have an immediate benefit realized by forgoing RP, but could be
associated with greater downstream risks of disease progression and subsequent therapies.
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 clinical utility of Oncotype Dx® Prostate in active surveillance because all patients, regardless of
clinical criteria, elected RP 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.
Author Conclusions and Comment
Two RTPCR-based gene expression tests—Prolaris® and Oncotype Dx® Prostate—are commercially
available in the United States. We evaluated published evidence on their use in combination with current
clinical criteria (Gleason score, PSA 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 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 under active surveillance program.
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SUMMARY OF APPLICATION OF THE TECHNOLOGY EVALUATION CRITERIA
Based on the available evidence, the Blue Cross and Blue Shield Association Medical Advisory Panel
made the following judgments about whether use of the Prolaris® or the Oncotype Dx® Prostate gene
expression analysis test to guide treatment decisions in men with newly diagnosed, localized prostate
cancer meets the Blue Cross and Blue Shield Association Technology Evaluation Center (TEC) criteria.
1. The technology must have final approval from the appropriate governmental regulatory
bodies.
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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® or Oncotype Dx® Prostate 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.
2. The scientific evidence must permit conclusions concerning the effect of the technology
on health outcomes.
Analytic Validity
No published evidence has demonstrated the analytic validity of Prolaris® testing, although it is indirectly
suggested by results from the MicroArray Quality Control project. One publication provides sufficient
evidence to support the analytic validity of Oncotype Dx® Prostate testing.
Clinical Validity
Evidence supporting the clinical validity of Prolaris® testing includes a retrospective cohort (N=349)
selected from 6 cancer registries in Great Britain. In the primary univariate analysis, a 1-unit increase in
the cell cycle progression (CCP) score was associated with a 2.02-fold (95% confidence interval [CI], 1.62
to 2.53) increase in the risk of death from prostate cancer at 10-year follow-up. Multivariate analyses
showed only the CCP score (hazard ratio [HR] for a 1-unit increase in CCP score, 1.65; 95% CI, 1.31 to
2.0), Gleason score less than 7 (HR=0.61; 95% CI, 0.32 to 1.16), and prostate-specific antigen (PSA) titer
(HR=1.37; 95% CI, 1.05 to 1.79) were associated with prostate cancer‒specific mortality at 10 years. This
evidence has several limitations. First, according to the investigators, the cohort in this study may not
reflect current prostate cancer treatment in that patients were universally managed conservatively,
despite the presence of higher risk characteristics such as T3 lesions (12% of cases), Gleason scores
greater than 7 (26% of cases), and median serum PSA levels around 20 ng/mL (range 12-42 ng/mL).
Furthermore, the archived biopsy specimens have limitations secondary to sampling a small portion of
each tumor yielding a small amount of tissue from which to generate a gene expression profile. Finally,
the authors acknowledge more empirical data are needed to establish a developmental multiple sampling
process for tumor specimens, to assure accuracy and reproducibility of the assay based on needle biopsy
specimens. Based on these limitations, the evidence is insufficient to support the clinical validity of
Prolaris® testing.
One article has reported on the clinical validity of Oncotype Dx® Prostate testing, specifically to predict
adverse tumor pathology in needle biopsy specimens. The validation study cohort (N=395), identified
from the University of California, San Francisco Urologic Oncology Data Base, had a mix of low to lowintermediate clinical risk characteristics using National Comprehensive Cancer Network criteria. These
men would be eligible to enter an active surveillance program according to clinical criteria. The
prespecified primary end point was the ability of the Genomic Prostate Score (GPS) to predict the
likelihood of favorable pathology in the tumor specimens. Favorable pathology was defined as freedom
from high-grade or non-organ-confined disease. The findings suggest that a lower GPS would increase
the likelihood of favorable pathology (ie, less biologically aggressive disease) upward (ie, a potentially
lower risk of disease progression), and vice versa within a clinical stratum. However, whether the
presence of adverse pathology in a tumor biopsy is sufficient to extrapolate to risk of tumor progression in
vivo is unclear when considered in the context of evidence from the Prostate Cancer Intervention versus
Observation Trial [PIVOT]), which showed no significant survival advantage for immediate intervention
(radical prostatectomy [RP]) compared with observation in men with clinically low risk disease. Thus, the
main value of the GPS would be to reclassify clinically low risk men into what would be deemed a
“biologically low risk” (indolent) category with greater predictive power than clinical classification alone.
This remains to be demonstrated in an active surveillance study.
In their prostatectomy study, Klein et al showed a reduction in the clinical recurrence rate in men with
lower GPS compared with those in higher GPS categories. They suggested that the GPS helps to further
stratify tumors according to biological aggressiveness. However, the evidence does not demonstrate the
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effect of reclassification on a clinical end point (eg, overall survival, cancer-specific survival) in patients
under active surveillance, nor does it reflect the potential benefit realized by avoiding unnecessary RP
and its adverse events. Therefore, the evidence is insufficient to support the clinical validity of Oncotype
Dx® Prostate testing in men under active surveillance.
Clinical Utility
No direct evidence was found to support the clinical utility of Prolaris® testing.
Klein et al reported decision-curve analyses to support the clinical utility of Oncotype Dx® Prostate
testing. They suggested a potential effect of the combined GPS and Cancer of the Prostate Risk
Assessment data to assess the net benefit of surgery versus no treatment for each category of highgrade disease (Gleason >4+3), high-stage disease, and combined high-grade and high-stage disease in
prostate tumor specimens. They concluded that the combined use of the GPS and clinical criteria could
lead to fewer treatments among patients with favorable pathology without increasing the proportion who
are not treated but require intervention. As noted above, it is not clear whether adverse pathology in a
tumor specimen represents an adequate surrogate to predict risk of in vivo tumor progression. Moreover,
this study provided no direct evidence of the clinical utility for Oncotype Dx® Prostate testing in choosing
between RP or an active surveillance program because all patients—although eligible for active
surveillance—elected RP within 6 months of diagnostic biopsies. Therefore, the evidence is insufficient to
support the clinical utility of Oncotype Dx® Prostate testing in men under active surveillance.
3. The technology must improve the net health outcome.
The evidence is insufficient to determine whether Prolaris® or Oncotype Dx® Prostate testing affects the
net health outcome.
4. The technology must be as beneficial as any established alternatives.
The evidence is insufficient to determine the incremental value of Prolaris® or Oncotype Dx® Prostate
testing compared with established clinical criteria alone for discriminating men with aggressive and
indolent disease to guide treatment decisions that improve the net health outcome.
5. The improvement must be attainable outside the investigational settings.
The evidence is insufficient to determine whether Prolaris® or Oncotype Dx® Prostate testing improves
health outcomes in the investigational setting.
Based on the above, neither the Prolaris® nor Oncotype Dx® Prostate gene expression test meets the
Blue Cross and Blue Shield Association Technology Evaluation Center (TEC) criteria.
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
AUTHORS, STAFF, AND MEDICAL ADVISORY PANEL
TEC Staff Contributors
Lead Author: Thomas A. Ratko, Ph.D.
Executive Director, Center for Clinical Effectiveness: Suzanne E. Belinson, Ph.D., M.P.H.
Executive Director, Clinical Evaluation, Innovation, and Policy: Naomi Aronson, Ph.D.
Director, Technology Assessment: Mark D. Grant, M.D., Ph.D.
Research/Editorial Staff: Claudia Bonnell, R.N., M.L.S., Kimberly Hines, M.S., Michael Vasko, M.A.
Blue Cross Blue Shield Association Medical Advisory Panel
Chair
Trent T. Haywood, M.D., J.D., Senior Vice President, Clinical Affairs/Medical Director, Blue Cross Blue Shield Association
Vice Chair
Suzanne E. Belinson, Ph.D., M.P.H., Executive Director, Center for Clinical Effectiveness, Blue Cross Blue Shield Association
Scientific Advisors
Steven N. Goodman, M.D., M.H.S., Ph.D., Dean for Clinical and Translational Research, Stanford University School of Medicine, and
Professor, Departments of Medicine, Health Research and Policy
Mark A. Hlatky, M.D., Professor of Health Research and Policy and of Medicine (Cardiovascular Medicine), Stanford University School of
Medicine; American College of Cardiology Appointee
Panel Members
Peter C. Albertsen, M.D., Professor, Chief of Urology, and Residency Program Director, University of Connecticut Health Center
Ann Boynton, Deputy Executive Officer, Benefits Programs Policy and Planning, CalPERS
Virginia Calega, M.D., M.B.A., F.A.C.P., Vice President, Medical Management and Policy, Highmark Inc.
Sarah T. Corley, M.D., F.A.C.P., Chief Medical Officer, NextGen Healthcare Information Systems Inc.; American College of Physicians
Appointee
Helen Darling, M.A., Strategic Advisor, National Business Group on Health
Josef E. Fischer, M.D., F.A.C.S., William V. McDermott Professor of Surgery, Harvard Medical School; American College of Surgeons
Appointee
Lee A. Fleisher, M.D., Professor and Chair, Department of Anesthesiology and Critical Care, University of Pennsylvania Perelman School of
Medicine; Senior Fellow, Leonard Davis Institute of Health Economics
I. Craig Henderson, M.D., Adjunct Professor of Medicine, University of California, San Francisco
Jo Carol Hiatt, M.D., M.B.A., F.A.C.S., Chair, Inter-Regional New Technology Committee, Kaiser Permanente
Saira A. Jan, M.S., Pharm.D., Associate Clinical Professor, Ernest Mario School of Pharmacy, Rutgers, The State University of New Jersey;
Residency Director and Director of Clinical Programs Pharmacy Management, Horizon Blue Cross and Blue Shield of New Jersey
Lawrence Hong Lee, M.D., M.B.A., F.A.C.P., Vice President and Executive Medical Director for Quality and Provider Relations, Blue Cross
and Blue Shield of Minnesota
Bernard Lo, M.D., President, The Greenwall Foundation
Randall E. Marcus, M.D., Charles H. Herndon Professor and Chairman, Department of Orthopaedics, Case Western Reserve University
School of Medicine and University Hospitals Case Medical Center, Cleveland, Ohio
Barbara J. McNeil, M.D., Ph.D., Ridley Watts Professor and Head, Department of Health Care Policy, Harvard Medical School; Professor of
Radiology, Brigham and Women's Hospital
William R. Phillips, M.D., M.P.H., T.J. Phillips Endowed Professor in Family Medicine, University of Washington; American Academy of
Family Physicians Appointee
Rita F. Redberg, M.D., M.Sc., F.A.C.C., Professor of Medicine and Director, Women's Cardiovascular Services, University of California San
Francisco
Maren T. Scheuner, M.D., M.P.H., F.A.C.M.G., Chief, Medical Genetics, VA Greater Los Angeles Healthcare System; Professor,
Department of Medicine, David Geffen School of Medicine at UCLA; Affiliate Natural Scientist, RAND Corporation; American College of
Medical Genetics and Genomics Appointee
Leslie Robert Schlaegel, M.S., Associate Vice President of Human Resources, Stanford University
J. Sanford Schwartz, M.D., F.A.C.P., Leon Hess Professor of Medicine and Health Management & Economics, School of Medicine and The
Wharton School, University of Pennsylvania
John B. Watkins, Pharm.D., M.P.H., B.C.P.S., Pharmacy Manager, Formulary Development, Premera Blue Cross
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
Gene Expression Analysis for Prostate Cancer
Management
ASSESSMENT OBJECTIVE
Localized prostate cancers can appear very similar in terms of size, palpability, histology, and clinical
1
stage at diagnosis. However, cancers that are clinicopathologically similar may exhibit widely diverse
2-4
risks of progression and metastasis. Evidence suggests that high-grade (Gleason grade 8-10) and most
moderate-grade (Gleason 4+3) cancers will progress. There is most uncertainty over the likelihood of
progression among Gleason 3+3 and small-volume Gleason 7 tumors. This variation in biological
behavior often creates a significant patient management challenge for localized tumors, stated most
5,6
simply as: to treat or not to treat.
Given significant uncertainty in predicting the behavior of clinically low-risk prostate cancer, additional
predictive means are under investigation. They include molecular profiling tumor biology using
sequencing technology. Molecular profiling refers to the simultaneous analysis of the messenger RNA
7-10
(mRNA) expression levels of many genes in a tumor specimen.
A major goal of molecular profiling is to
identify specific gene expression patterns (eg, gene groupings that control cell-cycle functions, receptormediated signaling pathways, or apoptosis) that reliably reflect a cancerous phenotype and can be
applied to predict tumor behavior.
BACKGROUND
Burden of Disease
11
Prostate cancer is the second most common cancer diagnosed among men in the United States.
According to National Cancer Institute (NCI) figures, nearly 240,000 new cases were expected to be
diagnosed in the United States in 2013, with an estimated 30,000 deaths due to this disease. Autopsy
studies in the pre‒prostate-specific antigen (PSA) screening era have identified incidental cancerous foci
12
in 30% of men 50 years of age, with incidence reaching 75% at age 80 years. However, NCI
Surveillance Epidemiology and End Results data have shown that age-adjusted cancer-specific mortality
rates for men with prostate cancer 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 of low-risk disease using PSA screening
13,14
and improved primary management and treatment.
Terminology and Natural History of Prostate Cancer
The term localized prostate cancer is generally reserved for a tumor that is truly confined within the
prostate gland, not having invaded the seminal vesicles or beyond the glandular capsule. According to
the American Joint Committee on Cancer [AJCC] criteria, this would be termed pathological T2N0M0 (see
below and Appendix Table 1). The terminology used to refer to localized prostate cancer has varied in the
3
literature. Examples include insignificant, indolent, minute, microfocal, and minimal. For our purposes,
AJCC
AUA
CAP
CAPRA
CCP
cDNA
CI
CLIA
EBRT
FDA
FFPE
Abbreviations and Acronyms
American Joint Committee on Cancer
GPS
Genomic Prostate Score
American Urological Association
LDT
laboratory-developed tests
College of American Pathologists
MAQC
MicroArray Quality Control
Cancer of the Prostate Risk Assessment
mRNA
messenger RNA
cell cycle progression
NCCN
National Comprehensive Cancer Network
complementary DNA
NCI
National Cancer Institute
confidence interval
PSA
prostate-specific antigen
Clinical Laboratory Improvement Act
RP
radical prostatectomy
external-beam radiotherapy
RTPCR
real-time polymerase chain reaction
Food and Drug Administration
TURP
transurethral resection of the prostate
formalin-fixed paraffin-embedded
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
and because clinical investigators of the molecular profiling tests use the term indolent, we refer to
indolent cancers in the context of profiling results and biological behavior.
4,15
The natural history of prostate cancer is not well understood or predictable.
A large proportion of
prostate cancers will progress, although the rate and postdiagnostic timing of progression varies
2
substantially. In studies of conservative management, the risk of localized disease progression based on
16,17
18
prostate cancer‒specific survival rates may range from 15%
to 20% at 10 years to perhaps 27% at
19
20-year follow-up. Among elderly men (≥70 years) with this type of low-risk disease, most will die from
other comorbidities with prostate cancer present. However, very similar low-risk tumors can progress
unexpectedly, quickly spreading and becoming incurable.
Diagnosis, Grading, and Staging of Prostate Cancer
Prostate cancer is diagnosed through histologic analysis of prostate specimens obtained by needle
biopsy or transurethral resection. The histologic grade of prostate cancer is assessed according to the
20
Gleason system, the most predictive staging system used for this disease. The pattern made by the
glandular epithelium is graded on a scale ranging from 1 (least aggressive) to 5 (most aggressive) on the
largest available histologic specimen. The 2 most common Gleason patterns are added to give a total
score that ranges from 2 (1+1) to 10 (5+5). The Gleason system has recently been modified to assure
consistency and reproducibility among pathologists, and remains a highly valuable predictor of cancer
21,22
behavior.
Prostate cancer is clinically staged according to the 2010 modification of the 2002 TNM
23
(primary tumor, lymph node, metastases) classification for adenocarcinoma of the prostate (see
Appendix Table 1 for AJCC criteria). The population of interest in this Assessment is men who have
localized stage I or IIA disease (pT2N0M0).
Treatment of Prostate Cancer
The treatment of prostate cancer depends largely on how advanced the disease is at diagnosis. Options
can include surgery (radical prostatectomy [RP]), external-beam radiotherapy (EBRT), brachytherapy,
6,24
high-intensity-focused ultrasound, hormonal therapy, cryosurgery, or combinations thereof.
RP or
EBRT are the usual choices for treatment of localized tumors. Complications associated with those
treatments most commonly reported (RP, EBRT) and with the greatest variability are incontinence (0%73%) and other genitourinary toxicity (irritative and obstructive symptoms); hematuria (typically ≤5%);
gastrointestinal and bowel toxicity, including nausea and loose stools (25%-50%); proctopathy, including
24
rectal pain and bleeding (10%-39%); and erectile dysfunction, including impotence (50%-90%).
Active Surveillance
American Urological Association (AUA) guidelines suggest that patients with low- and intermediate-risk
prostate cancer have the option of “active surveillance,” which takes into account patient age, patient
24
preferences, and health conditions related to urinary, sexual, and bowel function. A patient may proceed
immediately to definitive treatment or may continue regular monitoring until signs of disease progression
25,26
are evident, at which point curative treatment is initiated.
Active surveillance defers the significant
morbidity and potential mortality associated with curative treatments for prostate cancer. However, active
surveillance can compromise treatment options if an otherwise low-risk tumor unexpectedly progress
24,27
rapidly.
Overall, numerous trade-offs must be considered with active surveillance or definitive therapy,
such that each patient must determine his preference, accepting that both approaches will be associated
with health complications that may impact daily life.
In August 2014, the College of American Pathologists (CAP) published guidelines, based on a systematic
review of the literature and a consensus statement with other urologic and surgical specialty societies,
that focused on pathologic parameters important to the successful identification of patients with low-risk
28
prostate cancer for whom the choice of active surveillance would be safe and beneficial. CAP suggests
that active surveillance should be a “ubiquitously adopted and formalized strategy” for management of
men with low-risk prostate cancer.
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Gene Expression Analysis for Prostate Cancer Management
Risk Assessment
Several factors are considered to assess risk of prostate cancer progression. The Gleason score is
typically incorporated into baseline risk assessment models with other criteria, including AJCC stage
29
(primarily by digital rectal examination) and PSA serum level. Table 1 outlines the D’Amico risk criteria,
30
which are widely accepted for evaluating the risk of progression of localized prostate cancer. These
criteria are identical to those used by AUA in its 2007 guidelines (updated in 2011) for the management of
24
clinically localized prostate cancer.
Table 1. D’Amico Risk Criteria for Stratification of Prostate Cancer
30
Risk
PSA, ng/mL
Gleason Score
Low
≤10
<6
Intermediate
10-20
7
High
>20
8-10
AJCC: American Joint Committee on Cancer; PSA: prostate-specific antigen.
a
See Appendix Table 1.
AJCC Clinical Stage
T1, T2
T2b
T2b, T3
a
Other systems—typically nomograms derived from multivariate models—have been developed to predict
the risk of tumor progression and to stratify patients into active surveillance and immediate curative
treatment. These nomograms are based on clinical variables, such as clinical stage, biopsy results
(Gleason score, number of positive cores, length of the tumor), and PSA serum level. Epstein et al has
suggested 4 widely cited criteria that could be used to predict insignificant disease at needle biopsy:
tumor volume less than 0.5 mL; PSA density less than 0.15 ng/mL; Gleason patterns less than 4; and
31
tumor involvement of less than 3 mm of tissue in 1 needle core. None of the models is 100% reliable in
predicting risk of progression, because tumors of similar risk levels may exhibit widely divergent biological
behavior; hence, the necessity to identify better ways to prognosticate the behavior of newly diagnosed
localized prostate cancer.
The National Comprehensive Cancer Network (NCCN) also offers risk stratification criteria that were
derived from the same set of clinical and biochemical findings (see Appendix Table 2). Unlike the
D’Amico or the Epstein criteria, NCCN includes a category of “very low risk” that may reflect a large
portion of prostate cancer detected in routine screening.
A major consideration within this Assessment is the potential relationship between the presence of
pathology in a needle biopsy specimen and the risk for tumor progression if left untreated. It seems
reasonable to conclude that the presence of “unfavorable” pathology itself could be a surrogate to predict
progression in patients with localized tumors deemed to be low risk by clinical criteria. However, it is not
clear that using pathology-based criteria alone as a means to direct treatment, eg, choosing RP over
active surveillance, would result in improved outcomes. This contention is supported by evidence from the
Prostate Cancer Intervention versus Observation Trial (PIVOT) that showed no difference between RP
and observation in all-cause mortality or prostate cancer‒specific mortality rates at 12-year follow-up in
patients with localized cancer stratified by age, race, underlying morbidities, performance status, or tumor
32
histology. By contrast, more than 20% of men who underwent RP in PIVOT experienced a procedurerelated adverse event, including significantly higher rates of erectile dysfunction (81% vs 44%, p<0.001)
and urinary incontinence (17% vs 6%, p<0.001). These findings suggest that each patient must consider
the overall balance of benefits and harms when choosing a management approach for his localized
prostate cancer. The molecular profiling tests we assess here are intended to help address this clinical
challenge.
Gene Expression Analysis Testing
In this Assessment, we considered 2 commercially available gene expression tests intended to
characterize the biological behavior of localized prostate cancer: Prolaris® (Myriad Genetics, Salt Lake
City, UT) and Oncotype Dx® Prostate Cancer Assay (Genomic Health, Redwood City, CA). The goal of
either test is to identify discrete gene expression patterns that can be associated with specific cancerous
phenotypes (eg, risk of progression, cellular proliferation, the likelihood of recurrence or metastasis). Both
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tests use quantitative real-time polymerase chain reaction (RTPCR) technology to evaluate the
expression of specific sets of genes in tumor cells based on the intracellular levels of mRNA produced by
transcription of each gene. In this section, we provide an overview of the RTPCR methods used in the
tests, and subsequently outline specific characteristics and the target populations of the tests. Detailed
analysis of the specific technologies and biochemical procedures, which together comprise each
commercialized “test,” is beyond our scope. The components are commercially available and the methods
33
are common in clinical laboratories that perform RTPCR.
To analyze gene expression with RTPCR, total RNA is extracted from tissue samples and converted to
complementary DNA (cDNA) using a reverse transcriptase‒based method that yields a DNA copy of the
original mRNA complement within tumor cells. The cDNA obtained from this procedure is preamplified in
a set of enzymatic reactions prior to being subject to RTPCR. During RTPCR, preamplified cDNA is
34
further amplified by PCR in instruments called “thermal cyclers.” Thermal cyclers simultaneously amplify
and detect cDNA product in closed-tube systems (“low-density arrays”) that contain within multiple “wells”
the nucleic acid probes and primers, enzymes, buffer, and chromophore components necessary to
33,35
produce and detect DNA specific to the original mRNA expression.
Thermal cyclers are equipped with fluorescence detection modules that continuously monitor a
fluorescent signal produced as PCR progresses. Two key probe methods are used to assess the PCR
output using a fluorescent signal: light activation of a reporter chromophore that is released from a
hybridized probe during PCR (hydrolysis probe), or activation of a DNA-binding dye that intercalates into
34
double-stranded DNA thereby enhancing production of fluorescence (hybridization probe). An increase
in the emitted signal shows an increase in the amount of DNA product, which can be quantitated using
proprietary software based on the rate at which it grows relative to prespecified time points.
The results of RTPCR can be qualitative, signaling the presence (or absence) of a specific expressed
gene sequence, or quantitative, providing the number of copies of a gene sequence expressed in a tissue
sample. Both tests evaluated in this Assessment measure expression of cancer-related gene sets relative
to specific sets of housekeeping genes that are commonly expressed in mammalian cells. The
robustness of test results is defined by several technical performance parameters. Reaction linearity,
reflecting interassay variability, is evaluated by constructing a standard curve that is generated by RTPCR
2
quantitation of serially diluted samples of input mRNA template; the linearity of reaction is shown by an R
value greater than 0.980 for the standard curve. A second parameter, amplification efficiency, measures
the percentage of original mRNA template that is amplified, reflected by how much DNA is produced in
each amplification cycle. With an optimized assay, the amount of DNA product will double with each
exponential amplification cycle; an amplification efficiency of 90% to 100% is indicative of a robust test.
Finally, consistency across multiple reactions is necessary for an optimized assay, demonstrated by
interassay similarity in standard curves and quantitation results.
Table 2 shows the gene expression tests considered in this Assessment. Both tests use RTPCR
technology and formalin-fixed paraffin-embedded (FFPE) tumor biopsy specimens. No overlap exists
between the genes in either test.
Table 2. Commercialized Gene Expression Profiles for Predicting Prostate Cancer Aggressiveness
Test Name (Source)
Prolaris® (Myriad Genetics,
Salt Lake City, UT)
http://prolaristest.com/
Oncotype Dx® Prostate
Target Population
According to developer,
test is intended for “low or
intermediate-risk patients
who may be candidates for
surveillance as well as
patients who may be
potentially at higher risk
and benefit from closer
monitoring or additional
therapy”
According to developer,
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Test Description
A RTPCR-based
gene expression
assay that quantitates
mRNA expression of
31 predefined cell
cycle progression
genes normalized to
the activity of 15
housekeeper genes
A RTPCR-based
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Specimen
According to developer:
“Acceptable sample types are
FFPE tissue from blocks or
slides of prostatic
adenocarcinoma biopsies.
Ideally, blocks should include
at least 2 mm of linear tumor
on diagnostic H&E slides for
sample processing and RNA
extraction”
According to developer,
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
Cancer Assay (Genomic
Health, Redwood City, CA)
http://prostatecancer.oncotypedx.com/enUS/prostate/professional
test is intended for
“Patients with early stage,
localized cancer”
gene expression
assay that quantitates
mRNA expression of
17 genes (12 cancerrelated, 5 reference
genes)
specimens should comprise:
“Tumor-containing biopsy block
with the greatest amount of
highest grade carcinoma
(longest linear measurement).
Radical prostatectomy
specimens are not accepted.”
FFPE: formalin-fixed paraffin embedded; H&E: hematoxylin-eosin; RTPCR: real-time polymerase chain reaction
Validation of Gene Expression Tests
Gene expression tests must be validated to improve risk prediction or treatment outcomes in a multistep
process. The ACCE (analytic validity, clinical validity, clinical utility and ethical, legal and social
implications) Model System for Collecting, Analyzing and Disseminating Information on Genetic Tests
provides a framework that is applicable to various genetic tests (available at
http://www.cdc.gov/genomics/gtesting/ACCE/index.htm). Validation of genomic test panels typically
requires the following:




Identifying a starting panel of candidate genes or a DNA microarray; evaluating individual
components for strength of association with outcome(s) in a clinically relevant population and
selecting a smaller panel of nucleic acid markers with the best results.
Establishing the specific genotyping test performance characteristics, ie, whether the test
accurately and reproducibly detects the gene markers of interest (analytic validity).
Conducting preliminary performance studies in relevant populations to evaluate test result
associations with patient outcomes of interest (clinical validity); may be retrospective.
Determining whether the use of gene expression profiling to influence management decisions
reduces adverse event rates and/or improves health outcomes (clinical utility).
FDA 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® or Oncotype Dx® Prostate 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 (FDA) has chosen not to require any regulatory review of this test.
METHODS
Search Strategy
We searched the National Library of Medicine MEDLINE® database (via PubMed) through June 24,
2014, updated September 30, 2014, to identify literature published on the use of Prolaris® and Oncotype
Dx® Prostate. The search string is listed in Appendix Table 3.
The search included primary studies, review articles, systematic reviews, and editorials published in
English. We reviewed the websites of the test manufacturers for background and clinical information, as
well as FDA’s website for regulatory information. We also contacted test developers for additional
information not identified in the search.
Study Selection
We sought publications that reported on the analytic validity, clinical validity, or clinical utility of either test,
using human prostate tumor FFPE specimens obtained by needle biopsy according to the patient
indications and specific Assessment question formulation. Review articles, systematic reviews, and other
materials were also reviewed.
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Gene Expression Analysis for Prostate Cancer Management
Data Abstraction and Bias/Quality Assessment
As relevant, we abstracted data on: patient demographics and characteristics; tumor characteristics (eg,
grade, stage); study design and characteristics; clinical outcomes (eg, cancer-specific survival); and
associations between clinical outcomes and gene expression analysis results. Because of the nature of
available evidence on gene expression analysis using the panels under consideration, U.S. Preventive
Services Task Force criteria did not apply for evaluation of study quality (ie, risk of bias). Instead, we used
criteria set forth by Pepe et al to biomarker evaluation, which account for design aspects, including
prospective sample collection, clinical context, biomarker performance, the biomarker test, blinded
36
evaluation, and study size.
Medical Advisory Panel Review
This Assessment was reviewed by the Blue Cross and Blue Shield Association Medical Advisory Panel
(MAP) on September 18, 2014. To maintain the timeliness of the scientific information in this Assessment,
literature search updates were performed subsequent to the Panel's review (see Search Strategy section
above). If the search updates identified any additional studies that met the criteria for detailed review, the
results of these studies were included in the tables and text where appropriate. We did not identify any
studies that would change the conclusions of this Assessment.
A previous version of this Assessment was reviewed by the MAP on October 2, 2013. The available
evidence was insufficient to permit conclusions on the clinical validity of Prolaris® testing and no
published evidence was available on its analytic validity or clinical utility. No published evidence was
available on Oncotype Dx® Prostate testing.
FORMULATION OF THE ASSESSMENT
Patient Indications
Patients of interest were men with localized prostate cancer diagnosed using needle biopsy specimens.
This included men with low- or intermediate-risk disease who could choose between management by
active surveillance or immediate definitive therapy.
Technologies to Be Evaluated and Compared
Two RTPCR gene expression profile tests were compared with active surveillance:


Prolaris®
Oncotype Dx® Prostate
Health Outcomes




Overall survival
Disease-free survival
Quality of life
Urinary, bowel, and sexual function
Analytic Framework
Figure 1 shows the analytic framework of the role of gene expression profiling for risk stratification. It
places in context the analytic validity, clinical validity, and clinical utility steps needed to validate a gene
expression test.
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
Figure 1. Analytic Framework
Specific Assessment Question
We formulated this Assessment to address 1 key question:
What is the incremental value of gene expression testing compared with clinical criteria for
discriminating men with aggressive cancer from those with indolent disease to guide treatment
decisions that improve overall net health outcomes?
To answer the question, we assessed the evidence using an analytic framework (see Figure 1) evaluating
the analytic validity, clinical validity, and clinical utility of each test when used to assess gene expression
in FFPE tumor specimens obtained by diagnostic needle biopsy.



Analytic validity: measures technical performance, whether the test accurately and reproducibly
detects genomic information of interest.
Clinical validity: measures the strength of associations between selected genomic information
and clinical status.
Clinical utility: determines whether the use of specific genomic markers to guide treatment
decisions improves patient outcomes, such as survival or adverse event rate, compared with
standard treatment without genomic information.
REVIEW OF EVIDENCE
Overview of Available Evidence
We reviewed evidence on the use of 2 gene expression profile tests to predict the aggressiveness (or
indolence) of newly diagnosed localized prostate cancer. We organized this Assessment to evaluate the
analytic validity, clinical validity, and clinical utility of each test.
Analytic Validity
Prolaris®
We did not identify direct evidence of the analytic validity of Prolaris® in our literature search, through an
Internet search for grey literature, or on the developers’ websites. FDA’s website does not contain specific
information on either test. However, FDA’s MicroArray Quality Control (MAQC) project has evaluated the
performance of gene expression analysis platforms, including the TaqMan RTPCR platform (Applied
33,37
Biosystems, Foster City, CA) used in Prolaris.
The MAQC investigators gathered expression data for
4 titration pools from 2 distinct reference RNA samples generated at multiple test sites on 7 microarraybased and 3 alternative technology platforms. The RNA samples used were a Universal Human
Reference RNA (catalog no. 740000; Stratagene, La Jolla, CA) and Human Brain Reference RNA
(catalog no. 6050; Ambion, Austin, TX). They found very similar performance across platforms, with a
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median coefficient of variation ranging from 5% to 15% for the quantitative signal and 80% to 95%
concordance for qualitative detection between sample replicates.
Oncotype Dx® Prostate
38
We identified 1 study specifically designed to assess the analytic validity of Oncotype Dx® Prostate.
The investigators measured expression of the 12 cancer-related and 5 reference genes that comprise the
test using mRNA prepared from 10 microdissected FFPE prostate tumor specimens obtained by needle
biopsy. The FFPE specimens were provided by the Cleveland Clinic, and centrally reviewed by 2
pathologists. A Gleason score for each sample was assigned using the 2005 International Society of
39
Urological Pathology Consensus guidelines. The methods used for the study generally followed those
outlined in the Background section. Test parameters investigated in this study included amplification
efficiency, analytical sensitivity, and accuracy of the multigene RTPCR expression assay; acceptable
numerical ranges for each quantity were prespecified for quality control. Assays also were internally
controlled by incorporation of 5 wells containing processing controls: 1 well with RNA from prostate
cancer specimens (positive control for reverse transcription, preamplification, and quantitative PCR); 1
well with human genomic DNA (positive control for genomic DNA detection), and 3 wells containing
nuclease-free water (negative control for contamination). Gene assays were performed in triplicate,
requiring 2 valid wells to be scored positive. Gene expression levels were quantified in a Roche
LightCycler® 480 (Roche Applied Science, Indianapolis, IN) thermal cycler.
The results showed that the assay could accurately measure expression of the 12 cancer-related and 5
reference genes used in the commercial test over a range of mRNA inputs found in typical prostate
cancer needle biopsy specimens. A low input level of 5 ng of mRNA was used to reflect the lowest 2.5
3
percentile (0.0225 cm ) of a tumor sample. The limit of quantitation for the assay was an mRNA
concentration of 0.5 ng/L. The analytical accuracy showed an average bias across all samples of less
than 9.7% at mRNA 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.
Analytical precision was assessed by examining variability in results obtained using the same mRNA
input, whereas reproducibility was measured by calculating both within and between mRNA input
variation. When converted to Genomic Prostate Score (GPS) units, the unit of measure used in the test,
the SD for analytical precision was 1.86 GPS units (95% confidence interval [CI], 1.60 to 2.20) on the
100-unit scale. The SD for reproducibility was 2.11 GPS units (95% CI, 1.83 to 2.50) on the 100-point
scale.
Summary of Analytic Validity
Prolaris®
Although the MAQC project results on the TaqMan assay platform, on which the Prolaris® test operates,
appears to be a reasonable surrogate for expected test performance, we question their adequacy to
support the analytic validity of the commercialized assay. The MAQC project was tightly controlled, used
optimized assay methods, and tested platform performance using commercially available, high-quality,
well-characterized mRNA samples as RTPCR input. However, we do not know whether the performance
of RTPCR using commercially available Human Brain Reference RNA, eg, is comparable to that using
mRNA samples isolated from prostate tumor specimens. Perhaps more important, the MAQC project did
not report on the specific set of cancer-related and reference genes that comprise Prolaris®. Although we
would expect clinical laboratories that use Prolaris® to adhere to stringent quality control criteria, we have
no direct evidence to assess test performance in that setting, and so cannot draw conclusions about its
analytical validity.
Oncotype Dx® Prostate
One well-documented study provides evidence of the analytic validity of this test to accurately and
precisely analyze the expression of 12 cancer-related and 5 housekeeping genes over a wide range of
input mRNA values used to construct the GPS for human prostate tumor specimens.
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Clinical Validity
Prolaris®
One full-length article reports the results of a validation study of Prolaris® to determine its predictive value
40
for prostate cancer death in a conservatively managed needle biopsy cohort. Cuzick et al did not state
whether their study adhered to the PRoBE (prospective-specimen-collection, retrospective-blinded
36
evaluation) criteria suggested by Pepe et al for an adequate biomarker validation study. They did report
that the cell-cycle expression data were reviewed absent knowledge of clinical data, which conforms to
the criteria. However, patients were identified retrospectively from tumor registries, which does not
conform to the PRoBE criteria.
Patients from 6 cancer registries in Great Britain were included if they had clinically localized prostate
cancer diagnosed by needle biopsy between 1990 and 1996; were younger than 76 years at diagnosis;
had a baseline PSA serum measurement; and were conservatively managed. Potentially eligible patients
who underwent RP, died, or showed evidence of metastatic disease within 6 months of diagnosis were
excluded. Those who received hormone therapy prior to diagnostic biopsy also were excluded. The
original biopsy specimens were retrieved, and centrally reviewed by a panel of expert urologic
pathologists (a) to confirm the diagnosis and (b), where necessary, to reassign Gleason scores using a
41
contemporary and consistent interpretation of the Gleason system.
Tumor cells were microdissected from needle biopsy blocks, with the number of cells determined by the
volume of cancer available in the core sample. This process enabled preservation of any remaining
cancer tissue for gene expression studies. The samples were processed using conventional methods;
total RNA was extracted and converted to single-strand cDNA using the High-Capacity cDNA Archive Kit
as described by the manufacturer (Applied Biosystems). A cell cycle progression (CCP) score consisting
of expression levels of 31 predefined CCP genes and 15 housekeeper genes was generated using
TaqMan low-density arrays. The values of each of the 31 CCP genes were normalized by subtracting the
average of up to 15 nonfailed housekeeper genes for that replicate.
Of 776 patients diagnosed by needle biopsy and for whom a section was available to review histology,
needle biopsies were retrieved for 527 (68%), of whom 442 (84% of subsample) had adequate material to
assay. Among the 442, 349 (79%) yielded 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 of 90 deaths from
prostate cancer occurred within 2799 person-years of actual follow-up. The main assessment of the study
40
was a univariate analysis of the association between death from prostate cancer and the CCP score. 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 serum
value; clinical stage; extent of disease (percent of positive cores); age at diagnosis; Ki-67
immunohistochemistry; and initial treatment. The results are shown in Table 3.
Table 3. Univariate and Multivariate Analysis for Death From Prostate Cancer in the Cuzick (2012)
Validation Study
Variable
1-unit increase in CCP score
Gleason score
<7
7
>7
log (1 + PSA)/(ng/mL)
Proportion of positive cores
<50%
50 to <100%
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n
349
349
106
152
91
349
69
106
Univariate
Hazard Ratio (95% CI)
2.02 (1.62 to 2.53)
Multivariate
Hazard Ratio (95% CI)
1.65 (1.31 to 2.09)
0.46 (0.25 to 0.86)
Referent
2.70 (1.72 to 4.23)
1.70 (1.31 to 2.20)
0.61 (0.32 to 1.16)
Referent
1.90 (1.18 to 3.07)
1.37 (1.05 to 1.79)
0.50 (0.22 to 1.12)
Referent
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
100%
160
1.66 (1.01 to 2.73)
Age at diagnosis, y
349
1.00 (0.96 to 1.04)
Clinical stage
T1
38
0.75 (0.32 to 1.75)
T2
106
Referent
T3
43
1.74 (0.90 to 3.38)
Hormone use
No
200
Referent
Yes
149
1.97 (1.30 to 2.98)
CCP: cell cycle progression; CI: confidence interval; PSA: prostate-specific antigen.
The median CCP score was 1.03 (interquartile range, 0.41-1.74). The primary univariate analysis
suggested that a 1-unit increase in CCP score was associated with a 2-fold increase in the risk of dying
from prostate cancer (see Table 3). 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
serum level remained in the final model. Further exploratory multivariate modeling to produce a combined
score (including CCP, Gleason score, PSA serum 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
suggested that 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 death rate ranged from 5.1% to 20.9% based on Gleason score and
PSA serum level; the range, when assessed against the combined CCP, Gleason score, and PSA serum
level, was 3.5% to 41%. They cautioned, however, that because death rates were rare in this group,
larger cohorts are required to fully assess the value of the combined CCP score.
Kaplan-Meier analyses of 10-year risk of prostate cancer death stratified by CCP score groupings are
shown in Table 4. Cuzick et al reported no significance tests for the estimates. Nor did they explain the
apparent substantial difference in mortality rates among patients in the 0 ≤ CCP ≤ 2 grouping (range,
19.3%-21.1%) and those in the 2 < CCP ≤ 3 and > 3 groupings (range, 48.2%-74.9%). The difference
may simply reflect clinical criteria, eg, proportions of lower compared with higher Gleason grade cancers,
respectively.
Table 4. Kaplan-Meier Estimates of Prostate Cancer Death at 10 Years According to CCP Score
Groupings in the Cuzick (2012) Validation Study
CCP Score Group
CCP ≤ 0
0 < CCP ≤ 1
1 < CCP ≤ 2
2 < CCP ≤ 3
>3
CCP: cell cycle progression.
N
36
133
114
50
16
10-Year Death Rate, %
19.3
19.8
21.1
48.2
74.9
Five sets of data from 4 other publications are available on Prolaris® testing in different populations of
prostate cancer patients (see Table 5).
Table 5. Other Studies of Prolaris®
Study
(Country)
42
Cuzick (2011)
(U.S.)
42
Cuzick (2011)
(Great Britain)
Cooperberg
43
(2013) (U.S.)
No. of Patients
(Years Included)
366 (1985-1995)
Source of Tumor Specimen and
Management
Radical prostatectomy
Outcome Associated With
CCP Score
Biochemical recurrence at 10 y
337 (1990-1996)
TURP followed by conservative
management
Radical prostatectomy
Prostate-specific mortality at
10 y
Biochemical recurrence at 10 y
413 (1995-2011)
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
44
Freedland (2013)
141 (1991-2006)
Diagnostic biopsy followed by EBRT
Biochemical recurrence at 10 y
(U.S.)
45
Bishoff (2014)
615 (3 cohorts)
Diagnostic biopsy followed by radical Biochemical recurrence or
(U.S.)
(1997-2006)
prostatectomy
metastatic progression at 10 y
CCP: cell cycle progression; EBRT: external-beam radiotherapy; TURP: transurethral resection of the prostate.
One retrospective validation study included 2 cohorts of patients, one from the United States who had
undergone RP between 1985 and 1995 (n=366), which provided the tumor samples for gene expression
analysis, and a cohort that had undergone diagnostic transurethral resection of the prostate (TURP)
42
between 1990 and 1996 (n=337) for active surveillance. Another study was prospectively performed in
the United States in a cohort of 413 patients who had undergone RP between 1995 and 2011 at an
43
academic medical center. Gene expression analyses were performed in these studies, as outlined in
40
Cuzick et al above, with the same caveats. In a third retrospective study, CCP analysis was used as an
adjunct to predict the risk for biochemical recurrence among 141 men diagnosed with prostate cancer
between 1991 and 2006, who ultimately underwent EBRT. Although biochemical recurrence is often
monitored as an indicator of prostate cancer recurrence after RP or EBRT, it is regarded as an
intermediate marker. A fourth study included 3 male cohorts, selected from registries at 3 different centers
in the United States, who underwent diagnostic needle biopsy or simulated needle biopsy followed by
45
RP. The patients in these cohorts were followed for biochemical recurrence or metastatic progression at
10 years.
The additional Prolaris® studies consistently report that the CCP score combined with clinical risk factors
can inform prediction of prostate cancer biochemical recurrence or metastatic progression following
definitive treatment (ie, RP, EBRT), allowing for reclassification of patients into different risk categories
42
43
than those predicted by clinical results alone. Cuzick (2011) and Cooperberg (2013) indicated that the
populations included in their studies are not the same as those in the 2012 needle biopsy cohort study by
the Cuzick group, and thus their results are not comparable. Instead, they agreed that the primary utility
of the CCP score will be in screen-detected, needle biopsy‒diagnosed patients with low-risk disease. The
45
Bishoff study provided evidence that the CCP score obtained from tumor specimens can be used to
identify men in whom surgery alone was likely to fail.
Oncotype Dx® Prostate
We included 1 publication that compiled results of studies in 3 cohorts of contemporary (1997-2011)
patients in a prostatectomy study (N=441; Cleveland Clinic database), a biopsy study (N=167; Cleveland
Clinic database), and an independent clinical validation study cohort (N=395; University of California, San
46
Francisco Urologic Oncology Data Base). In this Assessment, we included results from the clinical
validation study and prostatectomy study because they provide information on the potential clinical
validity of this test. Baseline characteristics for all 3 cohorts are summarized in Appendix Table 4. The
cohorts had a mix of low to low-intermediate clinical risk characteristics according to NCCN and 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 RP 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
47
Tumor Marker Prognostic Studies) guidelines for biomarker validation. 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 experience recurrence, 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 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
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
groupings was correlated to clinical recurrence-free interval in regression-to-the-mean estimated survival
curves.
The validation study showed that the GPS would further refine patient stratification within NCCN
categories, as summarized in Table 6. The proportions presented in the table are estimated from a plot of
46
GPS compared with the percent likelihood of favorable pathology. 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 recurrence), 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% 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.
Table 6. Reclassification of Prostate Cancer Risk Categories With Oncotype Dx® Prostate
NCCN Risk
Level
Estimated Mean Likelihood of Favorable Tumor Pathology
Estimated Corresponding
GPS, Range
NCCN Criteria, %
GPS + NCCN Criteria, % Range
Very low
84
63-91
76
Low
55-86
56
Intermediate
29-75
GPS: Genomic Prostate Score; NCCN: National Comprehensive Cancer Network.
60-6
53-1
66-4
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 “favorable pathology” in a biopsy specimen is unclear.
Furthermore, extrapolation of this evidence to an 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.
The prostatectomy study results provide estimates of reclassification of clinical recurrence risk from those
39
based only on AUA criteria (Epstein et al ) to those based on AUA criteria combined with the GPS.
These results are summarized in Table 7. The GPS groups are organized by tertiles defined in the overall
study.
Table 7. Reclassification of Prostate Cancer 10-Year Clinical Recurrence Risk With Oncotype Dx®
Prostate
Overall 10-Year Risk, %
10-Year Risk, %
10-Year Risk, %
(AUA Risk Level)
(GPS Low Group)
(GPS Intermediate Group)
3.4 (low)
2.0
3.4
9.6 (intermediate)
2.8
5.1
18.2 (high)
6.2
9.2
AUA: American Urological Association; GPS: Genomic Prostate Score.
10-Year Risk, %
(GPS High Group)
7.0
14.3
28.6
In the AUA intermediate group, the 10-year recurrence rate was 9.6% in the entire RP patient subset.
When the GPS was incorporated into the analysis, the 10-year recurrence rate fell to 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 that 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.
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Summary of Clinical Validity
Prolaris®
Evidence of the clinical validity of Prolaris® in predicting the aggressiveness of localized prostate cancer
derives from 1 retrospective study by Cuzick et al that used tumor mRNA prepared from archived FFPE
40
needle biopsy specimens. In their 2012 article, Cuzick et al concluded that the CCP score groupings are
associated with 10-year cancer-specific survival using Kaplan-Meier analyses. The relative increase in
risk of prostate cancer death accompanying higher CCP scores (HR=1.65 per 1-unit increase, with 50%
of scores falling in a 1.5-unit range) does not allow for inference of clinical validity. At a minimum,
reclassification results are needed for this outcome.
Four additional studies of Prolaris® (see Table 5) with study objectives and patient cohorts different from
those of Cuzick et al (2012) were performed. The results of these 4 studies suggest some association
between elevated CCP scores combined with PSA titer and Gleason grade in predicting biochemical
recurrence after RP or EBRT, or risk for metastatic progression in TURP or RP cohorts. The patients and
management approaches in these 4 studies do not represent the population of interest for or address the
primary question of interest in this Assessment.
Oncotype Dx® Prostate
The Klein clinical validation study results showed that combined use of GPS plus clinical criteria can
reclassify patients on an individual basis within established clinical risk categories. Whether the GPS
could predict the biological aggressiveness of a tumor—hence its propensity to progress—based 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 actually had elective RP within 6 months of diagnostic biopsy.
Clinical Utility
Prolaris®
We found no studies to support the clinical utility of Prolaris®. However, we identified 2 articles reporting
results of retrospective survey studies that assessed the potential impact of this test on attending
48,49
physicians’ treatment decisions.
Both author groups have suggested that 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 potential uptake of the test by urologists, it does not demonstrate
clinical utility in clinical treatment settings.
Oncotype Dx® Prostate
50
Klein et al reported a decision-curve analysis that they have proposed reflects the clinical utility of
46
Oncotype Dx® Prostate. In this analysis, they investigated the predictive impact of the GPS in
51
combination with the Cancer of the Prostate Risk Assessment (CAPRA) validated tool versus the
CAPRA score alone on the net benefit for outcomes of patients with high-grade disease (Gleason >4+3),
high-stage disease, and combined high-grade and high-stage disease. They reported that, over a range
of threshold probabilities for implementation of 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
GPS findings to assess the balance of benefits and harms (net benefit) when weighing the choice to
proceed immediately to curative RP with its attendant adverse sequelae, or to enter an active surveillance
program with deferred surgery. The latter choice would have an immediate benefit realized by forgoing
RP, but could be associated with greater downstream risks associated with disease progression and
subsequent therapies. 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 RP 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.
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Summary of Clinical Utility
No direct clinical evidence was found to support the clinical utility of Prolaris® or Oncotype Dx® Prostate
in the patient population we considered in this Assessment.
DISCUSSION
Evidence
Laboratory-based tests are being developed to predict the risk for progression (or indolence) of prostate
cancer. The patient population for these tests is men who have cancer that was first diagnosed by a
positive PSA screening result and digital rectal examination, and confirmed by other examinations and
needle biopsy. A substantial proportion of these lesions will be low risk, localized, and not likely to pose a
significant risk in the lifetime of these patients; their cancer is defined as indolent. However, 15% to 30%
16,17,19
of such tumors will progress rapidly.
The clinical challenge is how to identify and (re)classify patients
to avoid overtreating those with a biologically indolent cancer and to minimize undertreating those with a
biologically aggressive cancer. Two gene expression tests have been developed and commercialized to
predict these risks: Prolaris® and Oncotype Dx® Prostate. The tests differ in terms of the gene
expression patterns they evaluate, and in how they are combined with common clinical prognostic
findings (PSA serum level, Gleason score).
Published evidence on Prolaris® and Oncotype Dx® Prostate testing is sparse. One report has shown
38
convincing evidence of the analytic validity of the Oncotype Dx® Prostate commercial test. We did not
find any direct evidence to support the analytic validity of the commercial Prolaris® test.
One clinical validation study of Prolaris® was based on patients culled from 6 cancer registries in Great
40
Britain. The study examined the ability of the test to demonstrate an association between CCP score
plus clinical risk factors and risk of prostate cancer death at 10 years postdiagnosis. Although an
association between CCP score and prostate cancer death was found, and suggested improved
prognostication over clinical factors, this study did not demonstrate—or allow inferring—clinical utility. A
key strength of this trial is that all patients had baseline PSA serum levels at study entry and all diagnostic
slides were re-reviewed to assure commonality with modern Gleason scores. This corresponds well with
current practice in the United States. However, according to the investigators, the cohort in this study may
not reflect current prostate cancer treatment in that they were universally managed conservatively,
despite the presence of higher risk characteristics such as T3 lesions (12% of cases), Gleason scores
greater than 7 (26% of cases), and median serum PSA levels around 20 ng/mL (range 12-42 ng/mL).
Furthermore, the archived biopsy specimens have limitations secondary to sampling a small portion of
each tumor yielding a small amount of tissue from which to generate a gene expression profile; we
explore this issue as it relates to assay accuracy and reproducibility below.
The clinical validation study results of Klein et al have suggested that combining GPS and clinical criteria
46
could be used to reclassify patients on an individual basis within clinical risk categories. However, the
primary outcome of this study was the likelihood of favorable pathology in a tumor sample, which would
reflect the risk of disease recurrence in patients who had RP within 6 months of their diagnostic biopsy,
and perhaps reflect the propensity for a tumor to progress in vivo if untreated. However, these findings do
not specifically address the ability of a GPS to aid reclassification of patients under active surveillance
and guide treatment. Moreover, the Klein study decision-curve analysis does not provide evidence of
clinical utility in men under active surveillance.
We have several concerns about technical aspects of both tests. First, it is unclear what either gene
expression score means in terms of a direct association with the cancerous phenotype. A relationship has
been suggested for gene groupings related to CCP score—albeit not in the same gene groupings—for
52
53
54
other cancers, such as breast, lung, and glioblastoma. However, no direct evidence of a genotypic or
a phenotypic relationship is available for prostate cancer. Second, although the analytic methods used for
both tests are commercialized and used in clinical laboratories, they must be carefully monitored for
quality control. Both methods are subject to numerous methodologic variables that can affect test results
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and interpretation. As noted above, biopsy specimen size and quality are key parameters that can affect
gene expression profiling. Additional variables include fixation time and method used; storage time and
aging effect; microdissection and specimen selection; RNA extraction method and RNA quality; cDNA
reaction fidelity and completeness, including failure to amplify some genes; and the specific platform used
55
for the test. Replication of results for any specific patient would depend on the availability of additional
identical specimens. Third, it is not clear whether core-extended needle biopsy specimens obtained for
56
diagnosis always capture the full spectrum of disease. Finally, FDA does not oversee the 2 tests that
are marketed for guiding clinical management of prostate cancer. This void introduces uncertainty as to
what test performance could be expected, and the quality assurance processes necessary to ensure
results are reliable. The availability of the tests under CLIA regulations mitigates this concern somewhat,
but does not alleviate it.
Limitations
The 2014 CAP consensus statement and guidelines provide a succinct conclusion on use of molecular
28
methods to stratify or reclassify prostate cancer for clinical management purposes. CAP has
acknowledged that a critical need exists for biomarkers to predict and monitor prostate cancer grade,
stage, metastatic potential, and potential response to candidate drugs with better accuracy and less
morbidity than currently available clinical metrics offer. CAP has indicated that few candidates for
molecular testing have prognostic power independent of the conventional parameters of tumor grade,
serum PSA, and tumor stage. Furthermore, CAP has noted that the molecular tests have mostly been
tested in the pre- or postoperative setting, and that results may not be applicable for active surveillance
decisions.
In a statement pertaining to “Precision Medicine Markers,” CAP has stated: “Currently available data do
not support a recommendation for any particular molecular tool or test for determining eligibility of patients
into AS [active surveillance] programs. Several tests have been offered commercially and, although
purported to be useful, need further clinical experience and prospective validation for consistent inclusion
28
into clinical decision-making algorithms.”
Future Research Needs
Neither clinical validity nor clinical utility has been established for either gene expression test used in the
active surveillance setting. The primary missing piece is clinical utility. Can either test be used to direct
patient management? Does either test provide actionable patient management information beyond that
provided by established clinical criteria to direct patient management? Classification and reclassification
must be sufficiently robust to alleviate concerns over balancing uncertain relative risks of treatmentrelated morbidities and rapid disease progression to incurability. It is also unclear whether either test
would need to be repeated in patients under active surveillance to evaluate possible changes in cancer
behavior based on progressive genotypic and phenotypic alterations.
A randomized controlled trial could provide the most definitive evidence for clinical utility of gene
expression analysis to guide prostate cancer management. However, it is unlikely that a prospective trial
with newly diagnosed prostate cancer patients could be designed and executed to evaluate clinical utility
using the timeframe required (10-year minimum) for prostate cancer mortality in a PSA-screened cohort in
the United States. A prospective utility study could be designed using archival specimens from large
prospective randomized trials with appropriate patients. Such a study would be subject to criticisms
including testing methods and tumor sampling. But, it could provide evidence of utility if designed,
36,57
powered, and performed in adherence to criteria for biomarker studies.
Although we are not aware
that such trials are being contemplated, candidate trials with specimens and patient cohorts suited to this
32
58
could include PIVOT ; the European Randomized Study of Screening for Prostate Cancer (ERSPC) ;
59
the Prostate, Lung, Colorectal and Ovarian (PLCO) Screening Trial ; and the Prostate Cancer
18
Prevention Trial.
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Conclusions
Two RTPCR-based gene expression analysis tests—Prolaris® and Oncotype Dx® Prostate—are
commercially available in the United States. We evaluated published evidence on use of these test
results in combination with accepted clinical criteria (Gleason score, PSA serum level, clinical stage) to
further stratify biopsy-diagnosed, localized prostate cancer according to expression levels of discrete sets
of genes thought to reflect the biological aggressiveness of a lesion. Such information would be used to
assist in initial clinical disease management, specifically whether a patient should proceed to definitive
therapy (ie, surgery) or to active surveillance. The published evidence is insufficient to establish the
analytic validity, clinical validity, or clinical utility of Prolaris® in the specific patient population and clinical
setting we considered. Evidence also is insufficient to establish the clinical validity and utility of Oncotype
Dx® Prostate in the specific patient population and clinical setting we considered.
SUMMARY OF APPLICATION OF THE TECHNOLOGY EVALUATION CRITERIA
Based on the available evidence, the Blue Cross and Blue Shield Association Medical Advisory Panel
made the following judgments about whether use of the Prolaris® or the Oncotype Dx® Prostate gene
expression analysis test to guide treatment decisions in men with newly diagnosed, localized prostate
cancer meets the Blue Cross and Blue Shield Association Technology Evaluation Center (TEC) criteria.
1. The technology must have final approval from the appropriate governmental regulatory
bodies.
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® or Oncotype Dx® Prostate 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.
2. The scientific evidence must permit conclusions concerning the effect of the technology
on health outcomes.
Analytic Validity
No published evidence has demonstrated the analytic validity of Prolaris® testing, although it is indirectly
suggested by results from the MicroArray Quality Control project. One publication provides sufficient
evidence to support the analytic validity of Oncotype Dx® Prostate testing.
Clinical Validity
Evidence supporting the clinical validity of Prolaris® testing includes a retrospective cohort (N=349)
selected from 6 cancer registries in Great Britain. In the primary univariate analysis, a 1-unit increase in
the cell cycle progression (CCP) score was associated with a 2.02-fold (95% confidence interval [CI], 1.62
to 2.53) increase in the risk of death from prostate cancer at 10-year follow-up. Multivariate analyses
showed only the CCP score (hazard ratio [HR] for a 1-unit increase in CCP score, 1.65; 95% CI, 1.31 to
2.0), Gleason score less than 7 (HR=0.61; 95% CI, 0.32 to 1.16), and prostate-specific antigen (PSA) titer
(HR=1.37; 95% CI, 1.05 to 1.79) were associated with prostate cancer‒specific mortality at 10 years. This
evidence has several limitations. First, according to the investigators, the cohort in this study may not
reflect current prostate cancer treatment in that patients were universally managed conservatively,
despite the presence of higher risk characteristics such as T3 lesions (12% of cases), Gleason scores
greater than 7 (26% of cases), and median serum PSA levels around 20 ng/mL (range 12-42 ng/mL).
Furthermore, the archived biopsy specimens have limitations secondary to sampling a small portion of
each tumor yielding a small amount of tissue from which to generate a gene expression profile. Finally,
the authors acknowledge more empirical data are needed to establish a developmental multiple sampling
process for tumor specimens, to assure accuracy and reproducibility of the assay based on needle biopsy
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
specimens. Based on these limitations, the evidence is insufficient to support the clinical validity of
Prolaris® testing.
One article has reported on the clinical validity of Oncotype Dx® Prostate testing, specifically to predict
adverse tumor pathology in needle biopsy specimens. The validation study cohort (N=395), identified
from the University of California, San Francisco Urologic Oncology Data Base, had a mix of low to lowintermediate clinical risk characteristics using National Comprehensive Cancer Network criteria. These
men would be eligible to enter an active surveillance program according to clinical criteria. The
prespecified primary end point was the ability of the Genomic Prostate Score (GPS) to predict the
likelihood of favorable pathology in the tumor specimens. Favorable pathology was defined as freedom
from high-grade or non-organ-confined disease. The findings suggest that a lower GPS would increase
the likelihood of favorable pathology (ie, less biologically aggressive disease) upward (ie, a potentially
lower risk of disease progression), and vice versa within a clinical stratum. However, whether the
presence of adverse pathology in a tumor biopsy is sufficient to extrapolate to risk of tumor progression in
vivo is unclear when considered in the context of evidence from the Prostate Cancer Intervention versus
Observation Trial [PIVOT]), which showed no significant survival advantage for immediate intervention
(radical prostatectomy [RP]) compared with observation in men with clinically low risk disease. Thus, the
main value of the GPS would be to reclassify clinically low risk men into what would be deemed a
“biologically low risk” (indolent) category with greater predictive power than clinical classification alone.
This remains to be demonstrated in an active surveillance study.
In their prostatectomy study, Klein et al showed a reduction in the clinical recurrence rate in men with
lower GPS compared with those in higher GPS categories. They suggested that the GPS helps to further
stratify tumors according to biological aggressiveness. However, the evidence does not demonstrate the
effect of reclassification on a clinical end point (eg, overall survival, cancer-specific survival) in patients
under active surveillance, nor does it reflect the potential benefit realized by avoiding unnecessary RP
and its adverse events. Therefore, the evidence is insufficient to support the clinical validity of Oncotype
Dx® Prostate testing in men under active surveillance.
Clinical Utility
No direct evidence was found to support the clinical utility of Prolaris® testing.
Klein et al reported decision-curve analyses to support the clinical utility of Oncotype Dx® Prostate
testing. They suggested a potential effect of the combined GPS and Cancer of the Prostate Risk
Assessment data to assess the net benefit of surgery versus no treatment for each category of highgrade disease (Gleason >4+3), high-stage disease, and combined high-grade and high-stage disease in
prostate tumor specimens. They concluded that the combined use of the GPS and clinical criteria could
lead to fewer treatments among patients with favorable pathology without increasing the proportion who
are not treated but require intervention. As noted above, it is not clear whether adverse pathology in a
tumor specimen represents an adequate surrogate to predict risk of in vivo tumor progression. Moreover,
this study provided no direct evidence of the clinical utility for Oncotype Dx® Prostate testing in choosing
between RP or an active surveillance program because all patients—although eligible for active
surveillance—elected RP within 6 months of diagnostic biopsies. Therefore, the evidence is insufficient to
support the clinical utility of Oncotype Dx® Prostate testing in men under active surveillance.
3. The technology must improve the net health outcome.
The evidence is insufficient to determine whether Prolaris® or Oncotype Dx® Prostate testing affects the
net health outcome.
4. The technology must be as beneficial as any established alternatives.
The evidence is insufficient to determine the incremental value of Prolaris® or Oncotype Dx® Prostate
testing compared with established clinical criteria alone for discriminating men with aggressive and
indolent disease to guide treatment decisions that improve the net health outcome.
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TEC ASSESSMENT
Gene Expression Analysis for Prostate Cancer Management
5. The improvement must be attainable outside the investigational settings.
The evidence is insufficient to determine whether Prolaris® or Oncotype Dx® Prostate testing improves
health outcomes in the investigational setting.
Based on the above, neither the Prolaris® nor Oncotype Dx® Prostate gene expression test meets the
Blue Cross and Blue Shield Association Technology Evaluation Center (TEC) criteria.
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TEC ASSESSMENT
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APPENDIX
Appendix 1. Staging of Prostate Cancer
Prostate cancer is clinically staged according to the 2010 modification of the 2002 TNM (primary tumor,
23
lymph node, metastases) classification for adenocarcinoma of the prostate. In Appendix Table 1, the T
category is based on clinical examination, imaging, endoscopy, biopsy, and biochemical tests. The N
category is based on clinical examination or imaging. The M category is based on clinical examination,
imaging, skeletal studies, and biochemical tests. We focused on patients with stage I or IIA disease.
Appendix Table 1. Prostate Cancer Clinical Stage Groupings
Stage
I
IIA
IIB
III
IV
T
T1a–c
T2a
T1–2a
T1a–c
T1a–c
T2a
T2b
T2b
T2c
T1–2
T1–2
T3a–b
T4
T4
Any T
Any T
N
N0
N0
N0
N0
N0
N0
N0
N0
N0
N0
N0
N0
N0
N0
N1
Any N
M
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M1
Appendix Table 2. NCCN Clinical Risk Groupings for Prostate Cancer
Risk Groupings for Prostate Cancer
NCCN Very Low Risk (Must meet ALL of the following criteria):
• Gleason score ≤6
• PSA <10 ng/mL
• Clinical stage T1c
• Fewer than 3 positive biopsy cores, ≤50% involvement in any core
• PSA density <0.15 ng/mL/g
NCCN Low Risk (Must meet ALL of the following criteria):
• Gleason score ≤6
• PSA <10 ng/mL
• Clinical stage T1-T2a
Modified NCCN Intermediate Risk (Must meet ONE of the following):
• Gleason score ≤6, AND clinical stage T2b-T2c, OR PSA 10-20 ng/mL
• Gleason score 3+4, AND all of the following:
Fewer than 4 positive biopsy cores
Clinical stage T1-T2c
PSA ≤20 ng/mL
See Appendix Table 1 for details on clinical stages.
NCCN: National Comprehensive Cancer Network; PSA: prostate-specific antigen.
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Appendix Table 3: Search Strategy
Search Strategy (Through June 24, 2014)
“Prostatic Neoplasms” [Mesh] OR ((prostate OR prostatic) AND (cancer OR cancers OR carcinoma* OR neoplasms))
AND “pathology” [Subheading] OR pathology OR biopsy OR biopsies OR tissue AND “Prognosis” [Mesh] OR
prognosis OR prognostic OR indolent OR aggressive OR stratification AND (genomic* OR genome OR genomes)
AND (Prostate OR Prostatic) in the title AND Filters: Humans; English
Appendix Table 4. Baseline Characteristics of Patient Cohorts in Klein et al (2014)
46
Characteristics,
Prostatectomy Study
Biopsy Study
Validation Study
% Patients
(N=441)
(N=167)
(N=395)
Surgery year, range
1987-2004
1998-2007
1998-2011
Mean age (SD), y
61 (6.3)
60 (6.4)
58 (7.1)
Race
White
83
83
91
Black
12
17
3
Other
5
1
6
Clinical tumor stage
T1
66
89
58
T2
34
11
42
Baseline PSA, ng/mL
≤4
14
14
21
>4-10
68
80
66
>10-20
13
7
13
>20
5
0
0
Biopsy Gleason score
≤6
70
57
76
7
25
43
24
≥8
5
0
0
Surgical Gleason score
≤6
35
17
48
7
61
79
50
≥8
5
4
2
Pathologic tumor stage
T2
52
58
78
T2+
7
14
2
T3
41
28
21
Adverse pathology
Gleason score <3+4, pT2
43
64
69
Gleason score ≤3+4, pT3
25
14
13
Gleason score ≥4+3, pT2
9
8
9
Gleason score ≥4+3, pT3
23
13
9
a
CAPRA score
0
5
1
36
2
38
3
16
4
5
Missing
2
a
NCCN risk group
Very low
9
Low
48
Intermediate
41
Missing
2
CAPRA: Cancer of the Prostate Risk Assessment; NCCN: National Comprehensive Cancer Network; p = pathologic;
PSA: prostate-specific antigen.
a
Blank cells for CAPRA score and NCCN risk group indicate data not reported.
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