| Coverage Policy Manual | |
| Policy #: | 2004017 |
| Category: | Laboratory |
| Initiated: | May 2004 |
| Last Review: | December 2023 |
|
|
|
|||||||||||
| Genetic Test: Genetic and Protein Biomarkers for the Diagnosis and Cancer Risk Assessment of Prostate Cancer | |
|
|
|
| Description: |
Prostate cancer is the most common cancer, and the second most common cause of cancer death in men. Prostate cancer is a complex, heterogeneous disease, ranging from microscopic tumors unlikely to be life-threatening to aggressive tumors that can metastasize, leading to morbidity or death. Early localized disease can usually be treated with surgery and radiotherapy, although active surveillance may be adopted in men whose cancer is unlikely to cause major health problems during their lifespan or for whom the treatment might be dangerous. In patients with inoperable or metastatic disease, treatment consists of hormonal therapy and possibly chemotherapy. The lifetime risk of being diagnosed with prostate cancer for men in the U.S. is approximately 16%, while the risk of dying of prostate cancer is 3% (Howlader, 2017). African American men have the highest prostate cancer risk in the U.S.; the incidence of prostate cancer is about 60% higher and the mortality rate is more than 2 to 3 times greater than that of white men (Odedina, 2009). Autopsy results have suggested that about 30% of men age 55 and 60% of men age 80 who die of other causes have incidental prostate cancer, indicating that many cases of cancer are unlikely to pose a threat during a man’s life expectancy (Bell, 2015).
Grading
The most widely used grading scheme for prostate cancer is the Gleason system (Gleason, 1966). It is an architectural grading system ranging from 1 (well-differentiated) to 5 (undifferentiated); the score is the sum of the primary and secondary patterns. A Gleason score of 6 or less is low-grade prostate cancer that usually grows slowly; 7 is an intermediate grade; 8 to 10 is high-grade cancer that grows more quickly. A revised prostate cancer grading system has been adopted by the National Cancer Institute and the World Health Organization (NCI, 2021). A cross-walk of these grading systems is shown below.
Prostate Cancer Grading Systems
Regulatory Status
Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). Laboratories that offer laboratory-developed tests must be licensed under the CLIA for high-complexity testing. The following laboratories are certified under the CLIA : BioReference Laboratories and GenPath Diagnostics (subsidiaries of OPKO Health; 4Kscore®), ARUP Laboratories, Mayo Medical Laboratories, LabCorp, BioVantra, others (PCA3 assay), Clinical Research Laboratory (Prostate Core Mitomic Test™), MDx Health (SelectMDx, ConfirMDx), Innovative Diagnostics (phi™), and ExoDx® Prostate (Exosome Diagnostics). To date, the U.S. Food and Drug Administration (FDA) has chosen not to require any regulatory review of these tests.
In February 2012, the Progensa® PCA3 Assay (Gen-Probe; now Hologic) was approved by the FDA through the premarket approval process. The Progensa PCA3 Assay has been approved by the FDA to aid in the decision for repeat biopsy in men 50 years or older who have had 1 or more negative prostate biopsies and for whom a repeat biopsy would be recommended based on the current standard of care. The Progensa PCA3 Assay should not be used for men with atypical small acinar proliferation on their most recent biopsy. FDA product code: OYM.
In June 2012, proPSA, a blood test used to calculate the Prostate Health Index (phi; Beckman Coulter) was approved by the FDA through the premarket approval process. The phi test is indicated as an aid to distinguish prostate cancer from a benign prostatic condition in men ages 50 and older with prostate-specific antigen levels of 4 to 10 ng/mL and with digital rectal exam findings that are not suspicious. According to the manufacturer, the test reduces the number of prostate biopsies. FDA product code: OYA.
Coding
Effective January 1, 2021, there is a specific CPT Proprietary Laboratory Analyses (PLA) code for PanGIA Prostate testing:
0228U Oncology (prostate), multianalyte molecular profile by photometric detection of macromolecules adsorbed on nanosponge array slides with machine learning, utilizing first morning voided urine, algorithm reported as likelihood of prostate cancer
Effective October 1, 2017, there is a specific CPT Proprietary Laboratory Analyses (PLA) code for the Apifiny test:
0021U Oncology (prostate), detection of 8 autoantibodies (ARF 6, NKX3-1, 5’- UTR-BMI1, CEP 164, 3’-UTR- Ropporin, Desmocollin, AURKAIP- 1, CSNK2A2), multiplexed immunoassay and flow cytometry serum, algorithm reported as risk score
Effective May 1, 2017, there is a specific CPT Proprietary Laboratory Analyses (PLA) code for ExosomeDx® Prostate testing:
0005U Oncology (prostate) gene expression profile by real-time RT-PCR of 3 genes (ERG, PCA3, and SPDEF), urine, algorithm reported as risk score
Effective January 1, 2015, there is a specific CPT code for PCA3 testing:
81313 PCA3/KLK3 (prostate specific antigen 3 [non-protein coding]/kallikrein-related peptidase 3 [prostate specific antigen]) ratio (eg, prostate cancer)
Prior to 2015 for PCA3 testing and currently for the other types of testing mentioned above, including the ConfirmMDx test, there are no specific CPT codes. The unlisted molecular pathology code 81479 would be used. If the test includes multiple assays, utilizes an algorithmic analysis and is reported as a numeric score or a probability, the unlisted multianalyte assay with algorithmic analysis (MAAA) code 81599 would be reported.
Effective July 1, 2015, there is a specific CPT code for 4Kscore™ Test:
0010M Oncology (high-grade prostate cancer), biochemical assay of four proteins (total PSA, free PSA, intact PSA and human kallikrein 2 [hK2]) plus patient age, digital rectal examination status, and no history of positive prostate biopsy, utilizing plasma, prognostic algorithm reported as a probability score.
Effective April 1, 2012, there is a specific HCPCS “S” code for the PCA3 test –
S3721 Prostate Cancer Antigen 3 (PCA3) testing.
|
|
|
|
|
Policy/ Coverage: |
Effective January 2021
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Screening tests are exclusions in most member benefit certificates of coverage except for coverage based on the Patient Protection and Affordable Care Act (PPACA) screening recommendations for non-grandfathered plans and those contracts with wellness benefits (which like PPACA, covers specific screening procedures).
The following genetic and protein biomarkers for the diagnosis of prostate cancer do not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes. This includes, but is not limited to the following:
Single nucleotide variant testing for cancer risk assessment of prostate cancer does not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, single nucleotide variant testing for cancer risk assessment of prostate cancer is considered investigational. Investigational services are exclusions in most member benefit certificates of coverage.
Effective Prior to January 2021
Screening tests are exclusions in most member benefit certificates of coverage except for coverage based on the Patient Protection and Affordable Care Act (PPACA) screening recommendations for non-grandfathered plans and those contracts with wellness benefits (which like PPACA, covers specific screening procedures).
The following genetic and protein biomarkers for the diagnosis of prostate cancer do not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes. This includes, but is not limited to the following:
Single nucleotide polymorphisms (SNPs) testing for cancer risk assessment of prostate cancer do not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, single nucleotide polymorphisms (SNPs) testing for cancer risk assessment of prostate cancer is considered investigational. Investigational services are exclusions in most member benefit certificates of coverage.
Effective Prior to December 2018
Screening tests are exclusions in most member benefit certificates of coverage except for coverage based on the Patient Protection and Affordable Care Act (PPACA) screening recommendations for non-grandfathered plans and those contracts with wellness benefits (which like PPACA, covers specific screening procedures).
The following genetic and protein biomarkers for the diagnosis of prostate cancer do not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes. This includes, but is not limited to the following:
Single nucleotide polymorphisms (SNPs) testing for cancer risk assessment of prostate cancer do not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
For members with contracts without primary coverage criteria, single nucleotide polymorphisms (SNPs) testing for cancer risk assessment of prostate cancer is considered investigational. Investigational services are exclusions in most member benefit certificates of coverage.
Effective May 2011 – July 2016
Screening tests are exclusions in most member benefit certificates of coverage except for coverage based on the Patient Protection and Affordable Care Act (PPACA) screening recommendations for non-grandfathered plans and those contracts with wellness benefits (which like PPACA, covers specific screening procedures).
Gene-based tests for detection and management of prostate cancer do not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
This includes, but is not limited to the following:
For contracts without primary coverage criteria, gene-based tests for detection and management of prostate cancer are considered investigational. Investigational services are exclusions in most member benefit certificates of coverage.
This includes, but is not limited to the following:
Effective prior to May 2011
Gene-based tests for screening are a contract exclusion.
Gene-based tests for detection and management of prostate cancer do not meet benefit certificate primary coverage criteria that there be scientific evidence of effectiveness.
For contracts without primary coverage criteria, gene-based tests for detection and management of prostate cancer are considered investigational. Investigational services are an exclusion in the member certificate of coverage.
|
|
|
|
| Rationale: |
Published literature focuses on the technical feasibility of identifying an upregulated PCA3 gene and its possible function. There have been no published peer-reviewed studies in which PCA3 has been used as part of a screening program, diagnosis or in the management of the patient with suspected or known prostate cancer. Hessels and colleagues reported on the results of the PCA3 test in 108 men undergoing prostate biopsy prompted by a PSA level of greater than 3 ng/ml. Of these 108 men, 24 were found to have prostate cancer based on biopsy. Of these 16 were shown to be positive for PCA3. The sensitivity was 67% and the negative predictive value was 90%. The authors hypothesize that due to its high negative predictive value, the PCA3 test could eliminate the need for unnecessary biopsies in patients with marginally elevated levels of PSA. The manufacturer has reported on the results of a clinical study of 443 who underwent both a digital rectal exam, measurement of prostate specific antigen (PSA) and measurement of PCA3. According to the information on the manufacturer's website, the PCA3 test had a positive and negative predictive value of 75% and 84% respectively.
2005 Update
A literature search of the MEDLINE database was performed for the period of 2004 through June 2005. Saad and colleagues reported on a multicenter study of 517 men, in which the positive predictive value of the PCA3 test and PSA greater than 4 ng/dL was 75% and 38%, respectively, while the negative predictive value of the 2 tests was similar. Tinzl and colleagues reported on a case series of 201 men, of whom 158 had an evaluable urine specimen. The positive and negative predictive values were 67% and 87% for the PCA3 test, as compared to 40% and 83% for PSA level greater than 2.5 ng/dL. However, in this study, 39% of patients were found to have prostate cancer, suggesting that this population is not representative of a general screening population. No studies were identified in which the PCA3 test was used to direct patient management, and thus the policy statement is unchanged.
2006-2007 Update
A literature search was performed for the period of June 2005 through December 2006. Studies involving small numbers of patients continue to be published, demonstrating encouraging preliminary results (improved predictive values) for potential use of PCA3 test, alone or in combination with other prostate-related transcripts, in screening for prostate cancer. However, no studies were found in which the PCA3 test was used to direct patient management; the policy statement is unchanged.
2009 Update
A search of the MEDLINE database did not reveal any published studies that would prompt a change in the coverage policy. A 2009 editorial by Gelmann and Henshell discussed the recently published Scandinavian randomized trial of radical prostatectomy and the European randomized trial of PSA screenings. “The 2 trials show that most cases of screening-detected prostate cancer diagnosed today are overdiagnosed. These observations suggest that screening and aggressive treatment has little value for most men.” According to the authors, “The physicians and their patients need reliable markers that can identify cancer that requires immediate and aggressive therapy. Until we have sufficiently discriminating markers to inform treatment decisions, the problem of whom to treat will continue to grow exponentially as the number of cases of screening-detected, low-risk cancer increases.”(Gelmann, 2009). There is still a lack of scientific evidence that gene-based testing improves health outcomes. The policy remains unchanged.
2011 Update
This policy was updated with a search of the MEDLINE database through March 2011. A summary of the identified literature is included below.
Single-Nucleotide Polymorphisms (SNPS) for Risk Assessment
In a review by Ioannidis et al.(loannidis, 2010) , 27 gene variants at a wide variety of chromosomal locations were identified that incurred additional risk for prostate cancer although in all cases the incremental risk observed was modest (odds ratio of 1.36 or less). More recently Lindstrom et al. (Lindstrom, 2011), in a study of 10,501 cases of prostate cancer and 10,831 controls, identified 36 SNPs showing association with prostate cancer risk including two (rs2735893 and rs266849) showing differential association with Gleason grade. Per allele odds ratios ranged from 1.07 to 1.44.
Because the SNPs individually provide relatively modest incremental information on both the occurrence of cancer and its behavior, investigators have begun to explore use of algorithms incorporating information from multiples SNPs to increase the clinical value of testing. Gudmundsson et al. using 22 prostate cancer risk variants, estimated that carriers in the top 1.3% of the risk distribution have a 2.5 times increase in risk of developing disease compared to the general population (Gudmundsson, 2008). Zheng et al. identified five chromosomal regions in a Swedish population (2,893 patients with prostate cancer and 1,781 controls) and in conjunction with family history developed an algorithm which appeared to account for 46% of cases of prostate cancer (Zheng, 2008). Salinas et al. also evaluated use of 5 SNPs plus family history to predict risk of prostate cancer (Salinas, 2009). While they identified a significant association in risk, they were unable to demonstrate improved models for assessing who is at risk of getting or dying from prostate cancer, once known risk or prognostic factors are taken into account. Finally, Helfand et al. developed an expanded algorithm using 9 genomic regions which identified patients with a 6-fold increase risk for prostate cancer (Helfand, 2010). Two of the regions studied (2p15 and 11q13) were more likely to be associated with tumors with aggressive features.
To date there has been no report of clinical validity for testing using standard terms for diagnostic use (e.g., sensitivity, specificity, positive or negative predictive values) and no evidence that testing has any impact on health outcomes.
PCA3 for Disease Diagnosis
Ankerst et al. reported that incorporating the PCA3 Score into the Prostate Cancer Prevention Trial risk calculator improved the diagnostic accuracy of the calculator (from AUC 0.653 to AUC 0.696) (Ankerst, 2008). Chun et al, using a multivariate nomogram, demonstrated a 5% gain in predictive accuracy when PCA3 was incorporated with other predictive variables such as age, digital rectal examination (DRE) results, PSA levels, prostate volume, and past biopsy history (Chun, 2009). In a recent study of 218 patients with PSA values of 10 ng/ml or less, Perdona et al. performed a head-to-head comparison of these two risk assessment tools and suggested both might be of value in clinical decision making (Perdona, 2011).
Several studies have recently been focused on evaluating the PCA3 Score as a tool for distinguishing between patients with indolent cancers who may only need active surveillance and patients with aggressive cancers who warrant aggressive therapy. Haese et al., Nakanishi et al., and Whitman et al. have all demonstrated an association between PCA3 scores and evidence of tumor aggressiveness (Haese, 2008) (Nakanishi, 2008) (Whitman, 2008). However, Bostwick et al. and Vans Gils et al. failed to confirm these findings (Bostwick, 2006) (van Gils, 2008). Auprich et al. recently reported that PCA3 scores appeared to enhance identification of indolent disease but not pathologically advanced or aggressive cancer (Auprich, 2011).
Clinical utility studies of using assay results for decision-making for initial biopsy, repeat biopsy, or treatment have not been reported.
TMPRSS Fusion Genes for Diagnosis and Prognosis.
TMPRSS2 is an androgen-regulated transmembrane serine protease that is preferentially expressed in normal prostate tissue. In prostate cancer, it may be fused to an ETS family transcription factor (ERG, ETV1, ETV4 or ETV5), which modulates transcription of target genes involved in cell growth, transformation, and apoptosis. The result of gene fusion with an ETS transcription gene is that the androgen-responsive promoter of TMPRSS2 positively dysregulates expression of the ETS gene, suggesting a mechanism for neoplastic transformation. Fusion genes may be detected in tissue, serum, or urine.
TMPRSS2-ERG gene rearrangements have been reported in 50% or more of primary prostate cancer samples (Mackinnon, 2009). While ERG appears to be the most common ETS family transcription factor involved in the development of fusion genes, not all are associated with TMPRSS2. About 6% of observed rearrangements are seen with SLC45A3 and about 5% appear to involve other types or rearrangement (Esgueva, 2010).
Most recently, increased attention has been directed at using post DRE urine samples to look for fusion genes as a marker of prostate cancer. Laxman et al. developed an assay to measure ERG and TMPRSS2:ERG transcripts in urine samples following prostatic massage from 19 patients with prostate cancer (Laxman, 2006). They observed a strong concordance between the presence of these transcripts and prostate cancer. In a subsequent study of 234 patients presenting for biopsy or radical prostatectomy (138 with cancer; 86 with benign disease), these authors (Laxman, 2008) confirmed the association between cancer and TMPRSS2:ERG but failed to demonstrate a significant association between cancer and ERG transcripts. An algorithm was created using seven candidate biomarkers including SPINK1, PCA3, GOLPH2 and TMPRSS2:ERG. The area under the curve or this multiplex model was 0.785; sensitivity 66%, specificity 76%. Because the study was performed on a population enriched for cancer, external validation would be critical in properly defining and understanding test performance.
Rice et al. developed an assay directed at evaluation of ERG RNA in urine normalized for PSA RNA (Rice, 2010). In a study of 237 men scheduled for prostate biopsy, this assay was found to identify cancer with an area under the curve of 0.592, a sensitivity of 31% and specificity of 84%. Higher urine ERG values were associated significantly with a positive biopsy although these did not correlate with clinical stage or biopsy Gleason scores. Performance of the test was noted to be particularly good in Caucasian patients with a PSA value of 4 ng/mL or less. Adding ERG to results of PSA and other clinical parameters in a multivariate logistic regression model did not significantly improve performance in predicting biopsy. The authors conclude “further studies examining the long-term prognostic significance of these markers will show their full potential in augmenting the appropriate diagnosis and treatment of prostate cancer.”
Candidate Gene Panels for Prostate Cancer Diagnosis
Because no single gene markers have been found that are both highly sensitive and highly specific for diagnosing prostate cancer, particularly in men already known to have elevated PSA levels, some investigators are combining several markers into a single diagnostic panel. While promising in concept, only single studies of various panels have been published, and none apparently is offered as a clinical service.
Clarient, Inc. launched a “patent protected combination of four genes that have been shown to accurately identify the presence of Grade 3 or higher” prostate cancer in prostate tissue in 2009. This test is reportedly based on a study that has been submitted for publication but has not yet been accepted for publication or available for evaluation. It appears that at this time Clarient, Inc. is not offering this assay. It does not appear in the menu on the company’s web site and the consumer representative queried for its availability did not return calls.
Gene Hypermethylation for Diagnosis and Prognosis.
Epigenetic changes, chromatin protein modifications that do not involve changes to the underlying DNA sequence but which can result in changes in gene expression, have been identified in specific genes. There is extensive literature reporting significant associations of epigenetic DNA modifications with prostate cancer. Studies are primarily small, retrospective pilot evaluations of hypermethylation status of various candidate genes for discriminating prostate cancer from benign conditions (diagnosis) or for predicting disease recurrence and association with clinicopathologic predictors of aggressive disease (prognosis).
GSTP1 is the most widely studied methylation marker for prostate cancer, usually as a diagnostic application. Many studies have reported on the association of GSTP1 with prostate cancer. Two recent studies of GSTP1 hypermethylation using tissue samples reported significant results for identifying cancer with a sensitivity of 92%, a percent specificity of 85%, and an AUC of about 0.9. (Eilers, 2007) (Ellinger, 2009). However, 2 other studies did not find significant associations with disease (Henrique, 2007) (Woodson, 2006). In spite of these contradictory results, several investigators have evaluated detection of hypermethylation products in biological fluids for early detection of prostate cancer. Suh et al. studied the ejaculates of patients with prostate cancer and observed methylated GSTP1 in 4 of 9 patients (Suh, 2000). Goessl et al. confirmed the presence of the methylated biomarker in ejaculates (50%) and extended its evaluation to demonstrate an association with cancer in serum (82% of cancer patients), urine (36%), and urine following prostatic massage (73%) (Goessl, 2001).
Subsequently, Ellinger et al. studied hypermethylation of GSTP1 with additional genes (T1G1, Reprimo, and PTGS2) in 226 patients (168 with prostate cancer) in an effort to provide a more consistent yield of positives (Ellinger, 2008). They observed that the detection of aberrant methylation in serum DNA has high specificity (92%) but variable and more modest sensitivity (42 to 47%) for cancer. More recently Sunami et al. assayed blood from 40 healthy individuals and 83 patients with prostate cancer using a 3-gene cohort (GSTP1, RASSF1, and RARβ2) and demonstrated a sensitivity of 28% for cancer patients (Sunami, 2009).
Ahmed has recently published a comprehensive review of promoter methylation in prostate cancer outlining in detail a wide range of variable findings (Ahmed, 2010). More rigorous studies are needed to establish both the clinical validity and clinical utility of this assay in well-defined prospective or banked samples in order to determine if and how to introduce this interesting diagnostic technology into clinical decision making.
2013 Update
In 2013, the Agency for Healthcare Research an Quality (AHRQ) published a Comparative Effectiveness Review on PCA3 testing for the diagnosis and management of prostate cancer (Bradley, 2013). The published literature on the use of PCA3 compared to standard tests for the diagnosis and management of patients with elevated PSA and/or abnormal digital rectal examination who are candidates for initial or repeat biopsy was found to be limited and of poor quality. The authors concluded, “For diagnostic accuracy, there was a low strength of evidence that PCA3 had better diagnostic accuracy for positive biopsy results than tPSA elevations, but insufficient evidence that this led to improved intermediate or long-term health outcomes. For all other settings, comparators, and outcomes, there was insufficient evidence” (Bradley, 2013). These findings do not prompt a change in the coverage statement.
2014 Update
Single-Nucleotide Polymorphisms (SNPs) for Risk Assessment and Prognosis
In 2013, 2 groups from Asia published studies of prostate cancer-associated SNP panels. Ren et al reported AUCs of 0.62 with a panel of 29 SNPs and 0.62 with a subset of 13 SNPs (Ren, 2013). Tsuchiya et al identified 14 SNPs in 6 genes (XRCC4, PMS1, GATA3, IL13, CASP8, and IGF1) that were statistically associated with cancer-specific survival (Tsuchiya, 2013). Using a subset of 6 SNPs, 3 subgroups of men with prostate cancer were defined by the number of SNP’s present (0 to 1, 2 to 3, or 4 to 6). Median cancer-specific survival in these subgroups was 13.3, 7.0, and 3.8 years, respectively (log-rank test, p<0.001).
To date, there has been no report of clinical validity for testing using standard terms for diagnostic use (eg, sensitivity, specificity, positive or negative predictive values) and no evidence that testing has any impact on health outcomes.
PCA3 for Prostate Cancer Diagnosis
In 2013, the Agency for Healthcare Quality and Research (AHRQ) published a comparative effectiveness review entitled, “PCA3 Testing for the Diagnosis and Management of Prostate Cancer” (Bradley, 2013). Literature was searched and updated through May 15, 2012. Forty-three studies were included; all were rated poor quality. In their conclusion, the authors stated, “For diagnostic accuracy, there was a low strength of evidence that PCA3 had better diagnostic accuracy for positive biopsy results than [serum] total PSA elevations, but insufficient evidence that this led to improved intermediate or long-term health outcomes.” This finding appeared to apply to both initial and repeat biopsies. Evidence was insufficient to assess the use of PCA3 in treatment decision-making for men with positive biopsy.
Several studies published in 2013 and 2014 reported positive associations between PCA3 levels and prostate cancer diagnosis (Leyten, 2013; Rondon, 2013; Chevli, 2013; Capoluongo, 2013; Hagglof, 2014; Lin, 2013). Predictive value was increased when PCA3 testing was combined with PSA level and other clinical information (Gittelman, 2013; Hansen, 2013). Other groups reported moderate diagnostic accuracy of PCA3 testing. Among men with PSA level greater than 3 ng/mL, AUC of PCA3 was 0.74 (Rubio-Briones, 2013). Conversely, in men with PCA3 scores of 100 or greater, positive predictive value was 39% (Schroder, 2014). In a Japanese study of 647 men, sensitivity and specificity were 67% and 72%, respectively; AUC was 0.742 (Ochiai, 2013). Two studies compared PCA3 to multiparametric MRI; MRI was more accurate than PCA3 (Propiglia, 2014), but the combination was better than either alone (Busetto, 2013).
Clinical utility studies using assay results for decision-making for initial biopsy, repeat biopsy, or treatment have not been reported. One group reported potential reductions in unnecessary biopsies of 48-52% with attendant increases in missed prostate cancers of 6-15% using either a PCA3-based nomogram (Ruffion, 2013) or PCA3 level corrected for prostate volume (PCA3 density) (Ruffion, 2014). Although both studies were prospective, neither assessed utility of the test for clinical decision-making because all patients underwent biopsy. Also, recurrence or survival outcomes were not evaluated.
TMPRSS Fusion Genes for Diagnosis and Prognosis
In a prospective, multicenter study, Leyten et al (2014) investigated the predictive value of PCA3 and TMPRSS2 as individual biomarkers and as part of a panel in a prospective, multicenter study of 443 men (Leyten, 2014). TMPRSS2 was found to be highly specific (93%) for predicting clinically significant prostate cancer on biopsy. Because of this high specificity, the authors suggested that re-biopsy or magnetic resonance imaging (MRI) be performed in TMPRSS2:ERG-positive patients who do not have prostate cancer detected on initial biopsy. The authors stated that if PCA3 in combination with TMPRSS2 data had been used to select men for prostate biopsy, 35% of biopsies could have been avoided.
In 2013, Yao et al published a systematic review with meta-analysis of TMPRSS2:ERG for the detection of prostate cancer (Yao, 2013). Literature was searched through July 30, 2013, and 32 articles were included. Pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were 47% (95% CI, 46 to 49), 93% (95% CI, 92 to 94), 8.9 (95% CI, 5.7 to 14.1), and 0.49 (95% CI, 0.43 to 0.55), respectively. Statistical heterogeneity was high (I2>85%). It was unclear whether studies in screening populations were pooled with enriched patient samples, eg, elevated PSA and/or biopsy-negative. There also was variability in the type of tissue samples analyzed (urine, prostatic secretions, biopsy or surgical specimens); the type of TMPRSS2:ERG assays used (fluorescence in situ hybridization [FISH], immunohistochemistry [IHC], real-time reverse transcriptase polymerase chain reaction [RT-PCR], and transcription-mediated amplification); and in TMPRSS2:ERG threshold cutoff values.
Several studies published in 2013 and 2014 reported positive associations between TMPRSS2 fusion gene levels and prostate cancer diagnosis (Hagglof, 2014; Lin, 2013; Chan, 2013; Vaananen, 2014). One study reported lack of association between TMPRSS2-ERG status and biochemical relapse-free rate in 244 men treated with image-guided radiotherapy (IGRT) for prostate cancer (Chan, 2013). The authors observed that “TMPRSS2-ERG is therefore unlikely to be a predictive factor for IGRT response.”
Whelan et al (2014) compared 2 multivariate models to assess up-staging in 216 patients meeting National Comprehensive Cancer Network (NCCN) criteria for active surveillance (Whelan, 2014). One model included TMPRSS2:ERG plus serum PSA; the other model included serum PSA, total RNA in expressed prostatic secretion (EPS, collected by milking the urethra after prostatic massage), and total EPS volume. AUCs were similar (0.80 [95% CI, 0.75 to 0.85] and 0.79 [95% CI, 0.73 to 0.84], respectively). However, the second model was more accurate for detecting patients who were up-staged, or up-staged and up-graded, by NCCN criteria. Specifically, the second model decreased the risk of up-staging in patients with a negative test approximately 8-fold (from 7% to 1%); decreased the risk of up-staging plus up-grading approximately 5-fold (from 5% to 1%); and doubled the prevalence of up-staging in the positive test group. In comparison, the TMPRSS2:ERG model decreased up-staging 2.4-fold (from 7% to 3%) and decreased upstaging and upgrading approximately 3-fold (from 5% to 2%).
TMPRSS2:ERG in Combination With PCA3
In 2014, this same group evaluated 45 men using a multivariable algorithm that included serum PSA plus urine TMPSS2:ERG and PCA3 from a post-DRE sample (Salami, 2013). Samples were collected before prostate biopsy at 2 centers. For cancer prediction, sensitivity and specificity were 80% and 90%, respectively. AUC was 0.88.
Robert et al (2013) retrospectively examined tissue levels of TMPRSS2:ERG and PCA3 in 48 men with benign prostatic hypertrophy, 32 men with normal prostate tissue sampled next to prostate cancer, and 48 men with prostate cancer (Robert, 2013). Sensitivity, specificity, and positive and negative predictive values for the tests in combination were 94%, 98%, 96%, and 96%, respectively.
In summary concomitant detection of TMPRSS2:ERG and PCA3 may more accurately identify men with prostate cancer. However, current evidence is insufficient evidence to support its use. Estimated accuracy varies across available studies, and comparative studies, demonstrating improvements in health outcomes with the test compared with no testing, are lacking.
Candidate Gene Panels for Prostate Cancer Diagnosis and Prognosis
Ma et al (2014) examined various algorithms for cancer diagnosis and prognosis using urine and plasma levels of multiple genes, including PCA3, PSA, TMPRSS2, and ERG (Ma, 2014). One algorithm distinguished prostate cancer from benign prostatic hypertrophy with AUC 0.78. Another algorithm distinguished men with Gleason score 7 or higher from men with Gleason score less than 7 (AUC 0.88). Combination of these 2 algorithms into a scoring system predicted the presence of Gleason score 7 or higher in 75% of men. Qu et al (2013) reported preliminary results of a 3-gene panel (androgen receptor [AR], PTEN, and TMPRSS2:ERG) analyzed by FISH (Qu, 2013). Thirty-one percent of 110 archived primary tumor samples and 97 metastatic tumor samples from a separate cohort of patients were analyzable. Chromosomal abnormalities were detected in 53% of primary prostate cancers and 87% of metastatic tumors (p<0.001).
Gene Hypermethylation for Diagnosis and Prognosis
In 2013, several studies reported associations between DNA hypermethylation at various gene loci (RASSF1A, APC, GSTP1, PTGS2, RAR-beta, TIG1, AOX1, C1orf114, GAS6, HAPLN3, KLF8, and MOB3B) and prostate cancer (Ge, 2013; Moritz, 2013; Haldrup, 2013). In contrast, Kachakova et al (2013) found that HIST1H4K hypermethylation was more likely due to aging than to prostate carcinogenesis (Kahakova, 2013).
Ongoing Clinical Trials
A clinical study (NCT00977457) co-sponsored by the City of Hope Medical Center (Duarte, California) and the National Cancer Institute aims to evaluate the ability of urinary biomarkers collected after prostatic massage to predict the likelihood of biochemical recurrence after surgery. Estimated enrollment is 1200 men, and estimated completion date is February 2016.
A clinical study in Denmark (NCT01739062) will assess whether SNP results impact PSA testing in low risk men. Estimated enrollment is 1298 men, and estimated completion date is June 2016.
Practice Guidelines and Position Statements
American Urological Association
In 2013, the AUA published guidelines for the early detection of prostate cancer (AUA, 2013). Based on systematic review of the literature to 2013, the guideline Panel recognized that novel urinary markers, such as PCA3 and TMPRSS2:ERG, may be “used as adjuncts for informing decisions about the need for a prostate biopsy – or repeat biopsy – after PSA screening,” but emphasized the lack of evidence “that these tests will increase the ratio of benefit to harm.”
Evaluation of Genomic Applications in Practice and Prevention (EGAPP)
In 2013, the EGAPP Working Group published the following recommendations for PCA3 testing in prostate cancer, based on the AHRQ comparative effectiveness review (Bradley, 2013) summarized above: (EGAPP, 2013).
National Comprehensive Cancer Network (NCCN)
Current NCCN guidelines recommend PCA3 testing in men with a suspicious digital rectal exam, PSA greater than 3.0 ng/mL, or excess risk based on multiple factors (eg, accelerated PSA velocity or elevated risk using a risk calculator tool) who have not undergone a transrectal ultrasound-guided biopsy (NCCN, 2014). PCA3 is recommended as 1 of several tests to consider for following patients who have had a negative biopsy. Guideline authors note:
“Biomarkers that improve the specificity of detection are not recommended as first-line screening tests, but are reserved mostly for selecting for repeat biopsy, those who have undergone at least one negative biopsy…PCA3 score greater than 35 is strongly suspicious for prostate cancer.”
2016 Update
ConfirmMDx® (MDxHealth)
ConfirmMDx is intended to distinguish true from false negative prostate biopsies to avoid the need for repeat biopsy in cases of a true negative and to identify men who may need a repeat biopsy. The test measures methylation of the genes GSTP1, APC, and RASSF1. The company’s website states that the test has a negative predictive value of 90% in confirming a negative biopsy.
Published literature on the validation and clinical use of ConfirmMDx is described next.
In 2014, Wojno et al reported a field observation study in which practicing urologists at 5 centers had used the ConfirmMDx test to evaluate at least 40 men with previous cancer-negative biopsies who were considered to be at risk for prostate cancer (Wojno, 2014). Centers reported whether patients who had a negative test assay result had undergone a repeat biopsy at the time of the analysis. Median patient follow-up time after the assay results were received was 9 months. A total of 138 patients were included in the analysis. The current median PSA level was 4.7 ng/mL. Repeat biopsies had been performed in 6 of the 138 men (4.3%) with a negative ConfirmMDx test, in which no cancer was identified.
Two blinded multicenter validation studies of the ConfirmMDx test have been performed (Stewart, 2013; Partin, 2014). One evaluated archived, cancer-negative prostate biopsy core tissue samples from 350 men from a total of 5 U.S. urological centers. All of the patients underwent repeat biopsy within 24 months. The ConfirmMDx test, performed on the first biopsy, resulted in a negative predictive value of 88% (95% CI, 85 to 91). Multivariate analysis of potential predictors of cancer on repeat biopsy, corrected for age, PSA, DRE, first biopsy histopathology characteristics and race, showed that the ConfirmMDx test was the most significant independent predictor of patient outcome (odds ratio [OR], 2.69; 95% CI, 1.60 to 4.51).
The other validation study tested archived cancer-negative prostate biopsy needle core tissue samples from 498 men from the United Kingdom and Belgium. Patients underwent repeat biopsy within 30 months. The ConfirmMDx test, performed on the first biopsy, resulted in a negative predictive value of 90% (95% CI, 87 to 93). Multivariate analysis of potential predictors of cancer on repeat biopsy, corrected for patient age, PSA, DRE, and first biopsy histopathology characteristics, showed that the ConfirmMDx test was the most significant independent predictor of patient outcome (OR=3.17; 95% CI, 1.81 to 5.53).
Prostate Core Mitomics Test™ (Mitomics [Formerly Genesis Genomics])
The Prostate Core Mitomics Test (PCMT) is a proprietary test that is intended to determine whether a patient has prostate cancer, despite a negative prostate biopsy, by analyzing deletions in mitochondrial DNA by polymerase chain reaction (PCR) to detect “tumor field effect.” The test is performed on the initial negative prostate biopsy tissue. According to the company website, a negative PCMT result confirms the results of the negative biopsy (ie, the patient doesn’t have prostate cancer) and that the patient can avoid a second biopsy, but that a positive PCMT means that the patient is at high risk of undiagnosed prostate cancer. The company website states that the sensitivity of the test is 85% and has a negative predictive value of 92%.
Published literature from Genesis Genomics on the use of mitochondrial DNA mutations in prostate is described next.
A 2006 study retrospectively analyzed mitochondrial DNA mutations from 3 tissue types from 24 prostatectomy specimens: prostate cancer, adjacent benign tissue, and benign tissue distant to the tumor (defined as tissue from a nondiseased lobe or at least 10-cell diameters from the tumor if in the same lobe) (Parr, 2006). Prostate needle biopsy tissue (from 12 individuals referred for biopsy) that were histologically benign were used as controls. Results from the prostatectomy tissue analysis showed that 16 of 24 (66.7%) had mutations in all three tissue types, 22 of 24 (91.7%) had mutations in malignant samples, 19 of 24 (79.2%) in adjacent benign samples, and 22 of 24 in distant benign glands. Overall, 273 somatic mutations were observed in this sample set. In the control group, 7 (58.3%) patients were found to have between 1 and 5 alterations, mainly in noncoding regions. The authors concluded that the mutations found in the malignant group versus the control group were significantly different and that mitochondrial DNA mutations are an indicator of malignant transformation in prostate tissue.
In 2008, Maki et al reported the discovery and characterization of a 3.4-kb mitochondrial genome deletion and its association with prostate cancer (Maki, 2008). A pilot study analyzed 38 benign biopsy specimens from 22 patients, 41 malignant biopsy specimens from 24 patients, and 29 proximal to malignant (PTM) biopsy specimens from 22 patients. All of the patients with malignant biopsies had a subsequent prostatectomy, and the diagnosis of cancer was confirmed. The PTM biopsy samples were negative for cancer and were from the cohort that underwent prostatectomy. A confirmation study used 98 benign biopsy specimens from 22 patients, 75 malignant biopsy specimens from 65 patients, and 123 PTM biopsy specimens from 96 patients. In the confirmation study, patients were required to have at least 2 successive negative biopsies; the first negative biopsy was used for analyses. For both the pilot and confirmation studies, samples for analysis were selected based on review of pathology reports. The levels of the mutation were measured by quantitative PCR and using PCR cycle threshold data were used to calculate a score for each biopsy sample. In the pilot study, the scores were statistically significant between benign and malignant (p<0.000) and benign and proximal (p<0.003) samples. The PTM samples closely resembled the malignant sample, with no statistical significant resolution between the scores (p<0.833), to which the authors attributed as a field cancerization phenomenon. Results from the larger confirmation study were similar. Compared with histopathologic examination of the benign and malignant samples, the sensitivity and specificity were 80% and 71%, respectively, and the area under a ROC curve was 0.83 for the deletion. A blinded, external validation study showed a sensitivity and specificity of 83% and 79% and the area under the ROC curve 0.87.
In 2010, Robinson et al. assessed the clinical value of the 3.4-kb deletion described in the Maki study in predicting re-biopsy outcomes (Robinson, 2010). Levels of the deletion were measured by quantitative PCR in prostate biopsies negative for cancer from 101 patients who underwent repeat biopsy within 1 year and had known outcomes. Of the 101 first biopsies, the diagnosis was normal in 8, atypical and/or had prostatic intraepithelial neoplasia in 50, and hyperplasia or inflammation in 43. Using an empirically established cycle threshold cutoff, the lowest cycle threshold as diagnostic of prostate cancer, and the histopathologic diagnosis on second biopsy, the clinical performance of the deletion was calculated. The final data were based on 94 patients, who on second biopsy had 20 malignant and 74 benign diagnoses. The cycle cutoff gave a sensitivity and specificity of 84% and 54%, respectively, with the area under a ROC curve of 0.75. Negative predictive value was 91%.
Prostarix (Metabolon/Bostwick Laboratories)
Prostarix™ is a post-DRE urine test that is based on a panel of biomarkers and is used in the early detection of prostate cancer. The results are intended to aid in clinical decision making as to whether to biopsy or repeat biopsy the prostate, particularly in patients who have a suspicious DRE and modestly elevated PSA (2.5-10 ng/mL). The test addresses metabolic abnormalities that have been associated with prostate cancer. Prostarix measures the concentration of several metabolites: sarcosine, alanine, glycine, and glutamate, and these quantitative measurements are combined in a logistic regression algorithm to generate a Prostarix Risk Score. If PSA level and TRUS-determined prostate volume are available, they can be used along with the metabolite measurements to generate the Prostarix-PLUS Risk Score. The
test claims to have increased sensitivity and specificity over standard assessment tools to predict the likelihood of a positive prostate biopsy.
Two studies, described next, correlated the level of sarcosine in urine of prostate biopsy-positive and - negative patients, and found increased levels of sarcosine in the urine of patients with prostate cancer; however, is not clear in which patient population a test measuring urine sarcosine would be used, or what level of sarcosine would warrant a prostate biopsy. In addition, other studies done by different authors have shown conflicting results from those performed by the authors from Metabolon.
In their initial study of the potential role of metabolomic profiles to delineate the role of sarcosine in prostate cancer progression, Sreekumar et al profiled 1126 metabolites across 262 prostate-derived clinical samples (42 tissue samples and 110 matched specimens of plasma and post-DRE urine from biopsy-positive cancer patients [n=59] and biopsy-negative control patients [n=51]) (Sreekumar, 2009). The authors reported that levels of sarcosine increased progressively in benign, localized prostate cancer, and metastatic disease.
Subsequently, the investigators used benign prostate tissue and localized prostate cancer obtained from a radical prostatectomy series from one university’s hospital (Khan, 2013). Urine specimens were collected from patients who were being screened for prostate cancer with PSA levels considered clinically significant (8.59±6.30). Urine was collected post-DRE but before prostate biopsy. Urine collected from patients undergoing prostatectomy was collected before surgery and used as a positive control. In total, 211 biopsy-positive and 134 biopsy-negative urine sediments were used. Using a logistic regression model, sarcosine levels were elevated in prostate cancer urine sediments compared with controls, with an area under the receiver operating curve of 0.71.
4Kscore Test (OPKO Lab)
The 4Kscore Test is a blood test that generates a risk score for the probability for finding high-grade prostate cancer (defined as a Gleason score ≥7) if a prostate biopsy were performed. The intended use of the test is to aid in the decision of whether or not to proceed with a prostate biopsy. The test algorithm combines the measurement of 4 prostate-specific kallikreins (total prostate-specific antigen [tPSA], free PSA [fPSA], intact PSA [iPSA], and human kallikrein 2 [hK2]), which are combined in an algorithm with patient age, digital rectal exam (DRE) (nodules or no nodules), and whether the patient has had a prior negative prostate biopsy. A kallikrein is a subgroup of enzymes that cleave peptide bonds in proteins. The iPSA and hK2 tests are immunoassays that employ distinct mouse monoclonal antibodies.
The test is not intended to be used in patients with a previous diagnosis of prostate cancer, a patient who has had a DRE in the previous 4 days, a patient who has received 5-alpha reductase inhibitor therapy in the previous 6 months, or a patient who has undergone any procedure or therapy to treat symptomatic benign prostatic hypertrophy in the previous 6 months.
The performance of the 4Kscore Test was validated in a total of 1012 patients who were enrolled from October 2013 to April 2014 in a blinded, prospective study at 26 urology centers in the United States (Parekh, 2014). Enrollment into the study was open to all men who were scheduled for a prostate biopsy, regardless of age, PSA level, DRE, or prior prostate biopsy. Each patient underwent a transrectal ultrasound (TRUS)‒ guided prostate biopsy of at least 10 cores. A blinded blood sample that was collected before biopsy was sent to OPKO Lab for the 4 kallikrein markers. The results of the kallikrein markers, prostate biopsy histopathology, patient age, DRE, and prior biopsy status were unblinded and analyzed.
The biopsy was negative in 54% of cases (n=542), showed low-grade (all Gleason grade 6) prostatic cancer in 24% (n=239) and high-grade cancer in 23% (n=231). The statistical analysis of the 4Kscore Test clinical data had an area under the curve (AUC) of the receiver operator curve (ROC) of 0.82 for the detection of high-grade prostate cancer; the AUC for all patients using tPSA, age, DRE and prior biopsy was 0.76.
The authors have also conducted multiple studies predicting the use of the test in patient cohorts from the European Randomized Study of Prostate Cancer.
2019 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2019. No new literature was identified that would prompt a change in the coverage statement.
2020 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2020. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Verbeek et al conducted a retrospective comparison of the discriminatory ability of the 4K score compared to the Rotterdam Prostate Cancer Risk Calculator (Verbeek, 2018). The cohort included 2,872 men with PSA > 3.0 from the European Randomized Study of Screening for Prostate Cancer Rotterdam. The 4K panel was measured in frozen serum samples. The AUCs were similar, with an AUC of 0.88 for the 4K score and 0.87 for the Rotterdam Prostate Cancer Risk Calculator (p=0.41). Addition of the 4K score to the Rotterdam Prostate Cancer Risk Calculator had a modest, though statistically significant improvement in discriminatory ability with an AUC of 0.89. A limitation of this study is that men were included who had PSA outside of the levels of interest, which would be between 3 and 10 ng/ml.
Loeb et al conducted a modeling study to compare established risk calculators with and without phi (Loeb, 2016). The population for this retrospective analysis included 728 men from the prospective multicenter clinical trial of phi (Catalona, 2011). The probability of aggressive prostate cancer was evaluated at each value of phi from 1 to 100. The addition of phi to the PCPT 2.0 risk calculator increased the AUC for the discrimination of aggressive prostate cancer from 0.575 to 0.696 (p<0.001), while the addition of phi to the ERSPC 4 plus DRE risk calculator increased the AUC from 0.650 to 0.711 (p=0.014).
The multi-institutional Canary Prostate Surveillance Study (PASS) was reported by Newcomb et al (Newcomb, 2019). The study included 782 men under active surveillance (2,069 urine samples) to examine the association of urinary PCA3 and TMPRSS2:ERG with biopsy-based reclassification. TMPRSS2:ERG was not associated with short-term reclassification at the first surveillance biopsy.
Development and validation studies on a revised risk model that included HOXC6 and DLX1 expression along with patient age, DRE, and PSA density in men undergoing initial biopsy was reported by Haese et al (Haese, 2019). The new analysis included data from the Dutch patients in the report by Van Neste et al along with additional cohorts from France and Germany (Van Neste, 2016). In the validation cohort of men with all PSA levels, the AUC was 0.82 with 89% sensitivity and 53% specificity. The PCPTRC AUC was 0.76. Since some clinicians will proceed to biopsy when there is a positive DRE, results were also calculated for patients who had PSA <10 ng/ml and a negative DRE. For this cohort (n=591), the AUC was 0.80 with sensitivity of 84% and specificity of 57%. Comparison with the PCPTRC in this subgroup was not reported.
Wysock et al compared the performance of 4Kscore and SelectMDx to inform decisions of whether to perform a prostate biopsy (Wysock, 2020). New referrals (n=128) with elevated PSA were advised to undergo both 4K score and SelectMDX; 114 men underwent both tests. There was poor concordance between the two tests, with discordant guidance in 45.6% of the population. Since biomarker results were used to determine which patients should undergo biopsy (ie the reference test was not obtained for all patients), it cannot be determined which of the tests was more accurate.
Rodriguez et al conducted a systematic review of PCA3 in men who had not yet undergone biopsy (Rodriguez, 2020). Nine studies in men without prior biopsy were identified, and 5 studies that used a cutoff of 35 were included in the meta-analysis. Rodriguez et al found pooled sensitivity of 69% and specificity of 65% in the 5 studies that used a cutoff of 35 in men without prior biopsy (Rodriguez, 2020). The studies were all prospective cohorts and rated as having a low risk of bias, except for uncertainty in flow and timing.
A similar validation study was published by Ankerst et al in 854 men who underwent a diagnostic biopsy (Ankerst, 2018). The addition of PCA3 to the PCPTRC increased the AUC (95% CI) from 70% (66.0 to 74.0%) to 76.4% (72.8 to 80.0%). The AUC with TMPRSS2:ERG added to both was 77.1% (73.6 to 80.6%). These have been added to the online risk tool for further validation.
The prospective multi-institutional Canary Prostate Surveillance Study (PASS) was reported by Newcomb et al (Newcomb, 2019). The study included 782 men under active surveillance (2,069 urine samples) to examine the association of urinary PCA3 and TMPRSS2:ERG with biopsy-based reclassification. Under the PASS protocol, PSA is measured every 3 months and ultrasound-guided biopsies are performed 12 and 24 months after diagnosis, then every 2 years. Post-DRE urine samples were collected every 6 months. Modeling showed minimal benefit of adding PCA3 to a model with clinical variables, improving the AUC from 0.743 to 0.753.
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2021. No new literature was identified that would prompt a change in the coverage statement.
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Hendriks et al evaluated the SelectMDx test to detect high-grade prostate cancer in biopsy-naive men (Hendriks, 2021). In total, 599 men in the Netherlands with PSA level of 3 ng/mL or greater scheduled for their initial biopsy were included in the study. All subjects underwent a multi-parametric magnetic resonance imaging (MRI) test and biopsy after urine sample and DRE were complete. The primary outcome was the detection rates of low- and high-grade prostate cancer and the number of biopsies avoided in 4 distinct diagnostic strategies: (1) SelectMDx test only, (2) MRI only, (3) SelectMDx test followed by MRI when SelectMDx test was positive (conditional strategy), and (4) SelectMDx and MRI in all (joint strategy). Decision curve analysis was performed to assess clinical utility. Overall, prevalence of high-grade prostate cancer was 31% (183/599). Thirty-eight percent of patients had negative SelectMDx tests in whom biopsy could be avoided. Decision curve analysis showed the highest net benefit for the MRI only strategy, followed by the conditional strategy at risk thresholds over 10%. Investigators also found that SelectMDx test led to a 35% reduction of over detection of low-grade prostate cancer and could save 38% of MRIs, at the cost of missing 10% of high-grade prostate cancers compared to biopsy for all patients. However, the use of MRI alone in all patients to select for prostate biopsy had the highest net benefit as a prebiopsy stratification tool.
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2023. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Digital rectal examination has a relatively low interrater agreement among urologists, with an estimated sensitivity, specificity, and positive predictive value (PPV) for diagnosis of prostate cancer of 59%, 94%, and 28%, respectively (Hoogendam, 1999). Digital rectal examination might have a higher PPV in the setting of elevated PSA (Gosselaar, 2008).
The risk of prostate cancer increases with increasing PSA levels; an estimated 15% of men with a PSA level of 4 ng/mL or less and a normal DRE, 30% to 35% of men with a PSA level between 4 ng/mL and 10 ng/mL, and more than 67% of men with a PSA level greater than 10 ng/mL will have biopsy-detectable prostate cancer (Thompson, 2004).
The European Randomized Study of Screening for Prostate Cancer (ERSPC) trial and Goteborg Randomized Prostate Cancer Screening Trial demonstrated that biennial PSA screening reduces the risk of being diagnosed with metastatic prostate cancer (Aus 2007, Buzzoni, 2015, Arnsrud, 2015, Hugosson, 2010, Schröder, 2009).
Using a common PSA level cutoff of 4.0 ng/mL, on behalf of the American Cancer Society, a systematic review of the literature was performed and calculated pooled estimates of elevated PSA sensitivity of 21% for detecting any prostate cancer and 5% for detecting high-grade cancers with an estimated specificity of 91% (Wolf, 2010).
Serious biopsy risks (e.g., bleeding or infection requiring hospitalization) have estimated rates ranging from less than 1% to 3% (Rosario, 2012 and Liss, 2012).
The relevant population of interest are men for whom an initial prostate biopsy is being considered because of clinical symptoms(ego, difficulty with urination, elevated PSA). The population for which these tests could be most informative is men in the indeterminate or “gray zone” range of PSA level on repeat testing with unsuspicious DRE findings. Repeat PSA testing is important because results initially reported being between4 ng/mL and 10 ng/mL frequently revert to normal (Lavallée, 2016). The gray zone for PSA levels is usually between 3 or 4 ng/mL and 10ng/mL, but PSA levels vary with age. Age-adjusted normal PSA ranges have been proposed but not standardized or validated.
TMPRSS2-ERG gene rearrangements have been reported in 50% or more of primary prostate cancer samples (Ruiz-Aragón, 2010).
Standard clinical examination for determining who requires a biopsy might include DRE, review of the history of PSA levels, along with consideration of risk factors such as age, race, and family history. The ratio of free (or unbound) PSA to total PSA(percent free PSA) is lower in men who have prostate cancer than in those who do not. A percent free PSA cutoff of 25% has been shown to have a sensitivity and specificity of 95% and 20%, respectively, for men with total PSA levels between 4.0 ng/mL and 10.0 ng/mL (Partin, 1998).
The best way to combine all risk information to determine who should go to biopsy is not standardized. Risk algorithms have been developed that incorporate clinical risk factors into a risk score or probability. Two examples are the Prostate Cancer Prevention Trial (PCPT) predictive model (Thompson, 2006) and the Rotterdam Prostate Cancer risk calculator (also known as the ERSPC-Risk Calculator 4 [ERSPC-RC]) (van Vugt, 2011). The American Urological Association and the Society of Abdominal Radiology (2016) recommend that high-quality prostate magnetic resonance imaging, if available, should be strongly considered in any patient with a prior negative biopsy who has persistent clinical suspicion for prostate cancer and who is under evaluation for a possible repeat biopsy (Rosenkrantz, 2016).
A systematic review and meta-analysis of studies reporting the diagnostic accuracy of the 4Kscoretest4K score to detect high grade prostate cancer using cutoff values of 7.5% to 10% (Mi, 2021) was performed. Pooled analysis found acceptable diagnostic accuracy (see Table 4). However, significant heterogeneity among the included studies lowered confidence in the results.
Several systematic reviews and meta-analyses have evaluated the clinical validity of p2PSA (proPSA) and PHI tests. The characteristics of the most relevant and comprehensive reviews are shown in Table 9. All primary studies were observational, and most were retrospective. Reviews included studies of men with a positive, negative, or inconclusive DRE; (Pecoraro, 2016) restricted eligibility to studies including PSA levels between 2 ng/mL and 10 ng/mL, while (Russo, 2017) restricted eligibility to studies including PSA levels between 2 ng/mL and 20 ng/mL. Anyango included studies in men of any age with any range of PSA levels and reported results according to different cutoffs (Anyango, 2021).
Pecoraro et al (2016) rated most of the 17 primary studies as low quality due to the design (most were retrospective), lack of blinding of outcome assessors to reference standard results, lack of clear cutoffs for diagnosis, and lack of explicit diagnostic question (Pecoraro, 2016). Russo et al (2017) included 23 studies that were mostly prospective and rated as moderate quality (Russo, 2017). There was high heterogeneity across studies, but pooled estimates showed generally low NPV (5% to 63%) and low specificity (25% to35%) when sensitivity was 90% to 93% (Table 10).
The performance of the 4Kscore test was validated in 1012 patients enrolled in a blinded, prospective study of all patients scheduled for a prostate biopsy at 26 urology centers in the U.S. (Tables 5 and 6). Biopsies were negative in 54% (n=542) of cases and showed low-grade (all Gleason grade 6) prostatic cancer in 24% (n=239) and high-grade cancer in 23% (n=231) of cases (Parekh, 2015). Statistical analysis of 4Kscore test clinical data had an area under the receiving operating curve of 0.82 for the detection of high-grade prostate cancer; the area under the receiving operating curve for the PCPT risk calculator model was 0.74, but a precision estimate was not given.
A second prospective validation study of the 4Kscore test conducted at 8 US Veterans Affairs hospitals from July 2015 to October 2016 (Tables 5 and 6) was reported on (Punnen, 2018). One aim of the study was to evaluate test performance in African American men; of 366 men enrolled and evaluated, 205 (56%) were African American. In a comparative analysis, there was no difference in test performance in African American and non-African American men (p =.32).
A retrospective exploratory analysis was conducted using data from the 2 previously published validation studies, to determine test performance with a cut-off of 7.5% as the indication to proceed with biopsy (Bhattu, 2021).
Longer-term data on the incidence of prostate cancer in men who do not have a biopsy following testing with the marketed version of 4Kscore are not available. However, a case-control study which was a nested cohort study of more than 17,000 Swedish men, estimated that, for men age 60 with PSA levels of 3 or higher and a kallikrein-related peptidase3 risk score less than 10%, the risk of metastasis at 20 years was 1.95% (95% confidence interval [CI], 0.64% to 4.66%) (Stattin, 2015).
A report on the results of a survey of 35 U.S. urologists identified through the 4Kscore database at OPKO Lab as belonging to practices that were large users of the test (Konety, 2015). All 611 patients of participating urologists to whom men were referred for an abnormal PSA level or DRE and had a 4Kscore test were included. Urologists, who received the 4Kscore as a continuous risk percentage, were retrospectively asked about their plans for biopsy before and after receiving the test results and whether the 4Kscore test results influenced their decisions. The physicians reported that the 4Kscore results influenced decisions in 89% of men and led to a 64.6% reduction in prostate biopsies. The 4Kscore risk categories (low risk: <7.5%,intermediate risk: 7.5% to 19.9%, high-risk: ≥20%) correlated highly (p<.001) with biopsy outcomes in 171 men with biopsy results.
A chain of evidence might be used to demonstrate clinical utility if each link in the chain is intact. Two observational studies have shown a reduction or delay in biopsy procedures for men with PSA levels in the 4 to 10 ng/mL range, nonsuspicious DRE findings, and a low PHI score. It was found a 9% reduction in the rate of biopsy of 345 men who underwent PHI testing compared with 1318 men who did not. (Tosoian , 2017). There was an associated 8% reduction in the incidence of negative biopsies in men who had PHI testing, but the interpretation of results is limited because the use of the PHI test was based solely on provider discretion. A prospective multicenter study evaluated physician recommendations for biopsy before and after receiving the PHI test result (White 2018). The PHI score affected the physician’s management plan in 73% of cases, with biopsy deferrals when the PHI score was low and the decision to perform biopsies when the PHI score was 36 or more. A chain of evidence requires evidence that the test could be used to affect health outcomes, and that the test is clinically valid. Due to questions about the clinical validity of the test, a chain of evidence cannot be constructed.
A retrospective outcome analysis follow-up study of 2.5 year of the initial 2020 study was reported on (Tutrone, 2023). Of the original 1094 cohort, 833 patients had complete follow-up data at 2.5 years. In this analysis, patients returned to routine standard of care after enrollment in the clinical utility trial, and a retrospective outcome analysis was conducted. The average time from ExoDX Prostate testing to the first biopsy was significantly longer in the low-risk ExoDX Prostate arm (216days) compared to high-risk ExoDX Prostate arm (68.7 days; p <.001) and when compared to low-risk ExoDX Prostate patients in the standard of care arm (79.4 days; p <.001). In the ExoDx Prostate arm, low-risk patients had significantly fewer biopsies than high-risk patients (44.6% vs 79.0%, p<.001); in the standard of care arm the decision to defer was independent of ExoDx Prostate score and, as a result, did not differ between low-risk and high-risk scores. Patients in both arms with low-risk ExoDx Prostate scores had lower rates of high-grade prostate cancer at 2.5 years than high-risk ExoDx Prostate score patients(7.9%vs. 26.8%; p<.001), and the ExoDx Prostate arm discovered 21.8% (106 vs 87) more high-grade prostate cancer than the standard of care arm. Limitations of this interim analysis mimic limitations that were described in the above study; the study was also retrospective in nature.
8 autoantibodies associated with prostate cancer were identified in a case-control study of men 40 to 70 years old with prostate cancer and PSA levels between 2.5 ng/mL and 20 ng/mL, compared to healthy men 25 to 40 years of age with PSA levels less than 1.0 ng/mL (Schipper, 2015). When the algorithm was applied to an independent validation set, the AUC was 0.69 (95% CI,0.62 to 0.75).
The beneficial outcome of the test is to avoid a negative biopsy for prostate cancer. A harmful outcome is a failure to undergo a biopsy that would be positive for prostate cancer, especially when the disease is advanced or aggressive. Thus, the relevant measures of clinical validity are sensitivity and NPV. The appropriate reference standard is a biopsy, though prostate biopsy is an imperfect diagnostic tool. Biopsies can miss cancers and repeat biopsies are sometimes needed to confirm the diagnosis. Detection rates vary by biopsy method and patient characteristics, with published estimates between 10% and 28% for a second biopsy and 5% and 10% for a third biopsy (Djavan, 2001 and Lujan, 2004). The timeframe of interest for calculating performance characteristics is time to biopsy results. Men who forego biopsy based on test results could miss or delay the diagnosis of cancer. Longer follow-up would be necessary to determine the effects on OS.
Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from RCTs. It was estimated the reduction in biopsies associated with ConfirmMDx use (Aubry, 2013). Using the performance characteristics from MATLOC, the authors estimated that 1106 biopsies per 1 million people would be avoided. The study did not include a decision analysis comparing the tradeoff in a reduction in biopsies and missed cancers.
A pathology services database was queried to identify (1) men who had a negative initial prostate biopsy and a negative PCMT (n=644), and (2) men who had a negative initial prostate biopsy and a repeat biopsy (n=823) (Legisi, 2016). Of the 644 patients with a negative PCMT, 35 had a repeat biopsy and 5 (14.2%) were false negatives who were found to have cancer on rebiopsy. The number of false negatives of the patients who did not have a repeat biopsy cannot be determined from this study (Legisi, 2016). Of the second group of 823 men who had a repeat biopsy, 132 had a PCMT. Changes in physician decision-making led to earlier detection of prostate cancer by 2.5 months and an increase in cancer detection rates, but this was only observed when men with atypical small acinar proliferation on index biopsy were not included. Interpretation of these results is limited because testing was not random or consecutive.
A 3-gene panel (HOXC6, TDRD1, DLX1) is now commercially available as SelectMDx (see above) (Leyten, 2015). It was reported the development of an 8-gene panel (PMP22, HPN, LMTK2, FN1, EZH2, GOLM1, PCA3,GSTP1) that distinguished high-grade prostate cancer from indolent prostate cancer with a sensitivity of 93% and NPV of 61%(Tables 36 and 37) (Xiao, 2016). Validation of this panel is needed.
|
|
|
|
| CPT/HCPCS: | |
|
|
|
| References: |
Ahmed H.(2010) Promoter methylation in prostate cancer and its application for the early detection of prostate cancer using serum and urine samples. Biomark Cancer 2010; 2010(2):17-33. American Urological Assoc.(2000) Prostate specific antigen (PSA). Best Practice Policy. Oncology 2000; 14:267-86. American Urological Association.(2013) Detection of prostate cancer, April 2013. Available online at: http://www.auanet.org/education/guidelines/prostate-cancer-detection.cfm. Ankerst DP, Goros M, Tomlins SA et al.(2018) Incorporation of Urinary Prostate Cancer Antigen 3 and TMPRSS2:ERG into Prostate Cancer Prevention Trial Risk Calculator. Eur Urol Focus, 2018 Feb 10;5(1). PMID 29422418 Ankerst DP, Groskopf J, Day JR et al.(2008) Predicting prostate cancer risk through incorporation of prostate cancer gene 3. J Urol 2008; 180(4):1303-8; discussion 08. Anyango R, Ojwando J, Mwita C, et al.(2021) Diagnostic accuracy of [-2]proPSA versus Gleason score and Prostate Health Index versus Gleason score for the determination of aggressive prostate cancer: a systematic review. JBI Evid Synth. Jun 2021; 19(6): 1263-1291. PMID 33741840 Arnsrud Godtman R, Holmberg E, Lilja H, et al.(2015) Opportunistic testing versus organized prostate-specific antigen screening: outcome after 18 years in the Göteborg randomized population-based prostate cancer screening trial. Eur Urol. Sep 2015; 68(3): 354-60. PMID 25556937 Aubry W, Lieberthal R, Willis A, et al.(2013) Budget impact model: epigenetic assay can help avoid unnecessary repeated prostate biopsies and reduce healthcare spending. Am Health Drug Benefits. Jan 2013; 6(1): 15-24. PMID 24991343 Auprich M, Chun FK, Ward JF et al.(2011) Critical assessment of preoperative urinary prostate cancer antigen 3 on the accuracy of prostate cancer staging. Eur Urol 2011; 59(1):96-105. Aus G, Bergdahl S, Lodding P, et al.(2007) Prostate cancer screening decreases the absolute risk of being diagnosed with advanced prostate cancer--results from a prospective, population-based randomized controlled trial. Eur Urol. Mar 2007; 51(3): 659-64. PMID 16934392 Bell KJ, Del Mar C, Wright G, et al.(2015) Prevalence of incidental prostate cancer: A systematic review of autopsy studies. Int J Cancer. Oct 01 2015; 137(7): 1749-57. PMID 25821151 Bhattu AS, Zappala SM, Parekh DJ, et al.(2021) A 4Kscore Cut-off of 7.5% for Prostate Biopsy Decisions Provides High Sensitivity and Negative Predictive Value for Significant Prostate Cancer. Urology. Feb 2021; 148: 53-58. PMID 33217456 Bill-Axelson A, Holmber L, Filen F et al.(2008) Radical prostatectomy versus watchful waiting in localized prostate cancer: the Scandinavian prostate cancer group-4 randomized trial. J Natl Cancer Inst. 2008; 100:1144-1154. Bostwick DG, Gould VE, Qian J et al.(2006) Prostate cancer detected by uPM3: radical prostatectomy findings. Mod Pathol 2006; 19(5):630-3. Bradley LA, Palomaki G, Gutman S et al.(2013) PCA3 Testing for the Diagnosis and Management of Prostate Cancer. Agency for Healthcare Research and Quality (AHRQ); Rockville MD2013. Bradley LA, Palomaki G, Gutman S, et al.(2013) PCA3 Testing for the Diagnosis and Management of Prostate Cancer. Comparative Effectiveness Review No. 98. (Prepared by the Blue Cross and Blue Shield Technology Evaluation Center Evidence-based Practice Center under Contract No. 290-2007-10058-I). AHRQ Publication No. 13-EHC030-EF. Rockville, MD: Agency for Healthcare Research and Quality; April 2013. www.effectivehealthcare.ahrq.gov/reports/final.cfm. Busetto GM, De Berardinis E, Sciarra A et al.(2013) Prostate cancer gene 3 and multiparametric magnetic resonance can reduce unnecessary biopsies: decision curve analysis to evaluate predictive models. Urology 2013; 82(6):1355-60. Bussemakers MJ, van Bokhoven A, et al.(1999) DD3: a new prostate-specific gene, highly overexpressed in prostate cancer. Cancer Res 1999; 59:5975-9. Buzzoni C, Auvinen A, Roobol MJ, et al.(2015) Metastatic Prostate Cancer Incidence and Prostate-specific Antigen Testing: New Insights from the European Randomized Study of Screening for Prostate Cancer. Eur Urol. Nov 2015; 68(5): 885-90. PMID 25791513 Capoluongo E, Zambon CF, Basso D et al.(2014) PCA3 score of 20 could improve prostate cancer detection: results obtained on 734 Italian individuals. Clin Chim Acta 2014; 429:46-50. Catalona WJ, Partin AW, Sanda MG et al.(2011) A multicenter study of [-2]pro-prostate specific antigen combined with prostate specific antigen and free prostate specific antigen for prostate cancer detection in the 2.0 to 10.0 ng/ml prostate specific antigen range. J. Urol., 2011 Mar 23;185(5). PMID 21419439 Chan SW, Nguyen PN, Violette P et al.(2013) Early detection of clinically significant prostate cancer at diagnosis: a prospective study using a novel panel of TMPRSS2:ETS fusion gene markers. Cancer Med 2013; 2(1):63-75. Chevli KK, Duff M, Walter P et al.(2013) Urinary PCA3 as a predictor for prostate cancer in a cohort of 3073 men undergoing initial prostate biopsy. J Urol 2013. Chun FK, de la Taille A, van Poppel H et al.(2009) Prostate cancer gene 3 (PCA3): development and internal validation of a novel biopsy nomogram. Eur Urol 2009; 56(4):659-67. Dal Pra A, Lalonde E, Sykes J et al.(2013) TMPRSS2-ERG status is not prognostic following prostate cancer radiotherapy: implications for fusion status and DSB repair. Clin Cancer Res 2013; 19(18):5202-9. de Kok JB, Verhaegh GW, et al.(2002) DD3, PCA3, a very sensitive and specific marker to detect prostate tumors. Cancer Res 2002; 62:2695-8. Djavan B, Waldert M, Zlotta A, et al.(2001) Safety and morbidity of first and repeat transrectal ultrasound guided prostate needle biopsies: results of a prospective European prostate cancer detection study. J Urol. Sep 2001; 166(3): 856-60. PMID 11490233 Draisma G, Etzioni R, Tsodikov A, et al.(2009) Lead time and overdiagnosis in prostate-specific antigen screening: importance of methods and context. J Natl Cancer Inst. 2009; 101:374-383. EGAPP Working Group(2013) Recommendations from the EGAPP Working Group: does PCA3 testing for the diagnosis and management of prostate cancer improve patient health outcomes? Genet Med 2013. Eilers T, Machtens S, Tezval H et al.(2007) Prospective diagnostic efficiency of biopsy washing DNA GSTP1 island hypermethylation for detection of adenocarcinoma of the prostate. Prostate 2007; 67(7):757-63. Ellinger J, Albers P, Perabo FG et al.(2009) CpG island hypermethylation of cell-free circulating serum DNA in patients with testicular cancer. J Urol 2009; 182(1):324-9. Ellinger J, Bastian PJ, Jurgan T et al.(2008) CpG island hypermethylation at multiple gene sites in diagnosis and prognosis of prostate cancer. Urology 2008; 71(1):161-7. Esgueva R, Perner S, J Lafarque C et al.(2010) Prevalence of TMPRSS2-ERG and SLC45A3-ERG gene fusions in a large prostatectomy cohort. Mod Pathol 2010; 23(4):539-46. Fradet Y, Saad F, et al.(2004) UPM3, a new molecular urine test for the detection of prostate cancer. Urology 2004; 64:311-16. Gandini O, Luci L, et al.(2003) Is DD3 a new prostate-specific gene. Anticancer Res 2003; 23:305-8. Ge YZ, Xu LW, Jia RP et al.(2013) The association between RASSF1A promoter methylation and prostate cancer: evidence from 19 published studies. Tumour Biol 2013. Gelmann, E.P. and Henshall, S.M.(2009) Clinically relevant prognostic markers for prostate cancer: the search goes on. Ann Intern Med. 2009; 150(9): 647-649. Gittelman MC, Hertzman B, Bailen J et al.(2013) PCA3 molecular urine test as a predictor of repeat prostate biopsy outcome in men with previous negative biopsies: a prospective multicenter clinical study. J Urol 2013; 190(1):64-9. Gleason DF.(1966) Classification of prostatic carcinomas. Cancer Chemother Rep. Mar 1966; 50(3): 125-8. PMID 5948714 Goessl C, Muller M, Heicappell R et al.(2001) DNA-based detection of prostate cancer in blood, urine, and ejaculates. Ann N Y Acad Sci 2001; 945:51-8. Gosselaar C, Roobol MJ, Roemeling S, et al.(2008) The role of the digital rectal examination in subsequent screening visits in the European randomized study of screening for prostate cancer (ERSPC), Rotterdam. Eur Urol. Sep 2008; 54(3): 581-8. PMID 18423977 Gudmundsson J, Sulem P, Rafnar T et al.(2008) Common sequence variants on 2p15 and Xp11.22 confer susceptibility to prostate cancer. Nat Genet 2008; 40(3):281-3. Haese A, de la Taille A, van Poppel H et al.(2008) Clinical utility of the PCA3 urine assay in European men scheduled for repeat biopsy. Eur Urol 2008; 54(5):1081-8. Haese A, Trooskens G, Steyaert S, et al.(2019) Multicenter Optimization and Validation of a 2-Gene mRNA Urine Test for Detection of Clinically Significant Prostate Cancer before Initial Prostate Biopsy. J Urol. Aug 2019; 202(2): 256-263. PMID 31026217 Hagglof C, Hammarsten P, Stromvall K et al.(2014) TMPRSS2-ERG Expression Predicts Prostate Cancer Survival and Associates with Stromal Biomarkers. PLoS One 2014; 9(2):e86824. Haldrup C, Mundbjerg K, Vestergaard EM et al.(2013) DNA methylation signatures for prediction of biochemical recurrence after radical prostatectomy of clinically localized prostate cancer. J Clin Oncol 2013; 31(26):3250-8. Hansen J, Auprich M, Ahyai SA et al.(2013) Initial prostate biopsy: development and internal validation of a biopsy-specific nomogram based on the prostate cancer antigen 3 assay. Eur Urol 2013; 63(2):201-9. Helfand BT, Fought AJ, Loeb S et al.(2010) Genetic prostate cancer risk assessment: common variants in 9 genomic regions are associated with cumulative risk. J Urol 2010; 184(2):501-5. Hendriks RJ, van der Leest MMG, Israel B, et al.(2021) Clinical use of the SelectMDx urinary-biomarker test with or without mpMRI in prostate cancer diagnosis: a prospective, multicenter study in biopsy-naive men. Prostate Cancer Prostatic Dis. Dec 2021; 24(4): 1110-1119. PMID 33941866 Henrique R, Ribeiro FR, Fonseca D et al.(2007) High promoter methylation levels of APC predict poor prognosis in sextant biopsies from prostate cancer patients. Clin Cancer Res 2007; 13(20):6122-9. Hessels D, Klein Gunnewiek JM, et al.(2003) DD3 (PCA3)-based molecular urine analysis for the diagnosis of prostate cancer. Eur Urol 2003; 44:8-15. Hoogendam A, Buntinx F, de Vet HC.(1999) The diagnostic value of digital rectal examination in primary care screening for prostate cancer: a meta-analysis. Fam Pract. Dec 1999; 16(6): 621-6. PMID 10625141 Howlader N, Noone AM, Krapcho M, et al.(2017) SEER Cancer Statistics Review, 1975-2014. Bethesda, MD: National Cancer Institute; 2017. Hugosson J, Carlsson S, Aus G, et al.(2010) Mortality results from the Göteborg randomised population-based prostate-cancer screening trial. Lancet Oncol. Aug 2010; 11(8): 725-32. PMID 20598634 Ioannidis JP, Castaldi P, Evangelou E.(2010) A compendium of genome-wide associations for cancer: critical synopsis and reappraisal. J Natl Cancer Inst 2010; 102(12):846-58. Kachakova D, Mitkova A, Popov E et al.(2013) Evaluation of the clinical value of the newly identified urine biomarker HIST1H4K for diagnosis and prognosis of prostate cancer in Bulgarian patients. J BUON 2013; 18(3):660-8. Konety B, Zappala SM, Parekh DJ, et al.(2015) The 4Kscore® Test Reduces Prostate Biopsy Rates in Community and Academic Urology Practices. Rev Urol. 2015; 17(4): 231-40. PMID 26839521 Lavallée LT, Binette A, Witiuk K, et al.(2016) Reducing the Harm of Prostate Cancer Screening: Repeated Prostate-Specific Antigen Testing. Mayo Clin Proc. Jan 2016; 91(1): 17-22. PMID 26688045 Laxman B, Morris DS, Yu J et al.(2008) A first-generation multiplex biomarker analysis of urine for the early detection of prostate cancer. Cancer Res 2008; 68(3):645-9. Laxman B, Tomlins SA, Mehra R et al.(2006) Noninvasive detection of TMPRSS2:ERG fusion transcripts in the urine of men with prostate cancer. Neoplasia 2006; 8(10):885-8. Legisi L, DeSa E, Qureshi MN.(2016) Use of the Prostate Core Mitomic Test in Repeated Biopsy Decision-Making: Real-World Assessment of Clinical Utility in a Multicenter Patient Population. Am Health Drug Benefits. Dec 2016; 9(9): 497-502. PMID 28465777 Leyten GH, Hessels D, Jannink SA et al.(2014) Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer. Eur Urol 2014; 65(3):534-42. Leyten GH, Hessels D, Smit FP, et al.(2015) Identification of a Candidate Gene Panel for the Early Diagnosis of Prostate Cancer. Clin Cancer Res. Jul 01 2015; 21(13): 3061-70. PMID 25788493 Leyten GH, Wierenga EA, Sedelaar JP et al.(2013) Value of PCA3 to Predict Biopsy Outcome and Its Potential Role in Selecting Patients for Multiparametric MRI. Int J Mol Sci 2013; 14(6):11347-55. Lin DW, Newcomb LF, Brown EC et al.(2013) Urinary TMPRSS2:ERG and PCA3 in an active surveillance cohort: results from a baseline analysis in the Canary Prostate Active Surveillance Study. Clin Cancer Res 2013; 19(9):2442-50. Lindstrom S, Schumacher F, Siddiq A et al.(2011) Characterizing Associations and SNP-Environment Interactions for GWAS-Identified Prostate Cancer Risk Markers-Results from BPC3. PLoS One 2011; 6(2):e17142. Liss M, Ehdaie B, Loeb S, et al.(2016) The Prevention and Treatment of the More Common Complications Related to Prostate Biopsy Update. 2012; updated 2016; https://www.auanet.org/guidelines-and-quality/guidelines/best-practice-statements-and-whitepapers/prostate-needle-biopsy-complications. Accessed September 19, 2022. Little J., Wilson B., Carter R., et al.(2012) Multigene Panels in Prostate Cancer Risk Assessment. Evidence Report No. 209. (Prepared by the McMaster University Evidence-based Practice Center under Contract No. 290-2007-10060-1.) AHRQ Publication No.12-E020-EF. Rockville, MD: Agency for Healthcare Research and Quality. July 2012. www.effectivehealthcare.ahrq.gov/reports/final.cfm. Loeb S, Shin SS, Broyles DL et al.(2016) Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer. BJU Int., 2016 Oct 16;120(1). PMID 27743489 Lujan M, Paez A, Santonja C, et al.(2004) Prostate cancer detection and tumor characteristics in men with multiple biopsy sessions. Prostate Cancer Prostatic Dis. 2004; 7(3): 238-42. PMID 15289810 Ma W, Diep K, Fritsche HA et al.(2014) Diagnostic and prognostic scoring system for prostate cancer using urine and plasma biomarkers. Genetic Test Mol Biomarkers 2014; 18(3):156-63. Mackinnon AC, Yan BC, Joseph LJ et al.(2009) Molecular biology underlying the clinical heterogeneity of prostate cancer: an update. Arch Pathol Lab Med 2009; 133(7):1033-40. MDx Health(2013) Epigenetic diagnostics for oncology, 2013. Available online at: http://mdxhealth.com/company/company-overview. Last accessed March 2014 Mi C, Bai L, Yang Y, et al.(2021) 4Kscore diagnostic value in patients with high-grade prostate cancer using cutoff values of 7.5% to 10%: A meta-analysis. Urol Oncol. Jun 2021; 39(6): 366.e1-366.e10. PMID 33685800 Moritz R, Ellinger J, Nuhn P et al.(2013) DNA hypermethylation as a predictor of PSA recurrence in patients with low- and intermediate-grade prostate cancer. Anticancer Res 2013; 33(12):5249-54. Nakanishi H, Groskopf J, Fritsche HA et al.(2008) PCA3 molecular urine assay correlates with prostate cancer tumor volume: implication in selecting candidates for active surveillance. J Urol 2008; 179(5):1804-9; discussion 09-10. National Cancer Institute (NCI).(2021) SEER Database. https://seer.cancer.gov/seerinquiry/index.php?page=view&id=20170036&type=q. Accessed February 23, 2021. National Comprehensive Cancer Network.(2014) NCCN clinical practice guidelines in oncology: prostate cancer early detection, version 1.2014. Available online at: http://www.nccn.org/professionals/physician_gls/pdf/prostate_detection.pdf. Newcomb LF, Zheng Y, Faino AV, et al.(2019) Performance of PCA3 and TMPRSS2:ERG urinary biomarkers in prediction of biopsy outcome in the Canary Prostate Active Surveillance Study (PASS). Prostate Cancer Prostatic Dis. Sep 2019; 22(3): 438-445. PMID 30664734 Ochiai A, Okihara K, Kamoi K et al.(2013) Clinical utility of the prostate cancer gene 3 (PCA3) urine assay in Japanese men undergoing prostate biopsy. BJU Int 2013; 111(6):928-33. Odedina FT, Akinremi TO, Chinegwundoh F, et al.(2009) Prostate cancer disparities in Black men of African descent: a comparative literature review of prostate cancer burden among Black men in the United States, Caribbean, United Kingdom, and West Africa. Infect Agent Cancer. Feb 10 2009; 4 Suppl 1: S2. PMID 19208207 Parekh DJ, Punnen S, Sjoberg DD, et al.(2015) A multi-institutional prospective trial in the USA confirms that the 4Kscore accurately identifies men with high-grade prostate cancer. Eur Urol. Sep 2015; 68(3): 464-70. PMID 25454615 Partin AW, Brawer MK, Subong EN, et al.(1998) Prospective evaluation of percent free-PSA and complexed-PSA for early detection of prostate cancer. Prostate Cancer Prostatic Dis. Jun 1998; 1(4): 197-203. PMID 12496895 Partin AW, Van Neste L, Klein EA, et al.(2014) Clinical validation of an epigenetic assay to predict negative histopathological results in repeat prostate biopsies. J Urol. Oct 2014; 192(4): 1081-7. PMID 24747657 Pecoraro V, Roli L, Plebani M, et al.(2016) Clinical utility of the (-2)proPSA and evaluation of the evidence: a systematic review. Clin Chem Lab Med. Jul 01 2016; 54(7): 1123-32. PMID 26609863 Perdona S, Cavadas V, Di Lorenzo G et al.(2011) Prostate cancer detection in the "grey area" of prostate-specific antigen below 10 ng/ml: head-to-head comparison of the updated PCPT calculator and Chun's nomogram, two risk estimators incorporating prostate cancer antigen 3. Eur Urol 2011; 59(1):81-7. Porpiglia F, Russo F, Manfredi M et al.(2014) The roles of multiparametric MRI, PCA3, and PHI: which is the best predictor of prostate cancer after a negative biopsy? Results of a prospective study. J Urol 2014. Punnen S, Freedland SJ, Polascik TJ, et al.(2018) A Multi-Institutional Prospective Trial Confirms Noninvasive Blood Test Maintains Predictive Value in African American Men. J Urol. Jun 2018; 199(6): 1459-1463. PMID 29223389 Qu X, Randhawa G, Friedman C et al.(2013) A three-marker FISH panel detects more genetic aberrations of AR, PTEN and TMPRSS2/ERG in castration-resistant or metastatic prostate cancers than in primary prostate tumors. PLoS One 2013; 8(9):e74671. Ren S, Xu J, Zhou T et al.(2013) Plateau effect of prostate cancer risk-associated SNPs in discriminating prostate biopsy outcomes. Prostate 2013; 73(16):1824-35. Rice KR, Chen Y, Ali A et al.(2010) Evaluation of the ETS-related gene mRNA in urine for the detection of prostate cancer. Clin Cancer Res 2010; 16(5):1572-6. Robinson K, Creed J, Reguly B, et al.(2010) Accurate prediction of repeat prostate biopsy outcomes by a mitochondrial DNA deletion assay. Prostate Cancer Prostatic Dis. Jun 2010; 13(2): 126-31. PMID 20084081 Rodon N, Trias I, Verdu M et al.(2013) Diagnostic and Predictive Value of Urine PCA3 Gene Expression for the Clinical Management of Patients with Altered Prostatic Specific Antigen. Actas Urol Esp 2013. Rodriguez SVM, Garcia-Perdomo HA.(2020) Diagnostic accuracy of prostate cancer antigen 3 (PCA3) prior to first prostate biopsy: A systematic review and meta-analysis. Can Urol Assoc J. May 2020; 14(5): E214-E219. PMID 31793864 Rosario DJ, Lane JA, Metcalfe C, et al.(2012) Short-term outcomes of prostate biopsy in men tested for cancer by prostate specific antigen: prospective evaluation within ProtecT study. BMJ. Jan 09 2012; 344: d7894. PMID 22232535 Rosenkrantz AB, Verma S, Choyke P, et al.(2016) Prostate Magnetic Resonance Imaging and Magnetic Resonance Imaging Targeted Biopsy in Patients with a Prior Negative Biopsy: A Consensus Statement by AUA and SAR. J Urol. Dec 2016; 196(6): 1613-1618. PMID 27320841 Rubio-Briones J, Casanova J, Dumont R et al.(2013) Optimizing prostate cancer screening; prospective randomized controlled study of the role of PSA and PCA3 testing in a sequential manner in an opportunistic screening program. Actas Urol Esp 2013. Ruffion A, Devonec M, Champetier D et al.(2014) PCA3 and PCA3-based nomograms improve diagnostic accuracy in patients undergoing first prostate biopsy. Int J Mol Sci 2013; 14(9):17767-80. Ruffion A, Perrin P, Devonec M et al. Additional value of PCA3 density to predict initial prostate biopsy outcome. World J Urol 2014. Ruiz-Aragón J, Márquez-Peláez S.(2010) [Assessment of the PCA3 test for prostate cancer diagnosis: a systematic review and meta-analysis]. Actas Urol Esp. Apr 2010; 34(4): 346-55. PMID 20470697 Russo GI, Regis F, Castelli T, et al.(2017) A Systematic Review and Meta-analysis of the Diagnostic Accuracy of Prostate Health Index and 4-Kallikrein Panel Score in Predicting Overall and High-grade Prostate Cancer. Clin Genitourin Cancer. Aug 2017; 15(4): 429-439.e1. PMID 28111174 Salinas CA, Koopmeiners JS, Kwon EM et al.(2009) Clinical utility of five genetic variants for predicting prostate cancer risk and mortality. Prostate 2009; 69(4):363-72. Schalken JA, Hessels D, Verhaegh G.(2003) New targets for therapy in prostate cancer: differential display code 3 (DD3(PCA3)), a highly prostate cancer-specific gene. Urology 2003; 62 (suppl 1):34-43. Schipper M, Wang G, Giles N, et al.(2015) Novel prostate cancer biomarkers derived from autoantibody signatures. Transl Oncol. Apr 2015; 8(2): 106-11. PMID 25926076 Schröder FH, Hugosson J, Roobol MJ, et al.(2009) Screening and prostate-cancer mortality in a randomized European study. N Engl J Med. Mar 26 2009; 360(13): 1320-8. PMID 19297566 Schroder FH, Venderbos LD, van den Bergh RC et al.(2014) Prostate cancer antigen 3: diagnostic outcomes in men presenting with urinary prostate cancer antigen 3 scores >/=100. Urology 2014; 83(3):613-6. Smith RA, Cokkinides V, et al.(2003) American Cancer Society Guidelines for the early detection of cancer 2003. CA Cancer J Clin 2003; 53:27-43. Stattin P, Vickers AJ, Sjoberg DD, et al.(2015) Improving the Specificity of Screening for Lethal Prostate Cancer Using Prostate-specific Antigen and a Panel of Kallikrein Markers: A Nested Case-Control Study. Eur Urol. Aug 2015; 68(2): 207-13. PMID 25682340 Stewart GD, Van Neste L, Delvenne P, et al.(2013) Clinical utility of an epigenetic assay to detect occult prostate cancer in histopathologically negative biopsies: results of the MATLOC study. J Urol. Mar 2013; 189(3): 1110-6. PMID 22999998 Suh CI, Shanafelt T, May DJ et al.(2000) Comparison of telomerase activity and GSTP1 promoter methylation in ejaculate as potential screening tests for prostate cancer. Mol Cell Probes 2000; 14(4):211-7. Sunami E, Shinozaki M, Higano CS et al.(2009) Multimarker circulating DNA assay for assessing blood of prostate cancer patients. Clin Chem 2009; 55(3):559-67. Thompson IM, Ankerst DP, Chi C, et al.(2006) Assessing prostate cancer risk: results from the Prostate Cancer Prevention Trial. J Natl Cancer Inst. Apr 19 2006; 98(8): 529-34. PMID 16622122 Thompson IM, Pauler DK, Goodman PJ, et al.(2004) Prevalence of prostate cancer among men with a prostate-specific antigen level or =4.0 ng per milliliter. N Engl J Med. May 27 2004; 350(22): 2239-46. PMID 15163773 Tosoian JJ, Druskin SC, Andreas D, et al.(2017) Use of the Prostate Health Index for detection of prostate cancer: results from a large academic practice. Prostate Cancer Prostatic Dis. Jun 2017; 20(2): 228-233. PMID 28117387 Tsuchiya N, Matsui S, Narita S et al.(2013) Distinct cancer-specific survival in metastatic prostate cancer patients classified by a panel of single nucleotide polymorphisms of cancer-associated genes. Genes Cancer 2013; 4(1-2):54-60. Tutrone R, Lowentritt B, Neuman B, et al.(2023) ExoDx prostate test as a predictor of outcomes of high-grade prostate cancer - an interim analysis. Prostate Cancer Prostatic Dis. Sep 2023; 26(3): 596-601. PMID 37193776 Vaananen RM, Lilja H, Kauko L et al.(2014) Cancer-associated changes in the expression of TMPRSS2-ERG, PCA3, and SPINK1 in histologically benign tissue from cancerous vs noncancerous prostatectomy specimens. Urology 2014; 83(2):511 e1-7. van Gils MP, Hessels D, Hulsbergen-van de Kaa CA et al.(2008) Detailed analysis of histopathological parameters in radical prostatectomy specimens and PCA3 urine test results. Prostate 2008; 68(11):1215-22. Van Neste L, Partin AW, Stewart GD, et al.(2016) Risk score predicts high-grade prostate cancer in DNA-methylation positive, histopathologically negative biopsies. Prostate. Sep 2016; 76(12): 1078-87. PMID 27121847 van Vugt HA, Roobol MJ, Kranse R, et al.(2011) Prediction of prostate cancer in unscreened men: external validation of a risk calculator. Eur J Cancer. Apr 2011; 47(6): 903-9. PMID 21163642 Verbeek JFM, Bangma CH, Kweldam CF et al.(2018) Reducing unnecessary biopsies while detecting clinically significant prostate cancer including cribriform growth with the ERSPC Rotterdam risk calculator and 4Kscore. Urol. Oncol., 2018 Dec 12;37(2). PMID 30528698 Whelan C, Kawachi M, Smith DD et al.(2014) Expressed prostatic secretion biomarkers improve stratification of NCCN active surveillance candidates: performance of secretion capacity and TMPRSS2:ERG models. J Urol 2014; 191(1):220-6. White J, Shenoy BV, Tutrone RF, et al.(2018) Clinical utility of the Prostate Health Index (phi) for biopsy decision management in a large group urology practice setting. Prostate Cancer Prostatic Dis. Apr 2018; 21(1): 78-84. PMID 29158509 Whitman EJ, Groskopf J, Ali A et al.(2008) PCA3 score before radical prostatectomy predicts extracapsular extension and tumor volume. J Urol 2008; 180(5):1975-8; discussion 78-9. Wolf AM, Wender RC, Etzioni RB, et al.(2010) American Cancer Society guideline for the early detection of prostate cancer: update 2010. CA Cancer J Clin. 2010; 60(2): 70-98. PMID 20200110 Woodson K, O'Reilly KJ, Ward DE et al.(2006) CD44 and PTGS2 methylation are independent prognostic markers for biochemical recurrence among prostate cancer patients with clinically localized disease. Epigenetics 2006; 1(4):183-6. Wysock JS, Becher E, Persily J, et al.(2020) Concordance and Performance of 4Kscore and SelectMDx for Informing Decision to Perform Prostate Biopsy and Detection of Prostate Cancer. Urology. Jul 2020; 141: 119-124. PMID 32294481 Xiao K, Guo J, Zhang X, et al.(2016) Use of two gene panels for prostate cancer diagnosis and patient risk stratification. Tumour Biol. Aug 2016; 37(8): 10115-22. PMID 26820133 Yao Y, Wang H, Li B et al.(2013) Evaluation of the TMPRSS2:ERG fusion for the detection of prostate cancer: a systematic review and meta-analysis. Tumour Biol 2013. Zheng SL, Sun J, Wiklund F et al.(2008) Cumulative association of five genetic variants with prostate cancer. N Engl J Med 2008; 358(9):910-9. |
|
|
|
|
Group specific policy will supersede this policy when applicable. This policy does not apply to the Wal-Mart Associates Group Health Plan participants or to the Tyson Group Health Plan participants.
CPT Codes Copyright © 2024 American Medical Association. |
|