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Medical Policy

Policy Num:       11.002.001
Policy Name:     Systems Pathology in Prostate Cancer
Policy ID:          [11.002.001]  [Ar / B / M / P ]   [2.04.64]

Last Review:       December 10, 2020
Next Review:      Archived
Issue:                   12, 2020

ARCHIVED

Related Policies:

7.01.121 Saturation Biopsy for Diagnosis and Staging of Prostate Cancer

Systems Pathology in Prostate Cancer

Summary

Systems pathology, an approach that combines cellular and biologic features to standard clinical parameters, such as age, clinical or pathologic stage, grade, percent of cancer on biopsy cores, and prostate-specific antigen (PSA) or its derivatives, is proposed as a way to estimate the probability of disease progression or recurrence, either before or after prostatectomy.

Objective

Studies are needed to determine which patients may benefit from this testing, as well as to determine when in the course of diagnosis and treatment the systems pathology assessment should be performed. There also should be further discussion about which outcomes are the best to be used in developing models; there can be substantial differences in models that predict PSA recurrence from those that predict metastatic disease and those that predict death. In addition, models may be needed that evaluate risk following treatments other than radical prostatectomy. The value of using the systems pathology approach to determine risk is not known based on currently available studies. Thus, the impact on clinical outcomes is not known, and the clinical utility of this testing is not known. Therefore, this testing is considered investigational. 

Policy Statements

Use of tests utilizing systems pathology that include cellular and biologic features of a tumor is considered investigational, including use in predicting risk of recurrence in patients with prostate cancer.

Policy Guidelines

There is no specific CPT code for this testing. The following are given as examples of coding that might
be used:
When the Prostate Px+ test was available, it was most likely reported as follows:
88313 (2 units) – Special stains; Group II, all other (eg, iron, trichrome), except immunocytochemistry and
immunoperoxidase stains, including interpretation and report, each
88323 (1 unit) – Consultation and report on referred material requiring preparation of slides
88347 (8 units) – Immunofluorescent study, each antibody; indirect method
88399 (1 unit) – Unlisted, surgical pathology procedure
When the Post-Op Px test was available, it was most likely reported as follows:
88313 (1 unit) – Special stains; Group II, all other (eg, iron, trichrome), except immunocytochemistry and
immunoperoxidase stains, including interpretation and report, each
88323 (1 unit) – Consultation and report on referred material requiring preparation of slides
88347 (5 units) – Immunofluorescent study, each antibody; indirect method
88399 (1 unit) – Unlisted, surgical pathology procedure

The test manufacturer stated at the time that the unlisted code was used to represent “the complex integrated data capture, image analysis and advanced supervised statistical modeling technologies necessary to perform this test.” It is possible that code 99090, analysis of clinical data stored in computers (eg, electrocardiograms, blood pressures, hematologic data), may be used instead of the unlisted code.

Benefit Application

BlueCard/National Account Issues

Some plans may have contract or benefit exclusions for genetic testing. This service has limited availability and may be performed by specialized laboratories.

Background

Predicting risk of recurrence in patients undergoing treatment for prostate cancer is difficult, as it is for most malignancies. Over time, risk models for patients with prostate cancer have evolved from early efforts that relied on grade, stage, and prostate-specific antigen (PSA) levels to complex multivariate models. A publication in 2008 indicates that there are more than 65 published, externally validated prostate cancer nomograms and other tools that use standard clinical parameters such as age, clinical or pathologic stage, grade, percent of cancer on biopsy cores, and PSA or its derivatives to predict various clinical and pathologic outcomes.1 Recent studies have begun to examine a different approach by adding both cellular and biologic features to the clinical and pathologic information just noted. This approach has been called “systems pathology.” Aureon Laboratories offered 2 pathology tests called the Prostate Px+™ test and the Post-Op Px™ test (formerly called Prostate Px). Prostate Px+ was described as useful at diagnosis for patients considering surgery (radical prostatectomy) or other treatment options by providing physicians with objective information on the probability of disease progression. Post-Op Px estimated risk of PSA recurrence and disease progression after surgery. In October 2011, the company ceased operations and the tests are no longer offered.

Regulatory Status

In 2011, the NADiA® ProsVue™ test (Iris International) was cleared for marketing by the U.S. Food and Drug Administration (FDA) through the 510(k) process .The NADiA ProsVue test evaluates risk of prostate cancer recurrence after radical prostatectomy when prostate-specific antigen (PSA) levels are less than 0.1 ng/mL. The NADiA immunoassay, polymerase chain reaction test is used to determine PSA levels on 3 serum samples taken between 6 weeks and 20 months after radical prostatectomy. The PSA data are entered into the ProsVue software to ensure appropriate serum sample use and calculation of assay results and to determine the rate of PSA change, the PSA slope.

Rationale

The evidence review was created with a literature review using MEDLINE through February 2010 and updated through November 12, 2015. Assessment of a diagnostic test, including tests used to predict clinical risk, typically focuses on 3 parameters: (1) technical performance; (2) diagnostic performance (sensitivity, specificity, and positive and negative predictive values) in appropriate populations of patients; and (3) demonstration that the diagnostic information can be used to improve patient outcomes (clinical utility). Technical performance for such testing may compare test measurements with a criterion standard and may also compare results taken on different occasions (test-retest). Diagnostic performance is evaluated by the ability of a test to accurately predict the clinical outcome. The sensitivity of a test is the ability to detect a disease (determine an outcome) when the condition is present (true positive), while the specificity is the ability to detect the absence of a disease or outcome when the disease is not present (true negative).

A key aspect in evaluating clinical test performance is evidence related to improvement of clinical outcomes with use of this testing, that is, evidence that assesses the link between use of a test to changes in health outcomes (clinical utility). In a clinical area such as prostate cancer in which multiple tools to predict risk already exist, a new test must demonstrate that any improvement in predictive accuracy results in meaningful changes in therapy and leads to improved outcomes. In many cases, comparative trials are needed to demonstrate the impact of testing on net health outcome.

In 2008, Donovan et al reported on use of a systems pathology tool through integration of clinicopathologic data with image analysis and quantitative immunofluorescence of prostate cancer tissue.2 In this study, an algorithm for postoperative risk was derived using a cohort of 758 patients with clinically localized or locally advanced prostate cancer who had tissue available for analysis and for whom outcomes were known. This cohort was assembled from 1 institution; patients were initially treated between 1985 and 2003. Samples were identified for 971 patients, but the cohort was reduced to 881 because some patients received treatment before prostatectomy and treatment before clinical failure. An additional 123 patients were excluded because of missing data elements, including missing outcome information. The derived model predicted distant metastasis and/or androgen-independent recurrence. The model was derived using 40 potential variables. The outcome was clinical failure; clinical failure was defined as unequivocal radiographic or pathologic evidence of metastasis, increasing prostate-specific antigen (PSA) in a castrate state, or death related to prostate cancer.

The model was derived using a training set of 373 patients with 33 (8.8%) clinical failure events (24 positive bone scans, 9 patients with increasing PSA levels). The model included androgen receptor levels, dominant prostatectomy Gleason grade, lymph node involvement, and 3 quantitative characteristics from hematoxylin and eosin (H&E) staining of prostate tissue. The model had a sensitivity of 90% and specificity of 91% for predicting clinical failure within 5 years after prostatectomy. The model was then validated on an independent cohort of 385 patients with 29 (7.5%) clinical failure events (22 positive bone scans, 7 with increasing PSA levels). This gave a sensitivity of 84% and specificity of 85%. High levels of androgen receptor predicted shorter time to castrate PSA increase after androgendeprivation therapy. The authors concluded that the integration of clinicopathologic variables with imaging and biomarker data (systems pathology) resulted in a highly accurate tool for predicting clinical failure within 5 years after prostatectomy. They also noted support for a role for androgen-receptor signaling in clinical progression and duration of response to androgen-deprivation therapy.

In a subsequent article from 2009, Donovan et al reported on derivation of another system’s pathology model to predict risk in prostate cancer based on preoperative assessment, including biopsy results.3 This publication reported on efforts to develop a patient-specific, biology-driven tool to predict outcome at diagnosis. The study also investigated whether biopsy androgen receptor levels predict a durable response to therapy after secondary treatment. The authors evaluated paraffin-embedded prostate needle biopsy tissue from 1027 patients with T1c-T3 prostate cancer treated with surgery between 1989 and 2003 and followed a median of 8 years. Information was initially compiled on 1487 patients from 6 institutions. Four-hundred sixty patients were excluded from analysis because of incomplete or missing information. Clinical failure was determined as noted in the study previously summarized. Modeling again began with 40 candidate variables. In the training set of 686 patients, 87 (12.7%) had clinical failure (9 with a positive bone scan, 78 with increasing PSA in a castrate state).

A total of 219 (32%) of these patients received standard androgen ablation with or without salvage radiotherapy.3 These treatments were done at the discretion of the treating physician for the cohort of patients in this analysis. Using clinical failure within 8 years as the outcome, the model had a sensitivity of 78% and specificity of 69% in the derivation set. The 6 variables in this model were as follows: preoperative PSA, dominant biopsy Gleason grade, biopsy Gleason score, and 3 systems pathology variables (androgen receptor, distance between epithelial tumor cells, tumor epithelial cell area). Patient from another (the fifth) institution were used for the validation set. In the validation set of 341 patients, the sensitivity was 76% and specificity 64%. There were 44 clinical failures (4 with positive bone scan, 40 with increasing PSA in a castrate state). This study also found that increased androgen receptor in biopsy tumor cells predicted resistance to therapy. The authors concluded that the additional systems pathology data improved the value of prediction rules used to assess outcome at diagnosis. The authors also commented that the nature of this study had the potential for bias.

Some investigators from these 2 studies were also involved in an earlier report from Memorial SloanKettering on used this approach to predict clinical failure (as measured by PSA recurrence) following radical prostatectomy.4 This study involved a training set of 323 patients.

Similarly, Eggener et al from the University of Chicago described development of 2 systems pathology models to determine which patients undergoing radical prostatectomy were likely to manifest systemic disease.5 They found their models to be accurate and commented that use of the novel markers may enhance the accuracy of the systems pathology approach.

Veltri et al from Johns Hopkins reported on use of nuclear morphometric signatures such as nuclear size, shape, DNA content, and chromatin texture in predicting PSA recurrence.6 This model was had an area under the receiver operating characteristic curve of 0.80. The authors concluded that PSA recurrence is more accurately predicted using these markers compared with routine pathology information alone.

In an editorial7 accompanying the 2008 article by Donovan et al,2 Klein et al raised a number of questions. Of particular concern was whether the differences with these new models have sufficient clinical relevance to justify the extra effort, expense, and expertise needed for the systems pathology approach. To make this determination, Klein recommended that additional studies be conducted to understand the incremental value of the new models.

Donovan et al commented that this approach would allow the development of more informed and appropriate treatment plans, including the potential for early decisions about androgen-deprivation therapy, radiotherapy, and/or chemotherapy in a subset of patients.

In 2010, Donovan et al investigated whether clinical variables before treatment and tumor specimen characteristics from patients with castrate-resistant metastatic prostate cancer could be used to predict time to prostate cancer‒specific mortality and overall survival.8 H&E slides, paraffin blocks, and outcome data from 104 castrate patients with metastatic prostate cancer were independently reviewed. Pathology samples were from prostatectomy specimens (n=43) and prostate needle biopsies (n=61). Patients included in the study had local and advanced disease (T1-T4), had been managed with radiotherapy or primary hormonal therapy, 47% had PSA level of 20 ng/mL or higher, and 52% had a Gleason sum greater than 7 at diagnosis. H&E morphometry and quantitative immunofluorescence assays for cytokeratin-18 (epithelial cells), 4,6-diamidino-2-phenylindole (nuclei), p63/high molecular weight keratin (basal cells), androgen receptors, and α-methyl coenzyme A racemase were performed. Immunofluorescence images were acquired with spectral imaging software and processed for quantification with specific algorithms. Median follow-up was 12 years from diagnosis. Of the 104 patients, 66 had evaluable immunofluorescence features. PSA level was the only clinical variable associated with outcome. The amount of androgen receptors present within tumor nuclei correlated with a greater risk of a shorter time to prostate cancer‒specific mortality (p<0.05). No H&E features correlated with mortality. The authors concluded that, using systems pathology, they identified and characterized a population of cells that expressed very high levels of androgen receptors that predict a more aggressive phenotype of prostate cancer.

Two studies published by Donovan et al in 2012 both used the same sample of postoperative tissue specimens described in the 2008 article by Donovan et al.9,10 One compared the Post-Op Px algorithm with 2 other nomograms for predicting PSA recurrence and clinical failure (PSA rise, bone metastasis, or prostate cancer‒related death).10 Data came from 373 patients included in the 2008 training set. The concordance index was used as a measure of classification accuracy. Regarding PSA recurrence, the Px algorithm was more accurate (0.76) than the D’Amico nomogram (0.70) and the Kattan nomogram (0.75).

Similarly, the Px model was more accurate for predicting clinical failure (0.84) than the D’Amico nomogram (0.73) and the Kattan nomogram (0.79). The other study9 used specimens from transurethral resection of the prostate in a postoperative model for predicting prostate cancer‒specific survival and disease progression. A training set consisted of 256 patients and a validation set included 269 patients. Performance of the training set was a concordance index of 0.79, sensitivity of 75%, and specificity of 86%. In the validation set, concordance index was 0.76, sensitivity was 59%, and specificity was 80%.

In 2012 Moul et al reported on the ability of the NADiA ProsVue to predict prostate cancer recurrence after radical prostatectomy.11 The NADiA test is a PSA immunoassay, polymerase chain reaction test designed to measure PSA levels less than 0.01 ng/mL. The ProsVue software calculates the risk of prostate cancer recurrence based on the rate of PSA change or slope of the 3 sequential NADiA PSA values. To validate the NADiA ProsVue, archived serum samples were tested from 304 men with biopsyconfirmed prostate cancer who underwent radical prostatectomy. Included patients had 3 serum samples available from 3 different time points after prostatectomy. PSA levels in the first serum sample after radical prostatectomy were required to be less than 0.1ng/mL. Study patients had been treated from 1990 to 2001 and were followed for up to 17.6 years. Median NADiA PSA level was 3.1 pg/mL after prostatectomy in patients who did not have prostate cancer recurrence and 14.1 pg/mL in patients with recurrence (p<0.001). In the prostate cancer recurrent group, PSA levels increased in the subsequent 2 serum samples tested but changed minimally in patients without recurrence. Patients with a PSA slope greater than 2.0 pg/mL/mo had a median disease-free survival of 4.8 years compared with 17.6 years in patients with a PSA slope of 2.0 pg/mL/mo or less (p<0.001). PSA slope of greater than 2.0 pg/mL/mo predicted a significantly higher risk of recurrence with a univariate hazard ratio of 18.3 (95% confidence interval [CI], 10.6 to 31.8; p<0.001). When the PSA slope was evaluated with the covariates of preprostatectomy PSA level, Gleason score, and pathologic stage, the multivariate hazard ratio was 9.8 (95% CI, 5.4 to 17.8; p<0.001). Gleason score of 7 or more was the only other covariate that significantly predicted risk of recurrence (hazard ratio, 5.4; 95% CI, 2.1 to 13.8; p<0.001).

In 2012 Moul et al reported on the ability of the NADiA ProsVue to predict prostate cancer recurrence after radical prostatectomy.11 The NADiA test is a PSA immunoassay, polymerase chain reaction test designed to measure PSA levels less than 0.01 ng/mL. The ProsVue software calculates the risk of prostate cancer recurrence based on the rate of PSA change or slope of the 3 sequential NADiA PSA values. To validate the NADiA ProsVue, archived serum samples were tested from 304 men with biopsyconfirmed prostate cancer who underwent radical prostatectomy. Included patients had 3 serum samples available from 3 different time points after prostatectomy. PSA levels in the first serum sample after radical prostatectomy were required to be less than 0.1ng/mL. Study patients had been treated from 1990 to 2001 and were followed for up to 17.6 years. Median NADiA PSA level was 3.1 pg/mL after prostatectomy in patients who did not have prostate cancer recurrence and 14.1 pg/mL in patients with recurrence (p<0.001). In the prostate cancer recurrent group, PSA levels increased in the subsequent 2 serum samples tested but changed minimally in patients without recurrence. Patients with a PSA slope greater than 2.0 pg/mL/mo had a median disease-free survival of 4.8 years compared with 17.6 years in patients with a PSA slope of 2.0 pg/mL/mo or less (p<0.001). PSA slope of greater than 2.0 pg/mL/mo predicted a significantly higher risk of recurrence with a univariate hazard ratio of 18.3 (95% confidence interval [CI], 10.6 to 31.8; p<0.001). When the PSA slope was evaluated with the covariates of preprostatectomy PSA level, Gleason score, and pathologic stage, the multivariate hazard ratio was 9.8 (95% CI, 5.4 to 17.8; p<0.001). Gleason score of 7 or more was the only other covariate that significantly predicted risk of recurrence (hazard ratio, 5.4; 95% CI, 2.1 to 13.8; p<0.001).

In 2014, Moul et al reported on a prospective multicenter trial of men treated by radical prostatectomy to assess the clinical utility of ProsVue PSA slope results.13 At postsurgical follow-up, men were stratified into low-, intermediate-, or high-risk groups for cancer recurrence based on clinicopathologic findings and other findings. Three serial serum samples for ProsVue testing were collected. Investigators recorded whether their initial treatment plan was changed after the ProsVue result was reported. Of 225 men, 128 (57%) were stratified into intermediate- and high-risk groups. Investigators reported that they would have referred 41 (32%) of the 128 men for secondary treatment but that, after the ProsVue result was reported, they referred 15 (12%) of the 128 men.

It is unknown whether the NADiA ProsVue after radical prostatectomy results in improved health outcomes, and there is no evidence to demonstrate incremental predictive value over other variables such as Gleason score or independent PSA levels.

Ongoing and Unpublished Clinical Trials

A search of ClinicalTrials.gov in November 2015 did not identify any ongoing or unpublished trials that would likely influence this review.

Population Reference No. 1 Policy Statement

Summary of Evidence

Studies are needed to determine which patients may benefit from this testing, as well as to determine when in the course of diagnosis and treatment the systems pathology assessment should be performed. There also should be further discussion about which outcomes are the best to be used in developing models; there can be substantial differences in models that predict prostate-specific antigen recurrence from those that predict metastatic disease and those that predict death. In addition, models may be needed that evaluate risk following treatments other than radical prostatectomy. The value of using the systems pathology approach to determine risk is not known based on currently available studies. Thus, the impact on clinical outcomes is not known, and the clinical utility of this testing is not known. Therefore, this testing is considered investigational.

Supplemental Information

Practice Guidelines and Position Statements

The National Comprehensive Cancer Network guidelines on Prostate Cancer Early Detection and Prostate Cancer (v.2.2015) do not address systems pathology.

Medicare National Coverage

There is no national coverage determination (NCD). In the absence of an NCD, coverage decisions are left to the discretion of local Medicare carriers.

References

Shariat SF, Karakiewicz PI, Margulis V, et al. Inventory of prostate cancer predictive tools. Curr Opin Urol. May
2008;18(3):279-296. PMID 18382238
2. Donovan MJ, Hamann S, Clayton M, et al. Systems pathology approach for the prediction of prostate cancer
progression after radical prostatectomy. J Clin Oncol. Aug 20 2008;26(24):3923-3929. PMID 18711180
3. Donovan MJ, Khan FM, Fernandez G, et al. Personalized prediction of tumor response and cancer progression
on prostate needle biopsy. J Urol. Jul 2009;182(1):125-132. PMID 19450827
4. Cordon-Cardo C, Kotsianti A, Verbel DA, et al. Improved prediction of prostate cancer recurrence through
systems pathology. J Clin Invest. Jul 2007;117(7):1876-1883. PMID 17557117
5. Eggener SE, Vickers AJ, Serio AM, et al. Comparison of models to predict clinical failure after radical
prostatectomy. Cancer. Jan 15 2009;115(2):303-310. PMID 19025977
6. Veltri RW, Miller MC, Isharwal S, et al. Prediction of prostate-specific antigen recurrence in men with long-term
follow-up postprostatectomy using quantitative nuclear morphometry. Cancer Epidemiol Biomarkers Prev. Jan
2008;17(1):102-110. PMID 18199716
7. Klein EA, Stephenson AJ, Raghavan D, et al. Systems pathology and predicting outcome after radical
prostatectomy. J Clin Oncol. Aug 20 2008;26(24):3916-3917. PMID 18711177
8. Donovan MJ, Osman I, Khan FM, et al. Androgen receptor expression is associated with prostate cancer-specific
survival in castrate patients with metastatic disease. BJU Int. Feb 2010;105(4):462-467. PMID 19624594
9. Donovan MJ, Khan FM, Bayer-Zubek V, et al. A systems-based modelling approach using transurethral
resection of the prostate (TURP) specimens yielded incremental prognostic significance to Gleason when
predicting long-term outcome in men with localized prostate cancer. BJU Int. Jan 2012;109(2):207-213. PMID
21733075
10. Donovan MJ, Khan FM, Powell D, et al. Postoperative systems models more accurately predict risk of significant
disease progression than standard risk groups and a 10-year postoperative nomogram: potential impact on the
receipt of adjuvant therapy after surgery. BJU Int. Jan 2012;109(1):40-45. PMID 21771247
11. Moul JW, Lilja H, Semmes OJ, et al. NADiA ProsVue prostate-specific antigen slope is an independent
prognostic marker for identifying men at reduced risk of clinical recurrence of prostate cancer after radical
prostatectomy. Urology. Dec 2012;80(6):1319-1325. PMID 23107099
12. Moul JW, Sarno MJ, McDermed JE, et al. NADiA ProsVue prostate-specific antigen slope, CAPRA-S, and
prostate cancer--specific survival after radical prostatectomy. Urology. Dec 2014;84(6):1427-1432. PMID
25432832
13. Moul JW, Chen DY, Trabulsi EJ, et al. Impact of NADiA ProsVue PSA slope on secondary treatment decisions
after radical prostatectomy. Prostate Cancer Prostatic Dis. Sep 2014;17(3):280-285. PMID 25027863

Codes

Appplicable Modifiers

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Policy History