Coverage Policy Manual
Policy #: 2012011
Category: Laboratory
Initiated: March 2012
Last Review: April 2018
  Proteomics, Predict Response to Chemotherapy (VeriStrat®)

Description:
About 85% to 90% of lung cancers are non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (TK) frequently overexpressed and activated in non-small cell lung cancer (NSCLC). Mutations in two regions of the EGFR gene (exons 18-24) --small deletions in exon 19 and a point mutation in exon 21 (L858R) -- appear to predict tumor response to tyrosine kinase inhibitors (TKIs) such as erlotinib. Other biomarkers have been investigated for their ability to predict response to treatment including Kirsten rat sarcoma (KRAS) gene variants, and rearrangements of the anaplastic lymphoma kinase (ALK) gene.
 
The VeriStrat assay is a proteomic assay that uses matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) to characterize the protein profile of pretreatment serum samples from patients with NSCLC. Patients are classified as “good” or “poor” based on a set of eight discriminating features of the proteomic profile, with “good” profiles predicted to be more likely to respond to EGFR TKI therapy.
 
Proteomic profiling is also being studied in patients diagnosed with head and neck cancer and colorectal cancer to predict response to treatment with erlotinib and cetuximab (Chung, 2010) (NCT00397384).
 
The VeriStrat test was developed by Biodesix (Bloomfield, CO).  The test has not been reviewed or approved by the U.S. Food and Drug Administration.
 
Coding
Effective 3/2015, CPT published a specific CPT code for this service:
 
81538: Oncology (lung), mass spectrometric 8-protein signature, including amyloid A, utilizing serum, prognostic and predictive algorithm reported as good versus poor overall survival
 
Prior to 3/2015
There is no specific CPT code for this test. The unlisted CPT code 81599, Unlisted multianalyte assay with algorithmic analysis may be used to bill this service.
 
Related Policy:  Policy # 2004021, Proteomics Pattern Analysis for Identification of Cancer

Policy/
Coverage:
The use of the VeriStrat® test to predict response to cancer chemotherapy does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness because this test is presently under study to determine effectiveness, and at present the test has not been shown to improve health outcomes.
 
For contracts without primary coverage criteria, the use of the VeriStrat® test to predict response to cancer chemotherapy is considered investigational.  Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 

Rationale:
This policy is developed based on findings of a literature search of the MEDLINE database through February 2012.  The literature search was focused on VeriStrat and proteomics used to predict response to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) in the treatment of non-small cell lung cancer (NSCLC). The following is a summary of the identified literature.
 
Non-Small Cell Lung Cancer
Taguchi and colleagues developed a classification algorithm based on matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) analysis of pretreatment serum to identify patients that may benefit from treatment with EGFR TKIs. This algorithm is the basis of the VeriStrat test (Taguchi, 2007). Pretreatment serum was obtained from 139 NSCLC patients being treated with gefitinib (training set) and was used to identify and optimize the spectral classifiers. The training set was composed of three cohorts of patients from Italy and Japan. Two additional validation cohorts and three control cohorts were also tested to assess the reproducibility of the algorithm. The validation cohorts consisted of patients treated with gefitinib (N=67; Scientific Institute Hospital San Raffaele, Italy) and erlotinib (N=96; Eastern Cooperative Oncology Group [ECOG] 350). The control cohorts included 93 patients with resectable disease from Italy (N=32) and the United States (N=61) and 65 patients with resectable disease from Poland. MALDI-TOF mass spectrometry was used to identify a protein profile that correlated with treatment response. Eight spectral peaks were selected as discriminating “features” used to classify patients as having a “good” or “poor” treatment outcome with EGFR TKI treatment. The overall concordance with which the training set and the validation cohorts were labeled as “good”, “poor” or “undefined” was 97.1%. Clinical outcomes of overall survival (OS) and time to progression (TTP) were also assessed. Overall survival and time to progression was improved in both validation groups in those patients with “good” results compared to patients that received “poor” results. There was no significant difference in overall survival between patients with “good” versus “poor” results in all 3 control groups (Taguchi, 2007).
 
Salmon and colleagues also used MALDI-TOF mass spectrometry to analyze pretreatment samples in patients enrolled in an open-label, phase I/II study being treated with erlotinib and bevacizumab. Samples were also analyzed from patients in validation and control cohorts. The validation cohort (N=82) like the study by Taguchi and colleagues (2007), consisted of patients enrolled in the ECOG 350 protocol. The control group (N=61) was comprised of patients from Vanderbilt University Medical Center and were the same patients used in the 2007 study by Taguchi et al. Outcomes of OS and progression free survival (PFS) were assessed. The proteomic algorithm used in this study showed significant association with both OS and PFS 9 (Salmon, 2009). Carbone and colleagues evaluated the VeriStrat test in this same population of patients enrolled in an open-label, phaseI/II study assessing treatment with erlotinib and bevacizumab (Carbone, 2010). Pretreatment serum samples were obtained from 35 patients with stage IIIb or stage IV NSCLC.  The samples were analyzed and classified as VeriStrat “good” or VeriStrat “poor”. The median PFS was 26 weeks for those with a “good” result and 8 weeks for those with a “poor” result.  
 
Proteomic profiling to predict response to EGFR TKI treatment was assessed (Amann, 2010) in samples from 102 patients diagnosed with NSCLC enrolled in the Eastern Cooperative Oncology Group 3503 phase II study. In this study, tumor samples were also obtained to identify KRAS and epidermal growth factor receptor (EGFR) status. Of the  41 analyzable tumor samples, 9 demonstrated KRAS mutations and 3 were positive for EGFR mutations. VeriStrat results were available for 88 patients with 64 classified as VeriStrat “good” and 24 as VeriStrat “poor”. Using OS and TTP data updated from previously reported data (Taguchi, 2007), a univariate Cox regression analysis revealed a significant association between VeriStrat classification and OS as well as TTP. In a multivariate analysis, the correlation between VeriStrat “good” results and improved OS was not statistically significant (Amann, 2010).
 
Other Cancers
The VeriStrat test was used to analyze serum or plasma samples from 230 patients treated with cetuximab, EGFR-TKI or chemotherapy for recurrent/metastatic head and neck squamous cell carcinoma or colorectal cancer (Chung, 2010). Pretreatment samples were analyzed and classified as either VeriStrat “good” or VeriStrat “poor”.  Survival analyses of each cohort were done based on the classifications.  In the EGFR inhibitor-treated cohorts, the classification predicted survival but no survival difference was noted in the chemotherapy treatment cohort.  For colorectal cancer patients, tumor EGFR ligand RNA levels were significantly associated with the proteomic classification, and combined KRAS and proteomic classification proteomic classification provided improved survival classification.  The author reports, “prospective studies are necessary to confirm these findings”.
 
Proteomic profiling is currently being studied in clinical trials to predict response to chemotherapy in patients diagnosed with non-small cell lung cancer, head and neck cancer and colorectal cancer (NCT00397384) (NCT00550537) (NCT00717847).
 
National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology: Non-Small Cell Lung Cancer (V3.2011) does not mention VeriStrat testing to predict response in patients with NSCLC treated with EGFR Tyrosine Kinase Inhibitors.
 
It is important to note that several of the studies identified in the literature search involve overlapping patient populations (Taguchi, 2007) (Salmon, 2009) (Carbone, 2010) (Amann, 2010). This essentially reduces the number of patients that have been tested with VeriStrat and limits the significance of the findings of these studies.  Additionally, no studies were identified that evaluated the clinical utility of the VeriStrat test. Further studies that assess the impact of VeriStrat test results on patient management and health outcomes are needed.
 
2013 Update
A literature search was conducted using the MEDLINE database through February 2013. Several studies addressing the analytic and clinical validity of VeriStrat (Kuiper, 2012; Gautschi, 2013; Carbone, 2012; Stinchcombe, 2013) were identified. However, there was no new information identified regarding the clinical utility of the test. There remains a lack of scientific literature supporting the clinical utility of this testing and therefore the policy statement is unchanged.
 
2014 Update
A literature search was conducted using the MEDLINE database through February 2014. There was no new information identified that would prompt a change in the coverage statement.
 
2015 Update
 
A literature search conducted through February 2015 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Sun and colleagues conducted  studies by electronic searches for relevant articles in PubMed, Embase, Medline, and Web of Science published up to May 2013 (Sun, 2014). Stata Statistical Software version 12.0 was applied for statistical analysis. The combined hazard ratio (HR) and 95% confidence interval (CI) were estimated using fixed-effects models. Eleven cohorts involving 706 patients collected from seven studies were subjected to final analysis. This serum-based proteomic test's 'good' status predicted a better clinical outcome with a pooled HR of 0.40 (95% CI 0.32 to 0.49; p < 0.001) for overall survival (OS), and 0.49 (95% CI 0.39 to 0.60; p < 0.001) for progression-free survival (PFS). There was no significant heterogeneity, but a slight publication bias in this study. Our meta-analysis demonstrated that this serum-based proteomic test has a predictive value for NSCLC patients treated with EGFR-TKIs. Future data are needed to validate and update the results.
 
Molina-Pinelo and colleagues reported on the role of EGF receptor (EGFR) inhibitors in the treatment of lung cancer without activating EGFR mutations being a controversial issue, particularly their relative efficacy over the available chemotherapy in the second- and third-line setting (Molina-Pinelo, 2014). VeriStrat is a serum/plasma proteomic test developed using matrix-assisted laser desorption/ionization methodology, aiming at predicting benefit from EGFR treatment. The VeriStrat algorithm has been interrogated retrospectively and prospectively in samples from randomised trials, such as the PROSE study, confirming the prognostic information associated with the signature. In addition, the test appeared to be predictive of erlotinib impact on survival, as only VeriStrat Good patients benefited from such a treatment. Additional studies should confirm and further define its role in predicting EGFR tyrosine kinase inhibitor benefit, and to establish its better use in terms of clinical efficiency identifying which patients are candidates for the test, at which time on the history of the disease, and lastly at what extra cost.
 
2016 Update
A literature search was conducted using the MEDLINE database through March 2016. Several publications were reviewed (Ciuleanu, 2012;  Karampeazis, 2013; Garassino, 2013; Auliac, 2014; Yang, 2015; Hornberger, 2015; Masters, 2015) but there was no new information identified that would prompt a change in the coverage statement.   
 
2017 Update
A literature search conducted through March 2017 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Cicenas and colleagues reported results of the IUNO RCT, which compared maintenance therapy with erlotinib followed by second line chemotherapy if progression occurred to placebo followed by erlotinib if progression occurred in 643 patients with advanced NSCLC with no known EGFR variant (Cicenas, 2016). Because there were no significant differences between groups in terms of PFS, objective response rate, or disease control rate, maintenance therapy with erlotinib in patients without EGFR variants was not considered efficacious.
 
Ongoing Clinical Trials
Some currently ongoing trials that might influence this review are listed below:
Ongoing
(NCT02055144) VeriStrat as Predictor of Benefit of First Line Non-Small Cell Lung Cancer (NSCLC) Patients from Standard Chemotherapy; planned enrollment 100; projected completion date May 2015, study still ongoing.
 
2018 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2018. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
Proteomic Testing in NSCLC to Predict Response to Therapy
Based on the association between VeriStrat status and uutcomes in patients treated with EGFR-TKIs, it was postulated that VeriStrat testing may predict response to EGFR-TKIs.
 
In the largest study to evaluate the VeriStrat test as a predictor of therapy response (the PROSE trial), Gregorc et al prospectively evaluated the VeriStrat test in a randomized controlled trial (RCT) comparing erlotinib with chemotherapy as second-line treatment for patients with stage IIIB or IV NSCLC, stratified by performance status, smoking history, treatment center, and (masked) pretreatment VeriStrat classification (Gregorc, 2014). Standard chemotherapy was pemetrexed or docetaxel. Analysis was per protocol. Of 142 patients randomized to chemotherapy and 143 to erlotinib, and 129 (91%) and 134 (94%), respectively, were included in the per-protocol analysis (n=262). EGFR variant analysis was available for 193 (73%); 14 (5%) patients had sensitizing EGFR variants. Of the analysis sample, 184 (70%) and 79 (30%) had VeriStrat “good” and “poor” classifications, respectively. Across both groups, the VeriStrat “good” classification was associated with improved OS and PFS.
  
Several retrospective analyses of data from RCTs evaluating the efficacy of TKIs have examined VeriStrat as a prognostic and/or predictive test. Carbone et al investigated the prognostic and predictive effects of VeriStrat classification on response to treatment and survival in a subset of patients enrolled in a phase 3 clinical trial of erlotinib vs placebo (Carbone, 2012). BR.21, a randomized, placebo-controlled study of erlotinib, enrolled 731 previously treated patients with advanced NSCLC. In the primary study, PFS and OS were prolonged by erlotinib. EGFR variants were prognostic for OS, but not predictive of erlotinib benefit, while increased EGFR copy number variant was both prognostic and predictive of erlotinib benefit. For the present study, plasma from 441 patients was tested with the VeriStrat test, of which 436 (98.9%) could be classified as “good” or “poor.”
 
 Akerley et al published 2 studies evaluating the impact of VeriStrat testing on physician treatment recommendations. In a 2013 study of 226 physicians who provided pre- and posttest treatment plan information for 403 VeriStrat tests, in the 262 cases where pretreatment recommendations were for erlotinib only, for those patients who were classified as VeriStrat “poor,” physicians recommended erlotinib in 13.3% (Akerley, 2013). In a larger 2017 study, Akerley et al reported on 2411 physicians reporting on 14,327 VeriStrat tests (Akerley, 2017). The investigators only included test that were ordered for NSCLC, were ordered as the sole test, were not indeterminate, and were not ordered in patients with known EGFR variant status. VeriStrat findings were a classification of “good” for 1950 (78.2%) patients and “poor” in 544 patients (21.8%). After receiving the test results, physicians changed their treatment recommendations in 28.2% of the cases; within this group, 13.2% were classified as VeriStrat “good” and 81.6% as VeriStrat “poor”. Physicians initially considered treatment with an EGFR-TKI in 484 (89.0%) of 544 classified as VeriStrat “poor”; after receiving test results only 49 (10%) were actually recommended EGFR-TKI treatment. The studies did not evaluate patient outcomes, and did not evaluate the impact of EGFR testing on treatment recommendations (the number of patients who had previously received EGFR tests was not reported).

CPT/HCPCS:
81538Oncology (lung), mass spectrometric 8-protein signature, including amyloid A, utilizing serum, prognostic and predictive algorithm reported as good versus poor overall survival
81599Unlisted multianalyte assay with algorithmic analysis
84999Unlisted chemistry procedure

References: A study of serum protein profiling in patients with non-small cell lung cancer treated with gefitinib or erlotinib. NCT00717847. http://www.clinicaltrials.gov. Last accessed March 2012.

Akerley WL, Nelson RE, Cowie RH, et al.(2013) The impact of a serum based proteomic mass spectrometry test on treatment recommendations in advanced non-small-cell lung cancer. Curr Med Res Opin. May 2013;29(5):517-525. PMID 23452275

Amann JM, Lee JW, Roder H, et al.(2010) Genetic and proteomic features associated with survival after treatment with Erlotinib in first-line therapy of non-small cell lung cancer in Eastern Cooperative Oncology Group 3503. J ThoracOncol. 2010;5(2):169-178.

Auliac JB, Chouaid C, Greillier L, et al.(2014) Randomized open-label non-comparative multicenter phase II trial of sequential erlotinib and docetaxel versus docetaxel alone in patients with non-small-cell lung cancer after failure of first-line chemotherapy: GFPC 10.02 study. Lung Cancer. Sep 2014;85(3):415-419. PMID 25082565

Carbone DP, Ding K, Roder H, et al.(2012) Prognostic and predictive role of the VeriStrat plasma test in patients with advanced non-small-cell lung cancer treated with erlotinib or placebo in the NCIC Clinical Trials Group BR.21 trial. J Thorac Oncol. Nov 2012;7(11):1653-1660. PMID 23059783

Carbone DP, Ding K, Roder H, et al.(2012) Prognostic and predictive role of the VeriStrat® plasma test in patients with advanced no-small-cell lung cancer treated with erlotinib or placebo in the NCIC clinical trials group BR.21 trial. J Thorac Oncol. 2012;7:1653-1660.

Carbone DP, Salmon JS, Billheimer D, et al.(2010) VeriStrat classifier for survival and time to progression in non-small cell lung cancer (NSCLC) patients treated with erlotinib and bevacizumab. Lung Cancer. 2010;69(3):337-340.

Chung CH, Seeley EH, Roder H, et al.(2010) Detection of tumor epidermal growth factor receptor pathway dependence by serum mass spectrometry in cancer patients. Cancer Epidemiol Biomarkers Prev. 2010 Feb;19(2):358-65.

Cicenas S, Geater SL, Petrov P, et al.(2016) Maintenance erlotinib versus erlotinib at disease progression in patients with advanced non-small-cell lung cancer who have not progressed following platinum-based chemotherapy (IUNO study). Lung Cancer. Dec 2016;102:30-37. PMID 27987585

Ciuleanu T, Stelmakh L, Cicenas S, et al.(2012) Efficacy and safety of erlotinib versus chemotherapy in second-line treatment of patients with advanced, non-small-cell lung cancer with poor prognosis (TITAN): a randomized multicentre, open-label, phase 3 study. Lancet Oncol. Mar 2012;13(3):300-308. PMID 22277837

Erlotinib and cetuximab in treating patients with advanced gastrointestinal cancer, head and neck cancer, non-small cell lung cancer, or colorectal cancer. NCT00397384. http://www.clinicaltrials.gov. Last accessed March 2012.

Garassino MC, Martelli O, Broggini M, et al.(2013) Erlotinib versus docetaxel as second-line treatment of patients with advanced non-small-cell lung cancer and wild-type EGFR tumours (TAILOR): a randomised controlled trial. The Lancet Oncology. 2013;14(10):981-988.

Gautschi O, Dingemans AM, Crowe S, et al.(2013) VeriStrat® has a prognostic value for patients with advanced non-small cell lung cancer treated with erlotinib and bevacizumab in the first line: pooled analysis of SAKK19/05 and NTR528. Lung Cancer. 2013 Jan;79(1):59-64.

Gregorc V, Novello S, Lazzari C, et al.(2014) Predictive value of a proteomic signature in patients with non-small-cell lung cancer treated with second-line erlotinib or chemotherapy (PROSE): a biomarker-stratified, randomised phase 3 trial. Lancet Oncol. Jun 2014;15(7):713-721. PMID 24831979

Grossi F, Rijavec E, Genova C, et al.(2017) Serum proteomic test in advanced non-squamous non-small cell lung cancer treated in first line with standard chemotherapy. Br J Cancer. Jan 03 2017;116(1):36-43. PMID 27898657

Hornberger J, Hirsch FR, Li Q, et al.(2015) Outcome and economic implications of proteomic test-guided second- or third-line treatment for advanced non-small cell lung cancer: extended analysis of the PROSE trial. Lung Cancer. May 2015;88(2):223-230. PMID 25804732

Karampeazis A, Voutsina A, Souglakos J, et al.(2013) Pemetrexed versus erlotinib in pretreated patients with advanced non-small cell lung cancer: a Hellenic Oncology Research Group (HORG) randomized phase 3 study. Cancer. Aug 1 2013;119(15):2754-2764. PMID 23661337

Kuiper JL, Lind JSW, Groen HJM et al.(2012) VeriStrat® has prognostic value in advanced stage NSCLC patients treated with erlotinib and sorafenib. Br J Cancer. 2012 Nov 20(11):1820-5.

Lazzari C, Spreafico A, Bachi A, et al.(2012) Changes in plasma mass-spectral profile in course of treatment of nonsmall cell lung cancer patients with epidermal growth factor receptor tyrosine kinase inhibitors. J Thorac Oncol.2012;7(1):40-48.

Masters GA, Temin S, Azzoli CG, et al.(2015) Systemic therapy for stage IV non-small-cell lung cancer: American Society of Clinical Oncology Clinical Practice Guideline Update. J Clin Oncol. Oct 20 2015;33(30):3488-3515. PMID 26324367

Molina-Pinelo S, Pastor MD, Paz-Ares L(2014) VeriStrat: a prognostic and/or predictive biomarker for advanced lung cancer patients? Expert Rev Respir Med. 2014 Feb;8(1):1-4. doi: 10.1586/17476348.2014.861744

National Comprehensive Cancer Network (NCCN)(2011) Clinical Practice Guidelines in Oncology: Non-Small Cell Lung Cancer (V3.2011) http://www.nccn.org. Last accessed March 2012.

Proteomic profiling in predicting response in patients receiving erlotinib for stage IIIB, stage IV, or recurrent non-small cell lung cancer. NCT00550537. http://www.clinicaltrials.gov. Last accessed March 2012.

Salmon S, Chen H, Chen S, et al.(2009) Classification by mass spectrometry can accurately and reliably predict outcome in patients with non-small cell lung cancer treated with erlotinib-containing regimen. J Thorac Oncol.2009;4(6):689-696.

Stinchcombe TE, Roder J, Peterman AH, et al.(2013) A retrospective analysis of VeriStrat status on outcome of a randomized phase II trial of first-line therapy with gemcitabine, erlotinib, or the combination in elderly patients (age 70 years or older) with stage IIIB/IV non-small-cell lung cancer. J Thorac Oncol. 2013 Apr;8(4):443-51.

Sun W, Hu G, Long G et al.(2014) Predictive value of a serum-based proteomic test in non-small-cell lung cancer patients treated with epidermal growth factor receptor tyrosine kinase inhibitors: a meta-analysis. Curr Med Res Opin. 2014 Oct;30(10):2033-9

Taguchi F, Solomon B, Gregorc V, et al.(2007) Mass spectrometry to classify non-small-cell lung cancer patients for clinical outcome after treatment with epidermal growth factor receptor tyrosine kinase inhibitors: a multicohort cross-institutional study. J Natl Cancer Inst 2007;99:838-46.

Taguchi F, Solomon B, Gregorc V, et al.(2007) Mass spectrometry to classify non-small-cell lung cancer patients for clinical outcome after treatment with epidermal growth factor receptor tyrosine kinase inhibitors: a multicohort cross-institutional study. J Natl Cancer Inst. 2007;99(11):838-846.

Yang L, Tang C, Xu B, et al.(2015) Classification of epidermal growth factor receptor gene mutation status using serum proteomic profiling predicts tumor response in patients with stage IIIB or IV non-small-cell lung cancer. PLoS One. 2015;10(6):e0128970. PMID 26047516


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 © 2019 American Medical Association.