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Proteomics, Predict Response to Chemotherapy (e.g., VeriStrat®) | |
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Description: |
Proteomic testing has been proposed as a way to predict survival outcomes, as well as the response to and selection of targeted therapy for patients with non-small-cell lung cancer (NSCLC). One commercially available test (the VeriStrat assay) has been investigated as a predictive marker for response to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors.
Lung cancer is the leading cause of cancer death in the U.S., with an estimated 228,820 new cases and 135,720 deaths due to the disease in 2020 (NCCN, 2022). NSCLC accounts for approximately 85% of lung cancer cases and includes nonsquamous carcinoma (adenocarcinoma, large cell carcinoma, other cell types) and squamous cell carcinoma.
The stage at which lung cancer is diagnosed has the greatest impact on prognosis (SEER, 2021). Localized disease confined to the primary site has a 59.8% relative 5-year survival but accounts for only 18% of lung cancer cases at diagnosis. Mortality increases sharply with advancing stage. Metastatic lung cancer has a relative 5-year survival of 6.3%. Overall, advanced disease, defined as regional involvement and metastatic, accounts for approximately 80% of cases of lung cancer at diagnosis. These statistics are mirrored for the population of NSCLC, with 85% of cases presenting as advanced disease and up to 40% of patients with metastatic disease.
In addition to tumor stage, age, sex, and performance status are independent prognostic factors for survival particularly in early-stage disease. Wheatley-Price et al reported on a retrospective pooled analysis of 2349 advanced NSCLC patients from 5 randomized chemotherapy trials (Wheatley-Price, 2010). Women had a higher response rate to platinum-based chemotherapy than men. Additionally, women with adenocarcinoma histology had greater overall survival than men. A small survival advantage exists for squamous cell carcinoma over non-bronchiolar nonsquamous histology (Chansky, 2009).
The oncology clinical care and research community use standard measures of performance status: Eastern Cooperative Oncology Group scale and Karnofsky Performance Scale.
Treatment approaches are multimodal and generally include surgery, radiotherapy, and chemotherapy (either alone or in combination with another treatment, depending on disease stage and tumor characteristics). Per the National Comprehensive Cancer Network (NCCN) guidelines, the clinical management pathway for stage I or II NSCLC is dependent on surgical findings and may involve resection, radiotherapy, chemotherapy, or chemoradiation. First-line chemotherapy regimens for neoadjuvant and adjuvant therapy utilize platinum-based agents (e.g., cisplatin, carboplatin) in combination with other chemotherapeutics and/or radiotherapy. Treatment recommendations are based on the overall health or performance status of the patient, presence or absence of metastases, as well as the presence or absence of a treatment-sensitizing genetic variant. These aspects inform the selection of targeted and systemic therapies (NCCN, 2022).
For patients who experience disease progression following initial systemic therapy, subsequent treatment regimens are recommended, mainly featuring novel programmed death-ligand 1 (PD-L1) inhibitors. The NCCN also includes recommendations for targeted therapy or immunotherapy in patients with biomarkers, including sensitizing epidermal growth factor receptor (EGFR) mutations. For patients with sensitizing EGFR mutations, recommendations include first-line therapy with EGFR tyrosine kinase inhibitors (TKIs) afatinib, erlotinib, dacomitinib, gefitinib, erlotinib plus ramucirumab, erlotinib plus bevacizumab (nonsquamous), or osimertinib and subsequent therapy with osimertinib. The NCCN does not make any recommendations for the use of EGFR TKIs in the absence of a confirmed sensitizing EGFR mutation. Initial systemic therapy recommendations can be considered for multiple, symptomatic, systemic lesions (NCCN, 2022).
Several common genetic alterations in NSCLC have been targets for drug therapy, the most well-established of which are TKIs targeting the EGFR and crizotinib targeting the anaplastic lymphoma kinase (ALK) gene rearrangement.
Epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (TK) frequently overexpressed and activated in NSCLC. Drugs that inhibit EGFR-signaling either prevent ligand-binding to the extracellular domain (monoclonal antibodies) or inhibit intracellular TK activity (small molecule TKIs). These targeted therapies dampen signal transduction through pathways downstream to the EGFR, such as the RAS/RAF/MAPK cascade. RAS proteins are G proteins that cycle between active and inactive forms in response to stimulation from cell surface receptors such as EGFR, acting as binary switches between cell surface EGFR and downstream signaling pathways. These pathways are important in cancer cell proliferation, invasion, metastasis, and the stimulation of neovascularization.
Variants 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. The prevalence of EGFR variants in NSCLC varies by population, with the highest prevalence in nonsmoking Asian women with adenocarcinoma; for that subpopulation, EGFR variants have been reported to as high as 30% to 50%. The reported prevalence of EGFR variants in lung adenocarcinoma patients in the U. S. is approximately 15% (Keedy, 2011).
For 2% to 7% of NSCLC patients in the U. S., tumors express a fusion gene comprising portions of the echinoderm microtubule-associated protein-like 4 (EML4) gene and the ALK gene (EML4-ALK), which is created by an inversion on chromosome 2p (Linderman, 2013). The EML4 fusion leads to ligand-independent activation of ALK, which encodes a receptor TK whose precise cellular function is not completely understood. EML4-ALK variants are more common in never smokers or light smokers, tend to be associated with younger age of NSCLC onset, and typically do not occur in conjunction with EGFR variants.
Testing for the EML4-ALK fusion gene in patients with adenocarcinoma-type NSCLC is used to predict response to the small molecule TKI crizotinib.
Other genetic variants, identified in subsets of patients with NSCLC, include KRAS, ALK, ROS1, RET, MET, BRAF, HER, and PIK3CA. The role of testing for these variants is to help select targeted therapies for NSCLC is less well-established than for EGFR variants.
The term proteome refers to the entire complement of proteins produced by an organism, or cellular system and proteomics refers to the large-scale comprehensive study of a specific proteome. The proteome may differ from cell to cell and may vary over time and in response to selected stressors.
A cancer cell’s proteome is related to its genome and genomic alterations. The proteome may be measured by mass spectrometry (MS) or protein microarray. For cancer, proteomic signatures in the tumor or bodily fluids (i.e., pleural fluid or blood) other than the tumor have been investigated as a biomarker for cancer activity.
A commercially available serum-based test (VeriStrat) has been developed and proposed to be used as a prognostic tool to predict expected survival for standard therapies used in the treatment of NSCLC. The test is also proposed to have predictive value for response to EGFR TKIs (Biodesix, 2019). The test uses matrix-assisted laser desorption ionization MS analysis, and a classification algorithm was developed on a training set of pretreatment sera from 3 cohorts (Italian A, Japan A, Japan B) totaling 139 patients with advanced NSCLC who were treated with second-line gefitinib (Taguchi, 2007). The classification result is either “good” or “poor". Two validation studies using pretreatment sera from 2 cohorts of patients (Italian B, Eastern Cooperative Oncology Group 3503) totaling 163 patients have been reported.
This assay uses an 8-peak proteomic signature; 4 of the 8 have been identified as fragments of serum amyloid A protein 1 (Keshtgarpour, 2016). This protein has been found to be elevated in individuals with a variety of conditions associated with acute and chronic inflammation (Wang, 2013; Santoso, 2013; Kotani, 2009; Bozinovski, 2012; Filippin-Monteiro, 2012). The specificity for malignant biologic processes and conditions has not been determined (Diamandis, 2004). With industry support, Fidler et al used convenience biorepository samples to investigate 102 analytes for potential correlations between the specific peptide and protein biomarkers and VeriStrat classification (Fidler, 2018). The VeriStrat test is currently marketed as a tool to measure a patient's "immune response to lung cancer." Biodesix indicates that a VeriStrat "Good" result indicates "a disease state that is more likely to respond to standard of care treatment," whereas a VeriStrat "Poor" rating indicates a chronic inflammatory disease state associated with aggressive cancer and patients that "may benefit from an alternative treatment strategy." The Biodesix website does not indicate whether the VeriStrat test should be reserved for use in patients with advanced lung cancer (Biodesix, 2019).
Although the VeriStrat matrix-assisted laser desorption ionization MS-based predictive algorithm has the largest body of literature associated with it, other investigators have used alternative MS methods, such as surface-enhanced laser desorption ionization/time-of-flight MS, and alternative predictive algorithms, to assess proteomic predictors of lung cancer risk (Jacot, 2008).
Best practices for peptide measurement and guidelines for publication of peptide and protein identification have been published for the research community (Abbatiello, 2017).
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. The commercially available proteomic test (VeriStrat®; Biodesix) is available under the Clinical Laboratory Improvement Amendments. Laboratories that offer laboratory-developed tests must be licensed by the Clinical Laboratory Improvement Amendments for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of these tests.
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
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Policy/ Coverage: |
Effective April 2022
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
The use of proteomic testing (e.g., VeriStrat® test) to predict response to cancer chemotherapy does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness.
For members with contracts without primary coverage criteria, the use of proteomic testing (e.g., VeriStrat® test) to predict response to cancer chemotherapy is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
Effective Prior to April 2022
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.
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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).
2019 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2019. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Buttigliero et al retrospectively examined VeriStrat as a prognostic and/or predictive test in a randomized controlled phase 3 RCT (MARQUEE trial) of previously treated patients with advanced nonsquamous NSCLC who were given erlotinib plus tivantinib or placebo (Buttigliero, 2018; Scagliotti, 2015). EGFR-variant status was not considered in trial eligibility, and patients previously treated with EGFR inhibitors were excluded from the trial. Of the 1048 patients assigned to treatment protocols, 976 (93%) patients discontinued treatment by protocol (duration of therapy, 0.1-92 weeks), which was discontinued for futility at an interim analysis. In this cohort, no significant difference was seen between the treatment arms for OS. Intention-to-treat analysis of VeriStrat pretreatment status was performed on data for 996 patients.
2020 Update
A literature search was conducted through March 2020. There was no new information identified that would prompt a change in the coverage statement.
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through March 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 March 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
In 2021, the American Society of Clinical Oncology updated its clinical practice guidelines to include recommendations for patients with stage IV NSCLC (Hanna, 2021; Hanna, 2020). Separate guidelines were published for patients with and without driver mutations. The guideline on treatment of NSCLC with driver mutations discusses treatments for patients with positive biomarkers (eg, EGFR, ALK, ROS1 fusions, BRAF V600e mutations, RET fusions, MET exon 14 skipping mutations, and NTRK fusions) (Hanna, 2021). The guideline on treatment of NSCLC without driver mutations discusses therapy for patients with stage IV NSCLC without driver alterations in EGFR or ALK and with programmed death ligand 1 (PD-L1) tumor proportion score status that is known to the clinician (Hanna, 2020).
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2023. No new literature was identified that would prompt a change in the coverage statement.
2024 Update
Annual policy review completed with a literature search using the MEDLINE database through March 2024. No new literature was identified that would prompt a change in the coverage statement.
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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. Abbatiello S, Ackermann BL, Borchers C, et al.(2017) New Guidelines for Publication of Manuscripts Describing Development and Application of Targeted Mass Spectrometry Measurements of Peptides and Proteins. Mol Cell Proteomics. Mar 2017; 16(3): 327-328. PMID 28183812 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 Biodesix.(2019) VeriStrat proteomic test. 2019; https://www.biodesix.com/products/lung-cancer/veristrat. Accessed November 9, 2021. Bozinovski S, Uddin M, Vlahos R, et al.(2012) Serum amyloid A opposes lipoxin A to mediate glucocorticoid refractory lung inflammation in chronic obstructive pulmonary disease. Proc Natl Acad Sci U S A. Jan 17 2012; 109(3): 935-40. PMID 22215599 Buttigliero C, Shepherd FA, Barlesi F, et al.(2018) Retrospective assessment of a serum proteomic test in a phase III study comparing erlotinib plus placebo with erlotinib plus tivantinib (MARQUEE) in previously treated patients with advanced non-small cell lung cancer. Oncologist. Aug 23 2018. PMID 30139835 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. 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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 Diamandis EP.(2004) Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. J Natl Cancer Inst. Mar 03 2004; 96(5): 353-6. PMID 14996856 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. Fidler MJ, Fhied CL, Roder J, et al.(2018) The serum-based VeriStrat(R) test is associated with proinflammatory reactants and clinical outcome in non-small cell lung cancer patients. BMC Cancer. Mar 20 2018; 18(1): 310. 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