Objectives: VeriStrat is a blood-based test that utilizes matrix-assisted laser desorption/ionization time-of-flight (MALDI ToF) mass spectrometry to assign a binary classification of VeriStrat Good or VeriStrat Poor that is associated with treatment outcomes in cancer patients. A number of other studies have shown an association between VeriStrat status and clinical outcomes in second and subsequent lines of therapy. The prognostic properties of VeriStrat were demonstrated in the placebo arms of two randomized studies in non-small cell lung cancer (NSCLC): TOPICAL and BR.21; the predictive properties of the test were shown in a prospective randomized phase III study PROSE in the second line treatment of NSCLC with erlotinib versus chemotherapy. Motivated by these observations, we sought to extend the clinical utility of VeriStrat to standard first line chemotherapy and evaluated the performance of the test in a number of clinical studies of patients treated with platinum-based regimens.

Materials And Methods: We examine the performance of VeriStrat in three independent clinical trials where the test classification was acquired for prospectively collected baseline samples from 481 patients treated with platinum-based chemotherapy in first line.

Results: Across these trials, 66-70% of patients were classified as VeriStrat Good; patients classified as VeriStrat Good had significantly longer progression-free survival and overall survival than VeriStrat Poor patients, with hazard ratios ranging from 0.36 to 0.72 and 0.26 to 0.51, respectively. These results demonstrated that VeriStrat is a strong prognostic test in NSCLC patients treated with platinum-based regimens in the first line.

Conclusion: VeriStrat provides valuable clinical information that may be used to support patient-physician conversations regarding prognosis and treatment options, and to identify a subset of patients who might benefit from other treatment strategies, possibly in the framework of clinical trials.

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http://dx.doi.org/10.1016/j.lungcan.2017.12.007DOI Listing

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