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Clinical Trial
. 2015 Jul 15;21(14):3196-203.
doi: 10.1158/1078-0432.CCR-14-2594. Epub 2015 Mar 31.

Detection and Dynamic Changes of EGFR Mutations from Circulating Tumor DNA as a Predictor of Survival Outcomes in NSCLC Patients Treated with First-line Intercalated Erlotinib and Chemotherapy

Affiliations
Clinical Trial

Detection and Dynamic Changes of EGFR Mutations from Circulating Tumor DNA as a Predictor of Survival Outcomes in NSCLC Patients Treated with First-line Intercalated Erlotinib and Chemotherapy

Tony Mok et al. Clin Cancer Res. .

Abstract

Purpose: Blood-based circulating-free (cf) tumor DNA may be an alternative to tissue-based EGFR mutation testing in NSCLC. This exploratory analysis compares matched tumor and blood samples from the FASTACT-2 study.

Experimental design: Patients were randomized to receive six cycles of gemcitabine/platinum plus sequential erlotinib or placebo. EGFR mutation testing was performed using the cobas tissue test and the cobas blood test (in development). Blood samples at baseline, cycle 3, and progression were assessed for blood test detection rate, sensitivity, and specificity; concordance with matched tumor analysis (n = 238), and correlation with progression-free survival (PFS) and overall survival (OS).

Results: Concordance between tissue and blood tests was 88%, with blood test sensitivity of 75% and a specificity of 96%. Median PFS was 13.1 versus 6.0 months for erlotinib and placebo, respectively, for those with baseline EGFR mut(+) cfDNA [HR, 0.22; 95% confidence intervals (CI), 0.14-0.33, P < 0.0001] and 6.2 versus 6.1 months, respectively, for the EGFR mut(-) cfDNA subgroup (HR, 0.83; 95% CI, 0.65-1.04, P = 0.1076). For patients with EGFR mut(+) cfDNA at baseline, median PFS was 7.2 versus 12.0 months for cycle 3 EGFR mut(+) cfDNA versus cycle 3 EGFR mut(-) patients, respectively (HR, 0.32; 95% CI, 0.21-0.48, P < 0.0001); median OS by cycle 3 status was 18.2 and 31.9 months, respectively (HR, 0.51; 95% CI, 0.31-0.84, P = 0.0066).

Conclusions: Blood-based EGFR mutation analysis is relatively sensitive and highly specific. Dynamic changes in cfDNA EGFR mutation status relative to baseline may predict clinical outcomes.

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