Table S2: Demographics of the 97 NSCLC patients treated at UCLA on KEYNOTE-001 (N=97) compared with the demographics of the total KEYNOTE-001 study population (n=495). Of note, the UCLA cohort of 97 patients is included in the total KEYNOTE-001 study population of 495 patients.
ARTICLE ABSTRACT
We retrospectively analyzed non–small cell lung cancer (NSCLC) patients from a single center treated with pembrolizumab on the KEYNOTE-001 trial and evaluated the association between treatment-related adverse events (trAEs) and clinical outcomes. Investigators reported AEs on trial and graded them according to Common Terminology Criteria for Adverse Events v4.0, labeling them as unlikely, possibly, or probably treatment-related. AEs labeled as possibly/probably related were considered trAEs for this analysis. The relationship between the incidence of a trAE and clinical outcomes was evaluated. Ninety-seven NSCLC patients treated on KEYNOTE-001 at the University of California, Los Angeles were evaluated. Ten percent (85/826) of AEs were trAEs, occurring in 40% (39/97) of patients. The most frequent trAEs were rash (21% patients), fatigue (6% patients), and hypothyroidism (6% patients). The 39 patients that experienced a trAE had increased objective response rate (ORR, 38.5%), progression-free survival (PFS: median, 248 days), and overall survival (OS: median, 493 days), compared with the 58 patients that did not (ORR: 8.9%, PFS: median 60 days, OS: median 144.5 days). The observed association between trAEs and improved clinical outcome persisted when using Cox proportional hazards regression models to assess the confounding effect of covariates and mitigate guarantee-time bias. The association also remained when data were substratified by grade, degree of association, and treatment-related select AE designation. This single-center analysis revealed that trAEs predicted for improved clinical outcome with pembrolizumab, and when controlling for guarantee-time bias and plausible confounders, this association remained. This observed relationship adds to our understanding of anti–PD-1 therapy and could aid clinicians in identifying patients most likely to benefit from therapy. Cancer Immunol Res; 6(3); 288–94. ©2018 AACR.
