Association Between Clinical Outcomes and Patient Characteristics/Genomic Profiles in Lung Cancer
As reported in JAMA, Singal et al used a clinicogenomic database in routine clinical practice to identify associations between treatment outcomes and patient characteristics or tumor genomic profiles in the setting of non–small cell lung cancer (NSCLC).
The study cohort of 4,064 patients with NSCLC was derived by linking an electronic health records (EHRs) database with a comprehensive genomic profiling (CPG) database of tumor-sequencing results. Among the patients with NSCLC, exploratory analysis of associations between tumor genomics and patient characteristics with clinical outcomes was performed using data from January 2011 to January 2018.
Characteristics and Outcomes
Among the 4,064 patients with NSCLC, the median age was 66.0 years; 51.9% were female; 78.3% had a history of smoking; 77.6% had nonsquamous cancer; and 21.4% had an alteration in EGFR (17.2%), ALK (3.1%), or ROS1 (1.0%). Over 7 years, there were 1,946 deaths. Among patients with a driver alteration, those treated with (n = 575) vs not treated with (n = 560) targeted therapy had improved overall survival (median = 18.6 months vs 11.4 months from advanced diagnosis; P < .001).
Tumor mutational burden (TMB) was higher among smokers vs nonsmokers (8.7 vs 2.6, P < .001) and lower among patients with vs without an alteration in EGFR (3.5 vs 7.8, P < .001), ALK (2.1 vs 7.0, P < .001), RET (4.6 vs 7.0, P = .004), or ROS1 (4.0 vs 7.0, P = .03).
Among 1,290 patients (31.7% of cohort) treated with anti–programmed cell death protein 1/anti–programmed death ligand 1 (PD-1/PD-L1) therapies, TMB of ≥ 20 vs < 20 was significantly associated with improved overall survival from therapy initiation (median = 16.8 months vs 8.5 months, P < .001), longer duration of therapy (median = 7.8 months vs 3.3 months, P < .001), and a higher clinical benefit rate (80.7% vs 56.7%, P < .001).
The investigators concluded, “Among patients with NSCLC included in a longitudinal database of clinical data linked to [comprehensive genomic profiling] results from routine care, exploratory analyses replicated previously described associations between clinical and genomic characteristics, between driver mutations and response to targeted therapy, and between TMB and response to immunotherapy. These findings demonstrate the feasibility of creating a clinicogenomic database derived from routine clinical experience and provide support for further research and discovery evaluating this approach in oncology.”
Gaurav Singal, MD, of Foundation Medicine, Inc, is the corresponding author for the JAMA article.
Disclosure: The study was funded by Flatiron Health and Foundation Medicine. For full disclosures of the study authors, visit jamanetwork.com.
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