Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non–Small Cell Lung Cancer Using a Clinicogenomic Database

Gaurav Singal(Brigham and Women's Hospital), Peter G. Miller(Dana-Farber Cancer Institute), Vineeta Agarwala(Flatiron Health (United States)), Gerald Li(Foundation Medicine (United States)), Gaurav Kaushik(Foundation Medicine (United States)), Daniel Backenroth(Flatiron Health (United States)), Anala Gossai(Flatiron Health (United States)), Garrett M. Frampton(Foundation Medicine (United States)), Aracelis Z. Torres(Flatiron Health (United States)), Erik Lehnert(Foundation Medicine (United States)), David Bourque(Foundation Medicine (United States)), Claire O’Connell(Flatiron Health (United States)), Bryan Bowser(Flatiron Health (United States)), Thomas Caron(Flatiron Health (United States)), Ezra Baydur(Flatiron Health (United States)), Kathi Seidl-Rathkopf(Flatiron Health (United States)), Ivan Ivanov(Flatiron Health (United States)), Garrett Alpha-Cobb(Foundation Medicine (United States)), Ameet Guria(Foundation Medicine (United States)), Jie He(Foundation Medicine (United States)), Shannon Frank(Flatiron Health (United States)), Allen C. Nunnally(Voyager Therapeutics (United States)), Mark Bailey(Foundation Medicine (United States)), Ann Jaskiw(Flatiron Health (United States)), Dana Feuchtbaum(Flatiron Health (United States)), Nathan C. Nussbaum(New York University), Amy P. Abernethy(Flatiron Health (United States)), Vincent A. Miller(Foundation Medicine (United States))
JAMA
April 9, 2019
Cited by 563Open Access
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Abstract

Importance: Data sets linking comprehensive genomic profiling (CGP) to clinical outcomes may accelerate precision medicine. Objective: To assess whether a database that combines EHR-derived clinical data with CGP can identify and extend associations in non-small cell lung cancer (NSCLC). Design, Setting, and Participants: Clinical data from EHRs were linked with CGP results for 28 998 patients from 275 US oncology practices. Among 4064 patients with NSCLC, exploratory associations between tumor genomics and patient characteristics with clinical outcomes were conducted, with data obtained between January 1, 2011, and January 1, 2018. Exposures: Tumor CGP, including presence of a driver alteration (a pathogenic or likely pathogenic alteration in a gene shown to drive tumor growth); tumor mutation burden (TMB), defined as the number of mutations per megabase; and clinical characteristics gathered from EHRs. Main Outcomes and Measures: Overall survival (OS), time receiving therapy, maximal therapy response (as documented by the treating physician in the EHR), and clinical benefit rate (fraction of patients with stable disease, partial response, or complete response) to therapy. Results: Among 4064 patients with NSCLC (median age, 66.0 years; 51.9% female), 3183 (78.3%) had a history of smoking, 3153 (77.6%) had nonsquamous cancer, and 871 (21.4%) had an alteration in EGFR, ALK, or ROS1 (701 [17.2%] with EGFR, 128 [3.1%] with ALK, and 42 [1.0%] with ROS1 alterations). There were 1946 deaths in 7 years. For patients with a driver alteration, improved OS was observed among those treated with (n = 575) vs not treated with (n = 560) targeted therapies (median, 18.6 months [95% CI, 15.2-21.7] vs 11.4 months [95% CI, 9.7-12.5] from advanced diagnosis; P < .001). TMB (in mutations/Mb) was significantly higher among smokers vs nonsmokers (8.7 [IQR, 4.4-14.8] vs 2.6 [IQR, 1.7-5.2]; P < .001) and significantly lower among patients with vs without an alteration in EGFR (3.5 [IQR, 1.76-6.1] vs 7.8 [IQR, 3.5-13.9]; P < .001), ALK (2.1 [IQR, 0.9-4.0] vs 7.0 [IQR, 3.5-13.0]; P < .001), RET (4.6 [IQR, 1.7-8.7] vs 7.0 [IQR, 2.6-13.0]; P = .004), or ROS1 (4.0 [IQR, 1.2-9.6] vs 7.0 [IQR, 2.6-13.0]; P = .03). In patients treated with anti-PD-1/PD-L1 therapies (n = 1290, 31.7%), TMB of 20 or more was significantly associated with improved OS from therapy initiation (16.8 months [95% CI, 11.6-24.9] vs 8.5 months [95% CI, 7.6-9.7]; P < .001), longer time receiving therapy (7.8 months [95% CI, 5.5-11.1] vs 3.3 months [95% CI, 2.8-3.7]; P < .001), and increased clinical benefit rate (80.7% vs 56.7%; P < .001) vs TMB less than 20. Conclusions and Relevance: Among patients with NSCLC included in a longitudinal database of clinical data linked to CGP 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.


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