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 MEASURESOverall 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,] 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,] 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 der...

Anti-PD-1 agents rapidly reached patients in clinical practice, and patients treated in clinical practice differed significantly from patients treated in pivotal clinical trials. Future actions are needed to ensure that rapid adoption occurs on the basis of representative trial evidence.

Amid growing excitement for immune checkpoint inhibitors of programmed death protein 1 (anti-PD1 agents), little is known about whether race- or sex-based disparities exist in their use. In this observational study, we constructed a large and mostly community-based cohort of patients with advanced stage cancers, including melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma, to compare the odds of receiving systemic treatment with or without anti-PD1 agents by race and by sex. In multivariable models that adjusted for age, stage, and number of prior anticancer therapies, we found no significant race-based disparities in anti-PD1 treatment. However, among patients with NSCLC, males had significantly higher odds of receiving anti-PD1 treatment compared with females (odds ratio 1.13, 95% confidence interval 1.02-1.24, = .02). This finding suggests that as anti-PD1 agents enter the market to transform patient care, it will be critical to monitor for disparities in the use of these drugs.

2514 Background: Genomic findings have diagnostic, prognostic, and predictive utility in clinical oncology. Population studies have been limited by reliance on trials, registries, or institutional chart review, which are costly and represent narrow populations. Integrating electronic health record (EHR) and genomic data collected as part of routine clinical practice may overcome these hurdles. Methods: Patients in the Flatiron Health Database with non-small cell lung cancer (NSCLC) who underwent comprehensive genomic profiling (CGP) by Foundation Medicine were included. EHR processing included structured data harmonization and abstraction of variables from unstructured documents. EHR and CGP data were de-identified and linked in a HIPAA-compliant process. Data included clinical characteristics, alterations across > 300 genes, tumor mutation burden (TMB), therapies and associated real-world responses, progression, and overall survival (OS). Results: The cohort (n = 1619) had expected clinical (mean age 66; 75% with smoking hx; 80% non-squamous) and genomic (18% EGFR; 4% ALK; 1% ROS1) properties of NSCLC. Presence of a driver mutation (EGFR, ALK, ROS1, MET, BRAF, RET, or ERBB2; n = 576) was associated with younger age, female gender, non-smoking, improved OS (35 vs 19 mo, LR p < 0.0001), and prolonged survival when treated with NCCN-recommended therapy (42 vs 28 mo, LR p = 0.001). CGP identified false negative results in up to 30% of single-biomarker tests for EGFR, ALK, and ROS1. CGP accuracy was supported by clinical outcomes. For example, 5 patients with prior negative ALK-fusion testing began ALK-directed therapy after positive CGP results. All 5 exhibited at least a partial response as recorded in the EHR by treating clinicians. Immunotherapy was used in 22% of patients (n = 353). TMB predicted response to nivolumab, including in PD-L1 negative populations. We recapitulated known associations with smoking, histology, and driver mutations. Conclusions: We present and validate a new paradigm for rapidly generating large, research-grade, longitudinal clinico-genomic databases by linking genomic data with EHR clinical annotation. This method offers a powerful tool for understanding cancer genomics and advancing precision medicine.

3068 Background: There are concerns about racial disparities in access to trials of new cancer drugs, including the programmed death 1 checkpoint inhibitors (anti-PD1s). It is unknown whether these disparities extend to anti-PD1 treated patients in real-world practice. Methods: We used retrospective data from Flatiron Health’s electronic health record database, which includes more than 250 cancer clinics and 1.5 million patients with cancer. We identified patients diagnosed after January 1, 2011 who underwent systemic therapy for: advanced non-small cell lung cancer (aNSCLC; n = 13,473), metastatic renal cell carcinoma (mRCC; n = 1,537), and advanced melanoma (n = 1,221). Within each cohort, we identified treatment type (anti-PD1 versus non-anti-PD1). Therapy lines containing study drugs were excluded. We used logistic regressions to model the use of anti-PD1s by race, adjusting for factors such as age, sex, stage at diagnosis and line of therapy. Results: Of 16,231 patients in our sample, 4,643 (28.6%) were treated with anti-PD1s. Racial distributions differed for anti-PD1 treated patients compared to non-anti-PD1 treated patients in the aNSCLC cohort (Table: p < 0.01), but not in the mRCC cohort (p = 0.84) or the advanced melanoma cohort (p = 0.96). In bivariate analyses of patients with aNSCLC, anti-PD1 treatment was associated with other race, male sex, stage II at diagnosis, squamous histology, smoking history and line of therapy (all p < 0.05). Adjusted models showed there were no significant differences in likelihood of receiving anti-PD1s when comparing black and white patients undergoing systemic therapy for aNSCLC (aOR for black vs. white: 0.86, 95% CI 0.72-1.02), mRCC (aOR 0.90, 95% CI 0.53-1.49), or melanoma (aOR 2.02, 95% CI 0.42-14.59). Conclusions: Among patients undergoing systemic therapy in a large national network of cancer clinics, we found no significant racial disparities in the use of anti-PD1s. [Table: see text]