Wong, William B

Abstract Advances in genetic technology have led to the increasing use of genomic panels in precision oncology practice, with panels ranging from a couple to hundreds of genes. However, the clinical utilization and utility of oncology genomic panels, especially among vulnerable populations, is unclear. We examined the association of panel size with socioeconomic status and clinical trial matching. We retrospectively identified 9,886 eligible adult subjects in the Mayo Clinic Health System who underwent genomic testing between January 1, 2016 and June 30, 2020. Patient data were retrieved from structured and unstructured data sources of institutional collections, including cancer registries, clinical data warehouses, and clinical notes. Socioeconomic surrogates were approximated using the Area Deprivation Index (ADI) corresponding to primary residence addresses. Logistic regression was performed to analyze relationships between ADI or rural/urban status and (i) use of genomic test by panel size; (ii) clinical trial matching status. Compared with patients from the most affluent areas, patients had a lower odds of receiving a panel test (vs. a single-gene test) if from areas of higher socioeconomic deprivation [OR (95% confidence interval (CI): 0.71 (0.61–0.83), P < 0.01] or a rural area [OR (95% CI): 0.85 (0.76–0.96), P < 0.01]. Patients in areas of higher socioeconomic deprivation were less likely to be matched to clinical trials if receiving medium panel tests [(OR) (95% CI): 0.69 (0.49–0.97), P = 0.03]; however, there was no difference among patients receiving large panel tests (P > 0.05) and rural patients were almost 2x greater odds of being matched if receiving a large panel test [(OR) (95% CI): 1.76 (1.21–2.55), P < 0.01]. Significance: We identified socioeconomic and rurality disparities in the use of genomic tests and trial matching by panel size, which may have implications for equal access to targeted therapies. The lack of association between large panel tests and clinical trial matching by socioeconomic status, suggests a potential health equity impact, while removing barriers in access to large panels for rural patients may improve access to trials. However, further research is needed.

e18321 Background: Despite the availability of targeted therapy for ROS1 NSCLC since 2016, there is limited information on real-world ROS1 testing practices to identify patients potentially eligible for targeted treatment among community practices. The objective of this study was to characterize ROS1 testing rates and identify potential barriers to ROS1 testing. Methods: The Flatiron Health EHR-derived database was used to identify patients diagnosed with advanced NSCLC between 7/1/2016 - 7/30/2018 and received systemic treatment in a community practice setting. Descriptive statistics were used to summarize the population, biomarker testing rates and timing of testing. Logistic and multinomial regressions including patient demographics and clinical characteristics were used to identify factors associated with the following outcomes: ROS1 testing, testing for biomarkers other than ROS1 (PDL1, ALK, EGFR) , longer times from advanced diagnosis (adv. dx) to ROS1 test results and initiation of therapy prior to ROS1 testing. Results: Of 9,275 eligible patients, ROS1 testing rates in squamous (SQ) and non-squamous histologies increased over the study period (30% to 52%, 62% to 75% respectively). Older age, males, poorer performance status, SQ histology, history of smoking and recurrent disease (RD) patients were significantly less likely to be tested. Among patients not tested for ROS1, 62% were tested for other biomarkers including > 50% of non-squamous patients tested for PDL1, EGFR or ALK and 51% of squamous patients tested for PDL1. The median time from adv. dx to test result was 24 days, with patient characteristics (i.e. Hispanic ethnicity, history of smoking) as well as test type predicting longer times to test results ( > 41 days vs. < 24 days after adv. dx). Patients who had a delay in test results were more likely to receive other therapy prior to availability of their ROS1 test results (25+ days vs. < 24 days OR [95% CI]: 9.18 [7.87, 10.70]). Conclusions: In real-world practice, patient characteristics were associated with ROS1 testing and testing delays which may result in some patient subgroups being less likely to be identified for potential targeted therapy.

e18240 Background: The time between a patient’s positive biomarker test result and initiation of targeted therapy may vary due to a number of factors, including the use of chemotherapy prior to or after the biomarker test result. The objective of this study was two-fold: first, to investigate the impact of delayed ALK inhibitor (ALKi) therapy on overall survival (OS) and second, to examine the association between the use of chemotherapy prior to or after biomarker testing and OS. Methods: The Flatiron Health EHR-derived database was used to identify patients with ALK-positive (ALK+) advanced NSCLC diagnosed between 1/1/2011 - 9/30/2018. The median time from ALK+ test result to ALKi start was used to separate patients into early versus delayed treatment cohorts. To account for potential immortal time bias, times from ALK+ test result to ALKi start from the delayed cohort were sampled with replacement and used to create modified index dates among the early cohort. Cox proportional hazards models adjusting for baseline characteristics (i.e. ECOG) were used to assess the association between delayed ALKi start and OS and the use of chemotherapy with OS. Results: 422 patients with ALK+ aNSCLC were included in this analysis with a median time from test result to ALKi start of 3 weeks. 88 patients (20.9%) received chemotherapy prior to starting their ALKi. Delayed ALKi use was associated with a 2.3 fold increase in risk of mortality (HR [95% CI]: 2.30 [1.28, 4.15], p < 0.01). There was no difference in survival observed between those who had received chemotherapy prior to initiating their ALKi and those who did not receive chemotherapy (HR [95% CI]: 0.99 [0.62, 1.58]). Among those who initiated chemotherapy prior to their ALK+ test result, the continued use of chemotherapy prior to initiating an ALKi did not result in differences in OS compared to those who switched to an ALKi without continuing chemotherapy (HR [95% CI]: 1.03 [0.44, 2.41]). Conclusions: Delayed initiation of ALKi may result in poor outcomes in patients with ALK+ NSCLC. Receipt of chemotherapy prior to ALKi or the duration of chemotherapy did not impact survival. Future strategies to improve the time to therapy initiation may be useful in improving patient outcomes.