Racial and Ethnic Inequities at the Practice and Physician Levels in Timely Next-Generation Sequencing for Patients With Advanced Non-Small-Cell Lung Cancer Treated in the US Community Setting.

PURPOSE: Racial/ethnic inequities in next-generation sequencing (NGS) were examined for patients with advanced non-small-cell lung cancer (aNSCLC) at the practice and physician levels to inform policies to improve equitable quality of care.

METHODS: This retrospective study used a nationwide electronic health record-derived deidentified database for patients with aNSCLC diagnosed between April 2018 and March 2022 in the community setting. Timely NGS was an NGS result between initial diagnosis and ≤60 days after advanced diagnosis. We studied how inequities were driven by (1) non-Latinx Black (Black) and Latinx patient under-representation at high testing practices versus (2) Black and Latinx patients being tested at lower rates than non-Latinx White (White) patients, even at the same practice. We defined these two concepts as across inequity and within inequity, respectively, with total inequity as their summation. Mean percentage point inequities were estimated using a Bayesian approach.

RESULTS: A total of 12,045 patients (9,981 White; 1,528 Black; 536 Latinx) met study criteria. At the practice level, versus White patients, the mean percentage point difference in NGS testing total inequity was 7.49 for Black and 8.26 for Latinx. Within- and across-practice inequities contributed to total inequity in NGS testing for Black (48% v 52%) and Latinx patients (60% v 40%). At the physician level, versus White patients, the mean percentage point difference in total inequity was 7.73 for Black and 8.81 for Latinx patients. Within- versus across-physician inequities contributed to total inequity for Black and Latinx patients (77% v 23% and 67% v 33%).

CONCLUSION: Within-practice, across-practice, and across-physician inequities were main contributors to total inequity in NGS testing, requiring a suite of interventions to effectively address inequities.