Real-World Biomarker Test Ordering Practices in Non-Small Cell Lung Cancer: Interphysician Variation and Association With Clinical Outcomes.

Abstract

Purpose: Patients with metastatic or advanced non-small cell lung cancer (NSCLC) need biomarker testing, including, in most cases, anaplastic lymphoma kinase (ALK), epidermal growth factor receptor (EGFR), and PD-L1, to identify options for targeted therapies and to optimally incorporate immune checkpoint inhibitors into therapeutic regimens. We sought to examine real-world patterns of biomarker testing, quantify interphysician practice variation, and correlate testing with clinical outcomes.

Methods: We extracted real-world data from a nationwide electronic health record-derived deidentified database from 17,165 patients diagnosed with advanced NSCLC between 2018 and 2021 and receiving care in the community setting. We analyzed data using descriptive analyses, fixed- and mixed-effects logistic regression models, and proportional hazard models.

Results: Only 67% of all 17,165 patients and 77% of patients with nonsquamous, metastatic NSCLC had ALK, EGFR, and PD-L1 testing within 90 days of diagnosis. Later diagnosis year (2019-2021 compared with 2018) was associated with higher rates of ALK, EGFR, and PD-L1 testing; stage IIIB/C disease (compared with stage IV), squamous histology, and Black or African American race were associated with lower rates. Interphysician variation was substantial with a median odds ratio between physicians (adjusted for patient factors) of 1.78 for ALK, EGFR, and PD-L1 testing. Patients with nonsquamous, metastatic NSCLC had significantly prolonged survival if tested with all three biomarkers (median, 364 days for all three v 180 for none of the three; hazard ratio, 0.67; P < .001).

Conclusion: Rates of biomarker testing appear suboptimal with substantial interphysician variation. Testing correlates with improved survival, although causality cannot be proven from this study. Additional work is needed to address the underlying causes of suboptimal test ordering.