Data from Accounting for <i>EGFR</i> Mutations in Epidemiologic Analyses of Non–Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data — Sabine Schmid (2025) | RDL Network
Data from Accounting for <i>EGFR</i> Mutations in Epidemiologic Analyses of Non–Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data
Article 2025
Authors
SS
Sabine Schmid
MJ
Mei Jiang
MB
M. Catherine Brown
Abstract
1 min read
<div>AbstractBackground:<p>Somatic <i>EGFR</i> mutations define a subset of non–small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, <i>EGFR</i>-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for <i>EGFR</i>-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches.</p>Methods:<p>Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for <i>EGFR</i>-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for <i>EGFR</i>-status.</p>Results:<p>Of 35,356 ILCCO patients with NSCLC, <i>EGFR</i>-mutation-status was available in 4,231 patients. A model regressing known <i>EGFR</i>-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74–0.77) in the training and 0.77 (95% CI, 0.74–0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and <i>EGFR</i>-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: <i>EGFR</i>-mutated Asian patients did not incur a survival benefit from being obese, as observed in <i>EGFR</i>-wildtype Asian patients.</p>Conclusions:<p>We introduce a pragmatic method to evaluate the potential impact of <i>EGFR</i>-status on epidemiological analyses of NSCLC.</p>Impact:<p>The proposed method is generalizable in the common occurrence in which <i>EGFR</i>-status data are missing.</p></div>
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