Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data.
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
Carcinoma, Non-Small-Cell Lung; ErbB Receptors; Humans; Lung Neoplasms; Mutation; Survival Analysis; washington; swedish cancer
BACKGROUND: Somatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches.
METHODS: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-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 EGFR-status.
RESULTS: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-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 EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients.
CONCLUSIONS: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC.
IMPACT: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.
Schmid, Sabine; Jiang, Mei; Brown, M Catherine; Fares, Aline; Garcia, Miguel; Soriano, Joelle; Dong, Mei; Thomas, Sera; Kohno, Takashi; Leal, Leticia Ferro; Diao, Nancy; Xie, Juntao; Wang, Zhichao; Zaridze, David; Holcatova, Ivana; Lissowska, Jolanta; Świątkowska, Beata; Mates, Dana; Savic, Milan; Wenzlaff, Angela S; Harris, Curtis C; Caporaso, Neil E; Ma, Hongxia; Fernandez-Tardon, Guillermo; Barnett, Matthew J; Goodman, Gary E; Davies, Michael P A; Pérez-Ríos, Mónica; Taylor, Fiona; Duell, Eric J; Schoettker, Ben; Brenner, Hermann; Andrew, Angeline; Cox, Angela; Ruano-Ravina, Alberto; Field, John K; Marchand, Loic Le; Wang, Ying; Chen, Chu; Tardon, Adonina; Shete, Sanjay; Schabath, Matthew B; Shen, Hongbing; Landi, Maria Teresa; Ryan, Brid M; Schwartz, Ann G; Qi, Lihong; Sakoda, Lori C; Brennan, Paul; Yang, Ping; Zhang, Jie; Christiani, David C; Reis, Rui Manuel; Shiraishi, Kouya; Hung, Rayjean J; Xu, Wei; and Liu, Geoffrey, "Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data." (2022). Articles, Abstracts, and Reports. 6069.