Accounting for EGFR mutations in epidemiological analyses of non-small cell lung cancers: Examples based on the International Lung Cancer Consortium data.



Schmid, Sabine, Jiang, Mei, Brown, M Catherine, Fares, Aline, Garcia, Miguel, Soriano, Joelle, Dong, Mei, Thomas, Sera, Kohno, Takashi, Ferro Leal, Leticia
et al (show 47 more authors) (2022) Accounting for EGFR mutations in epidemiological 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.

[img] Text
Accounting for EGFR mutations in epidemiological analyses of non-small cell lung cancers- Examples based on the International Lung Cancer Consortium data -Final word versuon.pdf - Accepted Version
Access to this file is embargoed until 13 January 2023.

Download (485kB)

Abstract

<h4>Introduction</h4>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 epidemiological datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiological datasets and evaluated the clinical utility of these approaches.<h4>Methods</h4>Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiological datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cutpoint, and a second epidemiological, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status.<h4>Results</h4>Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4231 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 NSCLC patients, 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.<h4>Conclusion</h4>We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC.<h4>Impact</h4>The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

Item Type: Article
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 26 Jan 2022 11:44
Last Modified: 07 Sep 2022 11:52
DOI: 10.1158/1055-9965.epi-21-0747
URI: https://livrepository.liverpool.ac.uk/id/eprint/3147625