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Clinical Epidemiology and Ageing

Prognostic role of a comprehensive geriatric assessment on the management of elderly patients with advanced non-small cell lung cancer (NSCLC): a pooled analysis of two prospective phase II trials by the GFPC Group.

Le Caer H, Borget I, Corre R, Locher C, Raynaud C, Decroisette C, Bérard H, Audigier-Valette C, Dujon C, Auliac JBernard, Crequit J, Monnet I, Vergnenègre A, Chouaid C J Thorac Dis. 2017;9(10):3747-3754.

Background: The prognostic role of a comprehensive geriatric assessment (CGA) on the management of elderly patients with advanced-stage non-small cell lung cancer (NSCLC) remains to be established. The objective of this analysis was to determine the prognostic role of each CGA domain on overall survival (OS) among elderly patients with advanced-stage NSCLC.

Methods: We pooled individual data from two prospective, randomized phases II trials in patients over 65 years old with advanced-stage NSCLC, who were considered fit (0405 trial) or no-fit (0505 trial) based on a CGA. Both trials compared first-line chemotherapy followed by second-line erlotinib with the reverse strategy in terms of progression-free survival (PFS) and OS. Factors prognostic of OS were sought by using the Kaplan-Meier method and the log rank test for univariate analysis, and a Cox model for multivariate analysis.

Results: Analysis performed on 194 patients (mean age: 77 years, male gender: 70%, never- or ex-smokers: 56%) showed, in univariate analysis that performance status (PS), smoking status, Charlson, simplified Charlson, nutritional scores, and a mobility score were prognostics of OS. In multivariate analysis, PS [HR: 1.4 (1.02-1.9), P=0.04] and the Charlson score [HR: 1.46 (1.07-1.99), P=0.02] were independently prognostic of OS, while the nutritional score [HR: 0.69 (0.46-1.04), P=0.07] and the mobility score [HR: 0.25 (0.06-1.01), P=0.06] were close to significance.

Conclusions: PS and comorbidities appear to be the main predictors of OS in elderly advanced NSCLC patients selected on the basis of CGA.

DOI: 10.21037/jtd.2017.09.51

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