P3.01-36 Prognostic Factors in Elderly Patients with Advanced Non-Small Cell Lung Cancer

M Honorio,N Guerra Pereira,A Tereso,M.A Almeida

doi:10.1016/j.jtho.2018.08.1596

M Honorio, N Guerra Pereira + Show 2 more

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https://doi.org/10.1016/j.jtho.2018.08.1596

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Abstract

There is no consensus method for identifying frail older patients. A number of clinical screening tests are now available but the prediction of outcome of treatment is difficult. Sarcopenia, as simply determined by a baseline Computed Tomography (CT) image, has been shown to be predictive of prognosis in Lung Cancer (LC). The purpose of this analysis was to determine the prognostic significance of CT determined sarcopenia, and other clinical parameters, on overall survival (OS) among elderly patients with advanced-stage Non-Small Cell Lung Cancer (NSCLC) and on active treatment. We also sought to determine the OS of this population, according to the different clinical parameters evaluated. A retrospective analysis of 77 patients older than 65 years old with advanced NSCLC and ECOG PS 0-2 treated between 2014 and 2017 was performed. The variables tested were age, gender, ECOG PS, polypharmacy (the use of 5 or more medications), The Charlson Comorbidity Index (CCI), Body Mass Index (BMI), Lactate dehydrogenase value and sarcopenia. For the quantification of Sarcopenia two methods were used: Total Psoas Index (TPI) and the Hounsfield Unit Calculation (HUAC). Both obtained from a single axial Computed Tomography (CT) image at L3 level. Median OS was assessed by Kaplan-Meier method. Cox survival analysis was performed for a 95% CI for the hazard ratios, considering a p value of 0.05 as an indicator of statistical significance. Analyses were performed with use of SPSS v.18 software. On our population we found sex, CCI and polypharmacy as independent risk factors associated with mortality. Median OS of the population was 14 months. Men and patients who presented with ECOG PS 2, BMI below 22 Kg/m2 and sarcopenia had worse outcome, but without statistical significance. Clinical variables may help to discuss prognosis with elderly LC patients. The identification of these factors can be used to improve patient selection for the different treatment options.

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