Identification of comprehensive geriatric assessment based risk factors for malnutrition in elderly Asian cancer patients

Abstract

Purpose: Elderly cancer patients are at increased risk for malnutrition. We aim to identify comprehensive geriatric assessment (CGA) based clinical factors associated with increased nutritional risk and develop a clinical scoring system to identify nutritional risk in elderly cancer patients. Patients and Methods: CGA data was collected from 249 Asian patients aged 70 years or older. Nutritional risk was assessed based on the Nutrition Screening Initiative (NSI) checklist. Univariate and multivariate logistic regression analyses were applied to assess the association between patient clinical factors together with domains within the CGA and moderate to high nutritional risk. Goodness of fit was assessed using Hosmer-Lemeshow test. Discrimination ability was assessed based on the area under the receiver operating characteristics curve (AUC). Internal validation was performed using simulated datasets via bootstrapping. Results: Among the 249 patients, 184 (74%) had moderate to high nutritional risk. Multivariate logistic regression analysis identified stage 3-4 disease (Odds Ratio [OR] 2.54; 95% CI, 1.14-5.69), ECOG performance status of 2-4 (OR 3.04; 95% CI, 1.57-5.88), presence of depression (OR 5.99; 95% CI, 1.99-18.02) and haemoglobin levels <12 g/dL (OR 3.00; 95% CI 1.54-5.84) as significant independent factors associated with moderate to high nutritional risk. The model achieved good calibration (Hosmer-Lemeshow test's p = 0.17) and discrimination (AUC = 0.80). It retained good calibration and discrimination (bias-corrected AUC = 0.79) under internal validation. Conclusion: Having advanced stage of cancer, poor performance status, depression and anaemia were found to be predictors of moderate to high nutritional risk. Early identification of patients with these risk factors will allow for nutritional interventions that may improve treatment tolerance, quality of life and survival outcomes. © 2016 Tan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.