151751-Najiba-Chargi

407 The elderly head and neck cancer patient: skeletal muscle mass and frailty GRONINGEN FRAILTY INDICATOR GFI is a 15-item frailty screening tool to evaluate frailty status in geriatrics through loss of function and resources in physical, social, and psychological domains. Patients were catego - rized as non-frail (GFI < 4) and frail (GFI ≥ 4). 28 In older patients with cancer the sensitivity and specificity of the GFI for predicting frailty, based on CGA, are amongst 39% to 62% and 69% to 87%, respectively. 10 The GFI is also useful in predicting postoperative complications, however this questionnaire is not special designed for oncological patients. 27 STATISTICAL ANALYSIS Data analyses were performed using IBM SPSS statistics 25. Firstly, the patient cohort was described regarding the baseline. Continuous data are represented as mean ± standard devi - ation (SD). Categorical data are represented as a number and percentage of total. MF was presented dichotomously as low MF and normal MF based on previously published gender specific cut-offs for HGS. The SMM, was presented dichotomously as low SMI and normal SMI based on previously published specific cut-offs for SMI. Sarcopenia was presented dichotomously as sarcopenic (only if patients had a lowHGS and low SMI) and non-sarcopenic (all other patients). Frailty was presented dichotomously as frail and non-frail based on abovementioned and previously published cut-offs for frailty based on the CGA, Fried criteria or GFI. Independent sample t-tests or Chi-square statistics were used for analyzing differences between the fre - quencies of each categorical variable with the presence or absence of sarcopenia and presence or absence of frailty. Univariate logistic regression analyses were performed, with sarcopenia or frailty as depen - dent variable and the baseline variables as independent variables. Variables were selected based on clinical relevance by exploring literature. Variables that were statistically significant (α < 0.05) in the univariate regression were included in the multivariate logistic regression. In this way, odds ratios (ORs) and 95% CIs were provided. RESULTS In total, 73 patients were included. The mean age was 81.73 (6.24 SD). The majority of the patients was female (55%). The mean BMI was 26.80 (5.70 SD) and most of the patients did not report loss of weight 6 months prior to diagnosis (63%). The majority of the patients used alcohol (56%) and were former smokers (55%). Most patients had a high CCI comorbidity score of >6 (63%). According to the TNM-classification most patients had stage IV disease (44%). Of the included 73 patients, 33 (45%) patients had low muscle strength, 58 (79%) had low SMI. A total of 24 (33%) patients were defined as sarcopenic. Based on the CGA 39 (54%) patients were defined as frail. Based on the frailty Fried criteria 21 (29%) patients were defined as frail, 20