151751-Najiba-Chargi

391 The elderly head and neck cancer patient: sarcopenia and frailty Table 2. (Continued) Total N=150 Sarcopenic N=21 Non Sarcopenic N=129 χ 2 p-value I 23 15 6 29 17 13 4.23 0.24 II 30 20 2 9 28 22 III 33 22 4 19 29 22 IV 64 43 9 43 55 43 Type of imaging (n, %) CT 92 61 12 57 80 62 0.18 0.67 MRI 58 39 9 43 42 38 Lowmuscle function (n, %) No 117 78 0 0 117 91 86.58 0.000* Yes 33 22 21 100 12 9 Low SMI (n, %) No 58 39 0 0 58 45 15.39 0.000* Yes 92 61 21 100 71 55 G8 Frailty questionnaire (n, %) Not frail > 14 129 86 47 78 82 91 4.88 0.027** Frail ≤ 14 21 14 13 22 8 9 UNIVARIATE AND MULTIVARIATE LOGISTIC REGRESSION Univariate and multivariate logistic regression analysis with frailty or sarcopenia as the de - pendent variable was performed. Table 3 shows the univariate regression analysis with frail - ty as the dependent variable which distinguished ACE-27 score (OR 6.17, 95% CI 1.90-20.00, P =0.002), handgrip strength (OR 0.94, 95% CI 0.90–0.97, P < 0.000), SMI (OR 0.92, 95% CI 0.87– 0.96, P < 0.000), and sarcopenia (OR 2.84, 95% CI 1.10-7.34, P =0.032) as significant variables for predicting frailty. These significant variables were subjected to two different multivariate analyses. The first with sarcopenia and the second with hand grip strength and SMI because of assumed multicollinearity. In the first multivariate analysis only ACE-27 score (OR 5.47, 95% CI 1.67-17.98, P =0.005) remained significant. In the second ACE-27 score (OR 8.08, 95% CI 2.21-29.60, P =0.003) and SMI (OR 0.92, 95% CI 0.86-0.98, P=0.006) remained significant. Table 4 shows the univariate regression analysis with sarcopenia as dependent variables distin- guished age (OR 3.68, 95%CI 1.27-10.64, P = 0.016) and G8 (OR 2.84, 95%CI 1.10-7.34, P = 0.032) as significant variables associated with sarcopenia. These significant variables were subjected to a multivariate analysis in which age (OR 3.65, 95% CI 1.25-10.71, P = 0.018) and G8 (OR 2.81, 95% CI 1.06-7.43, P = 0.037) remained significant. 19