Emanuele Cereda1, Paolo Pedrazzoli2, Federica Lobascio3, Sara Masi3, Silvia Crotti3, Catherine Klersy4, Annalisa Turri3, Nicole Stobäus5, Maja Tank6, Kristina Franz7, Sara Cutti8, Ester Giaquinto9, Andrea Riccardo Filippi10, Kristina Norman11, Riccardo Caccialanza3. 1. Clinical Nutrition and Dietetics Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. Electronic address: e.cereda@smatteo.pv.it. 2. Medical Oncology Unit, Fondazione IRCCS Policlinico San Matteo and Department of Internal Medicine, University of Pavia, Pavia, Italy. 3. Clinical Nutrition and Dietetics Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. 4. Clinical Epidemiology and Biometry Service, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. 5. Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Clinical Research Unit, Berlin, Germany. 6. Medizinisches Versorgungszentrum Hämatologie-Onkologie Tempelhof Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Germany; Department of Geriatrics, Research Group on Geriatrics, Berlin, Germany. 7. Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Germany; Department of Geriatrics, Research Group on Geriatrics, Berlin, Germany; German Institute of Human Nutrition Potsdam-Rehbrücke, Department of Nutrition and Gerontology, Nuthetal, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany. 8. Medical Direction, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. 9. M. Bufalini Hospital, Dietetic and Nutrition Unit, Cesena, Italy. 10. Radiation Oncology Department, Fondazione IRCCS Policlinico San Matteo and University of Pavia, Italy. 11. Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Germany; Department of Geriatrics, Research Group on Geriatrics, Berlin, Germany; German Institute of Human Nutrition Potsdam-Rehbrücke, Department of Nutrition and Gerontology, Nuthetal, Germany.
Abstract
BACKGROUND & AIMS: Reduced muscle mass represents one of the top ranked phenotypic criteria for malnutrition proposed by the Global Leadership Initiative on Malnutrition. Although height-indexed fat-free mass (FFMI) thresholds have been proposed as useful surrogate measures of reduced muscle mass, the independent prognostic value of BIA-derived FFMI by bioelectric impedance analysis (BIA) in patients with cancer still needs to be fully explored. METHODS: Data on body mass index (BMI), 6-month percentage of weight loss (%WL), FFMI by BIA and quality of life (QoL by EORTC Quality of Life Questionnaire [EORTC QLQ-C30]) of Italian and German patients observed prospectively until death or censoring were used (N = 1217). Patients were stratified in 5 risk categories according to a robustly validated scoring system based on BMI and %WL. Low FFMI was defined as follows: men, <17 kg/m2; women, <15 kg/m2. RESULTS: Reduced FFMI was found in 234 patients (19.2%). After a median follow-up of 57 months [25th-75th, 31-60], 620 patients (50.9%) had died. The study detected differences in survival between patients presenting with and without reduced FFMI (14.0 months vs. 45.1 months; P < 0.001). The fully-adjusted hazard ratio of mortality for low FFMI was 1.46 [95%CI, 1.18-1.81] (P < 0.001). Low FFMI was also independently associated with reduced QoL: fully-adjusted odds ratio, 1.50 [95%CI, 1.00-2.25] (P = 0.050). CONCLUSIONS: Reduced FFMI by BIA independently predicted survival and was associated with impaired QoL. Altered body composition should always be considered in all patients with cancer as additional phenotypic criterion of poor prognosis and BIA offers the possibility of multiple, noninvasive bedside assessments.
BACKGROUND & AIMS: Reduced muscle mass represents one of the top ranked phenotypic criteria for malnutrition proposed by the Global Leadership Initiative on Malnutrition. Although height-indexed fat-free mass (FFMI) thresholds have been proposed as useful surrogate measures of reduced muscle mass, the independent prognostic value of BIA-derived FFMI by bioelectric impedance analysis (BIA) in patients with cancer still needs to be fully explored. METHODS: Data on body mass index (BMI), 6-month percentage of weight loss (%WL), FFMI by BIA and quality of life (QoL by EORTC Quality of Life Questionnaire [EORTC QLQ-C30]) of Italian and German patients observed prospectively until death or censoring were used (N = 1217). Patients were stratified in 5 risk categories according to a robustly validated scoring system based on BMI and %WL. Low FFMI was defined as follows: men, <17 kg/m2; women, <15 kg/m2. RESULTS: Reduced FFMI was found in 234 patients (19.2%). After a median follow-up of 57 months [25th-75th, 31-60], 620 patients (50.9%) had died. The study detected differences in survival between patients presenting with and without reduced FFMI (14.0 months vs. 45.1 months; P < 0.001). The fully-adjusted hazard ratio of mortality for low FFMI was 1.46 [95%CI, 1.18-1.81] (P < 0.001). Low FFMI was also independently associated with reduced QoL: fully-adjusted odds ratio, 1.50 [95%CI, 1.00-2.25] (P = 0.050). CONCLUSIONS: Reduced FFMI by BIA independently predicted survival and was associated with impaired QoL. Altered body composition should always be considered in all patients with cancer as additional phenotypic criterion of poor prognosis and BIA offers the possibility of multiple, noninvasive bedside assessments.