Hanna Ræder1, Christine Henriksen2, Siv Kjølsrud Bøhn2, Anne-Rikke O de Fey Vilbo2, Hege Berg Henriksen2, Ane Sørlie Kværner1, Katrine Rolid1, Ingvild Paur2, Sigbjørn Smeland3, Rune Blomhoff4. 1. Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway; Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway. 2. Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway. 3. Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 4. Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Norway; Division of Cancer Medicine, Oslo University Hospital, Oslo, Norway. Electronic address: rune.blomhoff@medisin.uio.no.
Abstract
BACKGROUND AND AIMS: Low fat-free mass (FFM) is associated with adverse outcomes in colorectal cancer (CRC) patients. Patient-Generated Subjective Global Assessment (PG-SGA) is a widely used tool developed to detect patients with malnutrition or at risk of malnutrition. The aim of this study was to investigate the agreement between PG-SGA category and FFM in patients with non-metastatic CRC. METHODS: Ninety-seven patients were included and categorized as well nourished (PG-SGA:A, n = 67) or malnourished (PG-SGA:B, n = 30). No patients were severely malnourished (PG-SGA: C). Bioelectrical impedance analysis (BIA) was used to assess FFM. Low FFM was defined as low fat-free mass index (FFMI) according to cut-off values recently proposed by The European Society for Clinical Nutrition and Metabolism (ESPEN). RESULTS: Twenty-nine percent of the patients were identified with low FFMI. The proportion with low FFMI was significantly higher among patients classified as malnourished by PG-SGA compared to well nourished (p = 0.015). The sensitivity was however low, as the PG-SGA categorization classified only 50.0% of the patients with low FFMI as malnourished (PG-SGA B). Using the PG-SGA scores (cut-off point > 4), the sensitivity increased to 60.7%. Physical examination in the PG-SGA identified only 64.3% of the patients with low FFMI as muscle depleted. CONCLUSION: Our results indicate a low agreement between PG-SGA category and low FFMI among patients with non-metastatic CRC. In clinical practice, PG-SGA should be supplemented by muscle mass assessments by BIA or other methods in order to detect low FFM in this patient group.
BACKGROUND AND AIMS: Low fat-free mass (FFM) is associated with adverse outcomes in colorectal cancer (CRC) patients. Patient-Generated Subjective Global Assessment (PG-SGA) is a widely used tool developed to detect patients with malnutrition or at risk of malnutrition. The aim of this study was to investigate the agreement between PG-SGA category and FFM in patients with non-metastatic CRC. METHODS: Ninety-seven patients were included and categorized as well nourished (PG-SGA:A, n = 67) or malnourished (PG-SGA:B, n = 30). No patients were severely malnourished (PG-SGA: C). Bioelectrical impedance analysis (BIA) was used to assess FFM. Low FFM was defined as low fat-free mass index (FFMI) according to cut-off values recently proposed by The European Society for Clinical Nutrition and Metabolism (ESPEN). RESULTS: Twenty-nine percent of the patients were identified with low FFMI. The proportion with low FFMI was significantly higher among patients classified as malnourished by PG-SGA compared to well nourished (p = 0.015). The sensitivity was however low, as the PG-SGA categorization classified only 50.0% of the patients with low FFMI as malnourished (PG-SGA B). Using the PG-SGA scores (cut-off point > 4), the sensitivity increased to 60.7%. Physical examination in the PG-SGA identified only 64.3% of the patients with low FFMI as muscle depleted. CONCLUSION: Our results indicate a low agreement between PG-SGA category and low FFMI among patients with non-metastatic CRC. In clinical practice, PG-SGA should be supplemented by muscle mass assessments by BIA or other methods in order to detect low FFM in this patient group.
Authors: Cristina Regueiro; Laura Codesido; Laura García-Nimo; Sara Zarraquiños; David Remedios; Arturo Rodríguez-Blanco; Esteban Sinde; Catalina Fernández-de-Ana; Joaquín Cubiella Journal: JMIR Res Protoc Date: 2022-05-16
Authors: Xiaoling Zhang; Jialei Zhang; Yunyi Du; Xiaoyu Wu; Yali Chang; Weiling Li; Yaqin Liu; Wenqing Hu; Jun Zhao Journal: Support Care Cancer Date: 2022-06-27 Impact factor: 3.359