The patient-generated subjective global assessment is a promising screening tool for cancer cachexia. Issue Volume 12(2022)Issue e1 (21st August 2020)

• Record Type: Journal Article
• Authors: Cong, Minghua; Song, Chenxin; Xu, Hongxia; Song, Chunhua; Wang, Chang; Fu, Zhenming; Ba, Yi; Wu, Jing; Xie, Conghua; Chen, Gongyan; Chen, Zihua; Zhou, Lan; Li, Tao; Deng, Li; Xin, Lin; Yang, Liuqing; Cui, Jiuwei; Shi, Hanping
• Is Part Of: BMJ supportive & palliative care. Volume 12(2022)Issue e1
• Page Start: e39
• Page End: e46
• Publication Date: 2020-08-21
• Subjects: Palliative treatment -- Periodicals; Terminal care -- Periodicals; 616.029
• DOI: 10.1136/bmjspcare-2020-002296
• Languages: English
• ISSNs: 2045-435X

Abstract

Abstract : Background: Cancer cachexia is a complex metabolic syndrome characterised by a loss of muscle with or without loss of fat mass, and is associated with high morbidity and mortality. Despite its clinical importance, there is a lack of simple tools to screen patients for cancer cachexia. The aim of this study was to evaluate and validate the patient-generated subjective global assessment (PG-SGA) as a screening tool for cancer cachexia. Methods: This is a secondary analysis of a multicentre, cross-sectional, observational study. Cancer cachexia was diagnosed when there was weight loss ≥5% during the past 12 months and at least three of the five following conditions were present: decreased muscle strength, fatigue, anorexia, low Fat-Free Mass Index (FFMI) and abnormal laboratory findings. A quadratic discriminant analysis was conducted for the ability of PG-SGA to predict cachexia. Results: A total of 4231 patients with cancer were included in this analysis, and 351 patients (8.3%) were diagnosed as having cachexia. The highest incidence of cachexia was found among patients with pancreatic cancer (32.5%), oesophageal cancer (21.5%) and gastric cancer (17.9%). Compared with patients without cachexia, patients with cachexia had a lower body mass index, FFMI, hand grip strength, total protein, prealbumin, albumin, haemoglobin and Karnofsky performance status (p<0.05), while they had a higher C reactive protein level and PG-SGA Score (4.71±3.71 vs 10.87±4.84, p<0.05). The best cut-off value for PG-SGA was 6.5, with 79.8% of sensitivity and 72.3% specificity for cachexia, and the area under the receiver operating characteristic curve was 0.846 (95% CI 0.826 to 0.866, p<0.001). Conclusions: PG-SGA is a highly specific tool that can be used to screen patients for cancer cachexia.