The patient-generated subjective global assessment is a promising screening tool for cancer cachexia
BMJ SUPPORTIVE & PALLIATIVE CARE(2022)
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.
MoreTranslated text
Key words
cancer cachexia,subjective global assessment,promising screening tool,patient-generated
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined