A Sex‐Stratified Prognostic Nomogram Incorporating Body Compositions for Long‐Term Mortality in Cirrhosis. Issue 2 (2nd May 2020) - Hou, Lijun; Deng, You; Fan, Xiaofei; Zhao, Tianming; Cui, Binxin; Lin, Lin; Hou, Junjie; Mao, Lihong; Zhao, Wei; Jiang, Kui; Wang, Bangmao; Zhang, Jie; et al.
Abstract: Background: Alterations in body compositions are related to poor outcomes and the presence of complications in cirrhosis. However, no predictive tools combining all these anthropometric parameters are applicable in the clinical setting. We aimed to clarify the potential utility of body compositions and develop a nomogram incorporating any independent factor for prognosticating long‐term mortality in cirrhosis. Methods: A total of 414 patients were randomized into primary (n = 274) and validation (n = 140) cohorts. X‐tile was performed to identify optimal cut points for stratifying participants. Multivariate Cox regression was performed, and nomogram incorporating body compositions were generated. The utility of developed models was evaluated by Harrell concordance index (C‐index), calibration curve, and decision curve analysis (DCA). Results: Stratifying by X‐tilederived cut points, low skeletal muscle index (myopenia), high intramuscular adipose tissue content (myosteatosis), and the ratio of high visceral to subcutaneous adipose tissue area (adiposity) was independently associated with 3‐year mortality. A sex‐stratified nomogram incorporating anthropometric indices and clinical factors resulted in moderate discriminative accuracy, with a C‐index of 0.787 (95% CI, 0.736–0.838) and 0.789 (95% CI, 0.727–0.851) in males and females, respectively. The calibration curve showed predictive survival corresponding optimally with the actual outcomes. Our models were feasible in the clinical settings based on DCA. Similar results were observed in the validation cohort. Additionally, participants could be classified into 3 distinct risk groups by the nomogram. Conclusions: Our proposed nomogram embedding body compositions rendered an individualized predictive tool for long‐term mortality in cirrhosis.