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Updated: Sep 1, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Post-hepatectomy liver failure prediction and prevention: Development of a nomogram containing postoperative
Yi-Ran Li1, Jin-Dong Chen2, Jian Huang3
1Department of Intensive Care Medicine, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Introduction And Objectives:
Posthepatectomy liver failure (PHLF) is a serious complication after hepatectomy, and its effective methods for preoperative prediction are lacking. Here, we aim to identify predictive factors and build a nomogram to evaluate patients' risk of developing PHLF.
Patients And Methods:
A retrospective review of a training cohort, including 199 patients who underwent hepatectomy at the Shanghai Eastern Hepatobiliary Surgery Hospital, was conducted. Independent risk variables for PHLF were identified using multivariate analysis of perioperative variables, and a nomogram was used to build a predictive model. To test the predictive power, a prospective study in which a validation cohort of 71 patients was evaluated using the nomogram. The prognostic value of this nomogram was evaluated by the C-index.
Results:
Independent risk variables for PHLF were identified from perioperative variables. In multivariate analysis of the training cohort, tumor number, Pringle maneuver, blood loss, preoperative platelet count, postoperative ascites and use of anticoagulant medications were determined to be key risk factors for the development of PHLF, and they were selected for inclusion in our nomogram. The nomogram showed a 0.911 C-index for the training cohort. In the validation cohort, the nomogram also showed good prognostic value for predicting PHLF. The validation cohort was used with similarly successful results to evaluate risk in two previously published study models with calculated C-indexes of 0.718 and 0.711.
Conclusion:
Our study establishes for the first time a novel nomogram that can be used to identify patients at risk of developing PHLF.
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