Establishment and validation of a predictive nomogram for severe pleural effusion in liver cancer patients after hepatectomy

Author:

Zhao Jun-Yu1,Lin Hang-Yu2,Gong Cai-Fang1,Zhang Hong2,Huang Xu-Jian1,Xie Meng-Yi1,You Chuan1ORCID

Affiliation:

1. Department of Hepatobiliary Surgery, The Affiliated Hospital of North Sichuan Medical College, Nanchong, China

2. Department of Gastroenterology, The Affiliated Hospital of North Sichuan Medical College, Nanchong, China.

Abstract

This study aims to develop and validate a predictive nomogram for severe postoperative pleural effusion (SPOPE) in patients undergoing hepatectomy for liver cancer. A total of 536 liver cancer patients who underwent hepatectomy at the Department of Hepatobiliary Surgery I of the Affiliated Hospital of North Sichuan Medical College from January 1, 2018, to December 31, 2022, were enrolled in a retrospective observational study and comprised the training dataset. Lasso regression and logistic regression analyses were employed to construct a predictive nomogram. The nomogram was internally validated using Bootstrapping and externally validated with a dataset of 203 patients who underwent liver cancer resection at the Department of General Surgery III of the same hospital from January 1, 2020, to December 31, 2022. We evaluated the nomogram using the receiver operating characteristic curve, calibration curve, and decision curve analysis. Variables such as drinking history, postoperative serum albumin, postoperative total bilirubin, right hepatectomy, diaphragm incision, and intraoperative blood loss were observed to be associated with SPOPE. These factors were integrated into our nomogram. The C-index of the nomogram was 0.736 (95% CI: 0.692–0.781) in the training set and 0.916 (95% CI: 0.872–0.961) in the validation set. The nomogram was then evaluated using sensitivity, specificity, positive predictive value, negative predictive value, calibration curve, and decision curve analysis. The nomogram demonstrates good discriminative ability, calibration, and clinical utility.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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