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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastroenterol. Dec 21, 2026; 32(47): 121762
Published online Dec 21, 2026. doi: 10.3748/wjg.121762
Survival prediction for patients with malignant biliary obstruction caused by biliary tract cancer undergoing percutaneous biliary decompression
Yu-Zhou Zhang, Yuan-Ze Tang, Shu-Tong Pan, Yun-Xuan He, Hao-Cheng Dai, Wei-Zhong Zhou, Hai-Feng Zhou
Yu-Zhou Zhang, Yuan-Ze Tang, Shu-Tong Pan, Yun-Xuan He, Hao-Cheng Dai, School of Medical Imaging, Nanjing Medical University, Nanjing 211166, Jiangsu Province, China
Wei-Zhong Zhou, Hai-Feng Zhou, Department of Interventional Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
Co-first authors: Yu-Zhou Zhang and Yuan-Ze Tang.
Co-corresponding authors: Wei-Zhong Zhou and Hai-Feng Zhou.
Author contributions: Zhou HF and Zhou WZ designed the research study; Zhang YZ and Tang YZ performed the research; Pan ST, He YX, Dai HC and Zhou HF contributed new reagents and analytic tools; Zhang YZ and Tang YZ analyzed the data and wrote the manuscript; all authors have read and approve the final manuscript. Both of these two co-corresponding authors are study designers. They were responsible for overseeing the entire interventional procedure and data quality control throughout the study. Besides, Zhou WZ, with extensive expertise in interventional radiology, provided critical technical guidance. Zhou HF led the study methodology of survival prediction. Both authors were deeply involved in manuscript revision, responding to peer-review comments, and ensuring the accuracy and integrity of the research findings.
AI contribution statement: AI tools were used solely for linguistic refinement and formatting assistance. No AI tool was involved in the generation of research data, interpretation of results, or formulation of conclusions. All AI-generated outputs were critically reviewed and revised by the authors.
Supported by Jiangsu Provincial Innovative and Entrepreneurial Doctor Program, No. 303073543ER21; Young Scholars Fostering Fund of the First Affiliated Hospital of Nanjing Medical University, No. PY2023056; and Natural Science Foundation of Jiangsu Province (Youth Fund Project), No. BK20241121.
Institutional review board statement: This study was approved by the Institutional Review Board of the First Affiliated Hospital with Nanjing Medical University (Approval No. 2022-SR-014).
Informed consent statement: Due to the retrospective nature, there was no need to obtain informed consent.
Conflict-of-interest statement: All authors declare that they have no conflict of interest.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at [hfzhou_ir@sina.com].
Corresponding author: Hai-Feng Zhou, MD, PhD, Department of Interventional Radiology, The First Affiliated Hospital with Nanjing Medical University, No. 300 Guangzhou Road, Nanjing 210029, Jiangsu Province, China. hfzhou_ir@sina.com
Received: April 8, 2026
Revised: May 10, 2026
Accepted: June 2, 2026
Published online: December 21, 2026
Processing time: 209 Days and 16.6 Hours
Abstract
BACKGROUND

Malignant biliary obstruction (MBO) caused by biliary tract cancer (BTC) is considered to has a poor prognosis, and there is substantial survival heterogeneity after percutaneous biliary decompression (PBD). Although it’s widely agreed that a standardized prognostic evaluation system is needed, a comprehensive and universally accepted prediction model remains lacking.

AIM

To develop and validate a practical nomogram for individualized survival prediction in patients with MBO secondary to BTC.

METHODS

A total of 284 patients were retrospectively enrolled with BTC-induced MBO who underwent PBD between June 2015 and July 2021. These patients were randomly assigned to a training cohort (n = 204) and a validation cohort (n = 80). The Cox proportional hazards regression analysis was used to find independent prognostic factors, and these factors were included to build the modified Clinical Outcomes of MBO-Biliary tract cancer Survival (mCOMBO-BaS) nomogram. Model performance was assessed by concordance index, calibration plots, and the area under the curve (AUC).

RESULTS

Seven prognostic indicators were identified: Tumor subtype, subsequent surgery, total bilirubin, total cholesterol, hemoglobin, sodium, and carbohydrate antigen 19-9 level. The mCOMBO-BaS model showed good discriminatory ability, with C-indices over 0.65 for all BTC subtypes. In the training group, the AUCs for predicting 3-month, 6-month, and 1-year survival were 0.809, 0.798, and 0.733 respectively. In the validation group, they were 0.886, 0.804, and 0.793 respectively. Calibration plots indicated that the predicted survival probabilities were close to the actual observed ones.

CONCLUSION

The mCOMBO-BaS nomogram can accurately predict the survival of individual BTC patients with MBO undergoing PBD. This easy-to-use tool can help with clinical decision-making and risk stratification for various BTC subtypes.

Keywords: Biliary tract cancer; Malignant biliary obstruction; Percutaneous biliary decompression; Nomogram; Survival prediction

Core Tip: This study developed and validated the modified Clinical Outcomes of Malignant biliary obstruction-Biliary tract cancer Survival nomogram, a practical tool for predicting the survival of individual patients with biliary tract cancer (BTC)-related malignant biliary obstruction undergoing percutaneous biliary decompression. By integrating seven prognostic variables (tumor subtype, subsequent surgery, total bilirubin, total cholesterol, hemoglobin, sodium, and carbohydrate antigen 19-9 level), the model showed robust discriminatory ability across all BTC subtypes for predicting 3-month, 6-month, and 1-year survival in both training and validation cohorts. This nomogram addresses the lack of personalized risk stratification in this patient population, helping clinicians optimize treatment decisions and improve overall management.

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