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Multivariable prognostic models for post-hepatectomy liver failure: An updated systematic review
Xiao Wang1,2, Ming-Xiang Zhu2,3, Jun-Feng Wang4
1Department of Hepatobiliary Surgery, Chinese PLA 970 Hospital, Yantai 264001, Shandong Province, China.
World Journal of Hepatology
|May 1, 2025
Summary
This review found that post-hepatectomy liver failure (PHLF) prognostic models have a high risk of bias, with validation performance significantly lower than development performance. Improved quality assessment tools are needed for advanced modeling techniques.
Area of Science:
- Hepatobiliary surgery
- Medical predictive modeling
- Clinical risk assessment
Background:
- Partial hepatectomy is a key treatment for liver tumors.
- Post-hepatectomy liver failure (PHLF) is a critical surgical complication.
Purpose of the Study:
- To review recent PHLF prognostic models.
- To assess the risk of bias in these models.
Main Methods:
- Systematic review following PRISMA and relevant guidelines.
- Searched three databases (Nov 2019-Dec 2022), screened references.
- Evaluated model quality using PROBAST tool.
Main Results:
- Included 34 studies on PHLF prognostic models.
- Most models (94.1%) used private data; most (94.1%) used multiple data types.
- High risk of bias found across all studies due to analytical issues.
Conclusions:
- Model validation performance was lower than development performance.
- All studies had a high risk of bias, particularly in analytical aspects.
- Advanced modeling requires appropriate quality assessment tools.
