Journal article
Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults
- Abstract:
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Background: Risk prediction models can identify individuals at high risk of chronic liver disease (CLD), but there is limited evidence on the performance of various models in diverse populations. We aimed to systematically review and meta-analyze CLD prediction models and externally validated them in 0.5 million Chinese adults in the China Kadoorie Biobank (CKB).
Methods: Models were identified through a systematic review and categorized by the target population and outcomes (hepatocellular carcinoma [HCC] and CLD). The performance of models to predict 10-year risk of CLD was assessed by discrimination (C-index) and calibration (observed vs predicted probabilities).
Results: The systematic review identified 57 articles and 114 models (28.4% undergone external validation), including 13 eligible for validation in CKB. Models with high discrimination (C-index ≥0.70) in CKB were: (1) general population: Li-2018 and Wen 1-2012 for HCC, CLivD score (non-lab and lab) and dAAR for CLD; (2) hepatitis B virus (HBV) infected individuals: Cao-2021 for HCC and CAP-B for CLD. In CKB, all models tended to overestimate the risk (O:E ratio 0.55-0.94). In meta-analysis, we further identified models with high discrimination: (1) general population (C-index ≥0.70): Sinn-2020, Wen 2-2012, and Wen 3-2012 for HCC, and FIB-4, Forns for CLD; (2) HBV infected individuals (C-index ≥0.80): RWS-HCC and REACH-B IIa for HCC and GAG-HCC for HCC and CLD.
Conclusions: Several models showed good discrimination and calibration in external validation, indicating their potential feasibility for risk stratification in population-based screening programs for CLD in Chinese adults.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.8MB, Terms of use)
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(Preview, Supplementary materials, pdf, 2.2MB, Terms of use)
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- Publisher copy:
- 10.1186/s12916-024-03754-9
Authors
- Funder identifier:
- https://ror.org/029chgv08
- Grant:
- 104085/Z/14/Z
- 088158/Z/09/Z
- 202922/Z/16/Z
- 212946/Z/18/Z
- Publisher:
- BioMed Central
- Journal:
- BMC Medicine More from this journal
- Volume:
- 22
- Issue:
- 1
- Article number:
- 601
- Publication date:
- 2024-12-31
- Acceptance date:
- 2024-11-05
- DOI:
- EISSN:
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1741-7015
- Language:
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English
- Keywords:
- Pubs id:
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2062403
- Local pid:
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pubs:2062403
- Deposit date:
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2024-11-14
Terms of use
- Copyright holder:
- Cong et al.
- Copyright date:
- 2024
- Rights statement:
- Copyright © 2024, The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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