Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults

作者：Xue Cong, Shuyao Song, Y. Li, Kaiyang Song, Cameron Macleod, Yujie Cheng, Jun Lv, Canqing Yu, Dianjianyi Sun, Pei Pei, Ling Yang, Yiping Chen, Iona Y. Millwood, Shukuan Wu, Xiaoming Yang, Rebecca Stevens, Junshi Chen, Zhengming Chen, Liming Li, Christiana Kartsonaki, Yuanjie Pang, on behalf of the China Kadoorie Biobank Collaborative Group · 发表于：BMC Medicine · 年份：2024 · DOI：10.1186/s12916-024-03754-9 · 被引用次数：5 · 研究领域：Liver Disease Diagnosis and Treatment、Hepatitis C virus research、Hepatitis B Virus Studies

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 CLD prediction models, meta-analyze their performance, and externally validate 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 probabilies). 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 as follows: (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 and 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 mod...