Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults
Abstract 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 ext...
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2024-12-01
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| Online Access: | https://doi.org/10.1186/s12916-024-03754-9 |
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| author | Xue Cong Shuyao Song Yingtao Li Kaiyang Song Cameron MacLeod Yujie Cheng Jun Lv Canqing Yu Dianjianyi Sun Pei Pei Ling Yang Yiping Chen Iona 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 |
| author_facet | Xue Cong Shuyao Song Yingtao Li Kaiyang Song Cameron MacLeod Yujie Cheng Jun Lv Canqing Yu Dianjianyi Sun Pei Pei Ling Yang Yiping Chen Iona 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 |
| author_sort | Xue Cong |
| collection | DOAJ |
| description | Abstract 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 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. |
| format | Article |
| id | doaj-art-0e7abb29ce0d41f4a85e2b8a9ecaf327 |
| institution | Kabale University |
| issn | 1741-7015 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | BMC |
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| series | BMC Medicine |
| spelling | doaj-art-0e7abb29ce0d41f4a85e2b8a9ecaf3272025-01-05T12:32:53ZengBMCBMC Medicine1741-70152024-12-0122111310.1186/s12916-024-03754-9Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adultsXue Cong0Shuyao Song1Yingtao Li2Kaiyang Song3Cameron MacLeod4Yujie Cheng5Jun Lv6Canqing Yu7Dianjianyi Sun8Pei Pei9Ling Yang10Yiping Chen11Iona Millwood12Shukuan Wu13Xiaoming Yang14Rebecca Stevens15Junshi Chen16Zhengming Chen17Liming Li18Christiana Kartsonaki19Yuanjie Pang20on behalf of the China Kadoorie Biobank Collaborative GroupDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityMedical Sciences Division, University of OxfordMedical Sciences Division, University of OxfordDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordMeilan Center for Disease Control and PreventionClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordChina National Center for Food Safety Risk AssessmentClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordDepartment of Epidemiology & Biostatistics, School of Public Health, Peking UniversityAbstract 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 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.https://doi.org/10.1186/s12916-024-03754-9Risk predictionChronic liver diseaseHepatocellular carcinomaChineseSystematic reviewExternal validation |
| spellingShingle | Xue Cong Shuyao Song Yingtao Li Kaiyang Song Cameron MacLeod Yujie Cheng Jun Lv Canqing Yu Dianjianyi Sun Pei Pei Ling Yang Yiping Chen Iona 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 Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults BMC Medicine Risk prediction Chronic liver disease Hepatocellular carcinoma Chinese Systematic review External validation |
| title | Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults |
| title_full | Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults |
| title_fullStr | Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults |
| title_full_unstemmed | Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults |
| title_short | Comparison of models to predict incident chronic liver disease: a systematic review and external validation in Chinese adults |
| title_sort | comparison of models to predict incident chronic liver disease a systematic review and external validation in chinese adults |
| topic | Risk prediction Chronic liver disease Hepatocellular carcinoma Chinese Systematic review External validation |
| url | https://doi.org/10.1186/s12916-024-03754-9 |
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