Methodological quality evaluation on clinical prediction models of traditional Chinese medicine: a systematic review_Chinese Journal of Evidence-Based Medicine

Authors：

JING Chengyang ¹ , FENG Lin ² , LI Jiachen ² , LIANG Lirong ² ,  LIAO Xing ¹

1. Center for Evidence Based Chinese Medicine, Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, P. R. China;
2. Department of Clinical Epidemiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, P. R. China;

Corresponding author：

LIAO Xing, Email: okfrom2008@hotmail.com

Keywords：

Clinical prediction model; Prediction model research; Methodological quality; Systematic review; Traditional Chinese medicine

DOI：

10.7507/1672-2531.202307071

Video：

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Objective To systematically review the methodological quality of research on clinical prediction models of traditional Chinese medicine. Methods The PubMed, Embase, Web of Science, CNKI, WanFang Data, VIP and SinoMed databases were electronically searched to collect literature related to the research on clinical prediction models of traditional Chinese medicine from inception to March 31, 2023. Two reviewers independently screened literature, extracted data and assessed the risk of bias of the included studies based on prediction model risk of bias assessment tool (PROBAST). Results A total of 113 studies on clinical prediction models of traditional Chinese medicine (79 diagnostic model studies and 34 prognostic model studies) were included. Among them, 111 (98.2%) studies were rated at high risk of bias, while 1 (0.9%) study was rated at low risk of bias and risk of bias of 1 (0.9%) study was unclear. The analysis domain was rated with the highest proportion of high risk of bias, followed by the participants domain. Due to the widespread lack of reporting of specific study information, risk of bias of a large number of studies was unclear in both predictors and outcome domain. Conclusion Most existing researches on clinical prediction models of traditional Chinese medicine show poor methodological quality and are at high risk of bias. Factors contributing to risk of bias include non-prospective data source, outcome definitions that include predictors, inadequate modeling sample size, inappropriate feature selection, inaccurate performance evaluation, and incorrect internal validation methods. Comprehensive methodological improvements on design, conduct, evaluation, and validation of modeling, as well as reporting of all key information of the models are urgently needed for future modeling studies, aiming to facilitate their translational application in medical practice.

Citation： JING Chengyang, FENG Lin, LI Jiachen, LIANG Lirong, LIAO Xing. Methodological quality evaluation on clinical prediction models of traditional Chinese medicine: a systematic review. Chinese Journal of Evidence-Based Medicine, 2024, 24(3): 312-321. doi: 10.7507/1672-2531.202307071 Copy

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Chinese Journal of Evidence-Based Medicine

Methodological quality evaluation on clinical prediction models of traditional Chinese medicine: a systematic review

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