Abstract：
OBJECTIVE: Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.
METHODS: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.
RESULTS: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.
CONCLUSIONS: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.
METHODS: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.
RESULTS: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.
CONCLUSIONS: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.
摘要：
目的：多症，存在两个或两个以上的长期条件，是一个日益增长的公共卫生问题。许多研究使用分析方法从数据中发现多浊度模式。我们旨在回顾已发表文献中用于验证这些模式的方法。
方法：我们系统地搜索了PubMed和WebofScience在2017年7月至2023年7月之间发表的研究，这些研究使用分析方法发现了多患病模式。
结果：在搜索返回的31,617项研究中，包括172。其中,111项研究（64%）进行了验证，在2017-2019年至2022-2023年,获得验证的研究数量分别从53.13%(32项研究中的17项)增加至71.25%(80项研究中的57项).确定了五种类型的验证：评估多发病模式与临床结果的关联（n=79），跨子样本的稳定性(n=26)，临床合理性（n=22），方法间的稳定性(n=7)和探索常见的决定因素(n=2)。一些研究使用了多种类型的验证。
结论：进行多发病率模式验证的研究数量明显增加。最流行的验证方法是评估多发病模式与临床结果的关联。需要关于多发病率模式验证的方法学指导。
方法：我们系统地搜索了PubMed和WebofScience在2017年7月至2023年7月之间发表的研究，这些研究使用分析方法发现了多患病模式。
结果：在搜索返回的31,617项研究中，包括172。其中,111项研究（64%）进行了验证，在2017-2019年至2022-2023年,获得验证的研究数量分别从53.13%(32项研究中的17项)增加至71.25%(80项研究中的57项).确定了五种类型的验证：评估多发病模式与临床结果的关联（n=79），跨子样本的稳定性(n=26)，临床合理性（n=22），方法间的稳定性(n=7)和探索常见的决定因素(n=2)。一些研究使用了多种类型的验证。
结论：进行多发病率模式验证的研究数量明显增加。最流行的验证方法是评估多发病模式与临床结果的关联。需要关于多发病率模式验证的方法学指导。
