Risk models and scores for metabolic syndrome: a systematic review

Abstract

Background: Metabolic syndrome - ‘a clustering of risk factors which includes hypertension, central obesity, impaired glucose metabolism with insulin resistance, and dyslipidaemia’ is linked with increased risk of CVD, T2DM and all-cause mortality. Despite the high number of models and scores for assessing the risk of developing MetS, there is hardly any used in research or practical setting. Hence, we conducted a systematic review to determine the performance of risk models and scores for predicting MetS.Methods: Following the methods proposed by EPPI-Centre, we systematically searched MEDLINE, CINAHL, PUBMED and Web of Science to identify studies that either derive or validate risk models or scores for predicting the risk of MetS. Search was originally done in September 2018 and updated in September 2020. Data concerning models’ statistical properties as well as details of internal or external validations were extracted. Tables were used to compare various components of models and statistical properties. Finally, PROBAST was used to assess the methodological quality (risk of bias) of included studies.Results: A total of 27 studies reporting about the development, validation or both of MetS risk models were included. There is significant heterogeneity between studies in terms of geography/demographics, data type and methodological approach. Majority of the models or risk scores were developed or validated using data from cross-sectional studies, or routine data. Various combinations of risk factors (predictors) were considered significant in the respective final model. Similarly, different criteria were used in the diagnosis of MetS, but, NCEP criteria including its modified versions were by far the most widely used (32.5%). There is generally poor reporting quality across the studies, especially concerning statistical data. Any form of internal validation is either not conducted, or not reported in nearly a fifth of the studies. Only two (2) risk models or scores were externally validatedConclusions: There is an abundance of MetS models in the literature. But, their usefulness is doubtful, due to limitations in methodology, poor reporting and lack of external validation and impact studies. Therefore, researchers in the future should focus more on externally validating/ applying such models in a different setting.Protocol:The protocol of this study can be found at https://bmjopen.bmj.com/content/9/9/e027326PROSPERO registration number CRD42019139326