Cardiovascular risk prediction models for women in the general population: A systematic review

Abstract

AimTo provide a comprehensive overview of cardiovascular disease (CVD) risk prediction models for women and models that include female-specific predictors.MethodsWe performed a systematic review of CVD risk prediction models for women in the general population by updating a previous review. We searched Medline and Embase up to July 2017 and included studies in which; (a) a new model was developed, (b) an existing model was validated, or (c) a predictor was added to an existing model.ResultsA total of 285 prediction models for women have been developed, of these 160 (56%) were female-specific models, in which a separate model was developed solely in women and 125 (44%) were sex-predictor models. Out of the 160 female-specific models, 2 (1.3%) included one or more female-specific predictors (mostly reproductive risk factors). A total of 591 validations of sex-predictor or female-specific models were identified in 206 papers. Of these, 333 (56%) validations concerned nine models (five versions of Framingham, SCORE, Pooled Cohort Equations and QRISK). The median and pooled C statistics were comparable for sex-predictor and female-specific models. In 260 articles the added value of new predictors to an existing model was described, however in only 3 of these female-specific predictors (reproductive risk factors) were added.ConclusionsThere is an abundance of models for women in the general population. Female-specific and sex-predictor models have similar predictors and performance. Female-specific predictors are rarely included. Further research is needed to assess the added value of female-specific predictors to CVD models for women and provide physicians with a well-performing prediction model for women.

Association between the reproductive health of young women and cardiovascular disease in later life: umbrella review

“…Prediction models for traditional risk factors for cardiovascular disease could underestimate the true risk of cardiovascular disease in young women because they do not account for risk factors specific to women 155. A recent systematic review on risk prediction models for cardiovascular disease in women noted that only 1.1% of the 260 articles included in the review investigated the added value of incorporating risk factors specific to women in risk prediction models 156. Even in studies that evaluated the use of predictors specific to women, however, none included predictors such as hypertensive disorders of pregnancy, gestational diabetes, polycystic ovary syndrome, and premature ovarian insufficiency.…”

Variations between women and men in risk factors, treatments, cardiovascular disease incidence, and death in 27 high-income, middle-income, and low-income countries (PURE): a prospective cohort study

“…The inclusion of these factors to improve cardiovascular disease risk prediction in women has not been previously evaluated. 48 Moreover, a systematic review of risk prediction models in women in the general population concluded that established sex independent cardio vascular disease risk predictors (ie, age, blood pressure, and smoking) made the greatest contribution to model performance. 48 Second, although we accounted for differences in risk factor burden when examining use of primary and secondary prevention medicines, we were unable to account for differences in eligibility for or contraindi cations to specific medicines.…”

Association Between the Reproductive Health of Young Women and Cardiovascular Disease in Later Life: Umbrella Review

“…155 A recent systematic review on risk prediction models for cardiovascular disease in women noted that only 1.1% of the 260 articles included in the review investigated the added value of incorporating risk factors specific to women in risk prediction models. 156 Even in studies that evaluated the use of predictors specific to women, however, none included predictors such as hypertensive disorders of pregnancy, gestational diabetes, polycystic ovary syndrome, and premature ovarian insufficiency. The benefit of adding reproductive factors to risk prediction models for cardiovascular disease needs to be extensively evaluated.…”