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Assessing the Accuracy of Cardiovascular Disease Prediction Using Female-Specific Risk Factors in Women Aged 45 to 69
Jenny Doust1, Mohammad Reza Baneshi1, Hsin-Fang Chung1
1Australian Women and Girls' Health Research Centre, School of Public Health, The University of Queensland, Herston, Australia.
Insights
Adding female-specific risk factors to traditional cardiovascular disease (CVD) prediction models did not significantly improve risk reclassification in women aged 45-69. These factors should not be used for medication decisions in this age group.
Area of Science:
- Cardiology
- Epidemiology
- Women's Health
Background:
- Cardiovascular disease (CVD) is the primary cause of mortality among women.
- Traditional risk calculators may not fully capture CVD risk in women.
- Investigating female-specific factors is crucial for accurate risk prediction.
Purpose of the Study:
- To evaluate if incorporating female-specific risk factors enhances CVD risk prediction in women.
- To assess the impact of these factors on discrimination and calibration of existing risk models.
Main Methods:
- Utilized UK Biobank data from women aged 45-69, free of CVD at baseline.
- Employed Cox proportional hazards models with traditional risk factors from three calculators (PCE-ASCVD, Qrisk2, PREDICT).
- Added female-specific factors (e.g., menarche, endometriosis, menopause, pregnancy history) individually and combined to assess predictive improvements.
Main Results:
- The addition of individual female-specific risk factors did not improve model discrimination or calibration (c-indices ranged from 0.710 to 0.718).
- Simultaneously adding all female-specific factors resulted in a minor increase in c-indices (up to 0.720).
- No significant improvement in reclassification metrics or calibration plots was observed.
Conclusions:
- While some female-specific factors indicate early CVD risk, they do not improve risk reclassification in women aged 45-69 for medication initiation.
- Current traditional risk calculators, when augmented with these factors, do not offer substantial gains for clinical decision-making in this demographic.
- Further research may be needed to identify other factors or refine existing ones for better CVD risk prediction in women.
Background:
Cardiovascular disease (CVD) is the leading cause of mortality in women. We aimed to assess whether adding female-specific risk factors to traditional factors could improve CVD risk prediction.
Methods:
We used a cohort of women from the UK Biobank Study aged 45 to 69 years, free of CVD at baseline (2006-2010) followed until the end of 2019. We developed Cox proportional hazards models using the risk factors included in 3 contemporary CVD risk calculators: Pooled Cohort Equation - Atherosclerotic Cardiovascular Disease, Qrisk2, and PREDICT. We added each of the following female-specific risk factors, individually and all together, to determine if these improved measures of discrimination and calibration for predicting CVD: early menarche (<11 years), endometriosis, excessive, frequent or irregular menstruation, miscarriage, number of miscarriages, number of stillbirths, infertility, preeclampsia or eclampsia, gestational diabetes (without subsequent type 2 diabetes), premature menopause (<40 years), early menopause (<45 years), and natural or surgical early menopause (menopause <45 years or timing of menopause reported as unknown and oophorectomy reported at age <45).
Results:
In the model of 135 142 women (mean age, 57.5 years; SD, 6.8) using risk factors from Pooled Cohort Equation - Atherosclerotic Cardiovascular Disease, CVD incidence was 5.3 per 1000 person-years. The c-indices for the Pooled Cohort Equation - Atherosclerotic Cardiovascular Disease, Qrisk2, and PREDICT models were 0.710, 0.713, and 0.718, respectively. Adding each of the female-specific risk factors did not improve the c-index, the net reclassification index, the integrated discrimination index, the slope of the regression line for predicted versus observed events, and the Brier score or plots of calibration. Adding all female-specific risk factors simultaneously increased the c-index for the Pooled Cohort Equation - Atherosclerotic Cardiovascular Disease, Qrisk2, and PREDICT models to 0.712, 0.715, and 0.720, respectively.
Conclusions:
Although several female-specific factors have been shown to be early indicators of CVD risk, these factors should not be used to reclassify risk in women aged 45 to 69 years when considering whether to commence a blood pressure or lipid-lowering medication.
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