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Published on: September 26, 2018
Risk prediction models for atherosclerotic cardiovascular disease: A systematic assessment with particular reference
Aziz Sheikh1, Ulugbek Nurmatov2, Huda Amer Al-Katheeri3
1Usher Institute, University of Edinburgh, Edinburgh, UK
Insights
No current Atherosclerotic Cardiovascular Disease (ASCVD) risk calculator is ideal for Qatar
Area of Science:
- Cardiology
- Public Health
- Epidemiology
Background:
- Atherosclerotic cardiovascular disease (ASCVD) poses a significant health burden in Qatar.
- Current risk prediction models, like the ACC/AHA PCE, may not be optimal for Qatar's diverse ethnic population.
- Evaluating alternative ASCVD risk calculators is crucial for effective public health strategies.
Purpose of the Study:
- To systematically review and compare established ASCVD risk prediction models for the Qatari population.
- To assess the methodological quality and properties of available risk calculators.
- To identify the most suitable ASCVD risk models for Qatar.
Main Methods:
- Systematic review and head-to-head comparison of ASCVD risk calculators.
- Independent screening of studies based on predefined eligibility criteria.
- Critical appraisal using the Prediction Model Risk Of Bias Assessment Tool.
Main Results:
- 41 studies met eligibility criteria, identifying 16 unique risk prediction models.
- 50% of models had low risk of bias; only 2 models (PREDICT, QRISK3) showed low applicability risk.
- PREDICT demonstrated low risk of bias in both methodology and applicability.
Conclusions:
- No single ASCVD risk calculator is perfectly suited for Qatar's diverse population.
- PREDICT and QRISK3 are the most appropriate available models due to ethnicity considerations.
- Further direct comparison of PCE, PREDICT, and QRISK3 is warranted in the absence of a Qatar-specific model.
Background:
Atherosclerotic cardiovascular disease (ASCVD) is a common disease in the State of Qatar and results in considerable morbidity, impairment of quality of life and mortality. The American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) is currently used in Qatar to identify those at high risk of ASCVD. However, it is unclear if this is the optimal ASCVD risk prediction model for use in Qatar's ethnically diverse population.
Aims:
This systematic review aimed to identify, assess the methodological quality of and compare the properties of established ASCVD risk prediction models for the Qatari population.
Methods:
Two reviewers performed head-to-head comparisons of established ASCVD risk calculators systematically. Studies were independently screened according to predefined eligibility criteria and critically appraised using Prediction Model Risk Of Bias Assessment Tool. Data were descriptively summarized and narratively synthesized with reporting of key statistical properties of the models.
Results:
We identified 20,487 studies, of which 41 studies met our eligibility criteria. We identified 16 unique risk prediction models. Overall, 50% (n = 8) of the risk prediction models were judged to be at low risk of bias. Only 13% of the studies (n = 2) were judged at low risk of bias for applicability, namely, PREDICT and QRISK3.Only the PREDICT risk calculator scored low risk in both domains.
Conclusions:
There is no existing ASCVD risk calculator particularly well suited for use in Qatar's ethnically diverse population. Of the available models, PREDICT and QRISK3 appear most appropriate because of their inclusion of ethnicity. In the absence of a locally derived ASCVD for Qatar, there is merit in a formal head-to-head comparison between PCE, which is currently in use, and PREDICT and QRISK3.
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