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Stepwise approach to screen high-risk individuals using the non-laboratory-based and laboratory-based CVD risk
Noushin Fahimfar1,2, Sareh Eghtesad3, Hossein Poustchi3
1Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, 1411713119, Iran.
Insights
Non-laboratory models effectively identify high-risk individuals for cardiovascular disease (CVD) in resource-limited settings. This stepwise approach reduces healthcare costs and improves efficiency by minimizing laboratory testing.
Area of Science:
- Public Health
- Epidemiology
- Health Economics
Background:
- Cardiovascular disease (CVD) poses a significant global health burden, particularly in resource-limited settings.
- Accurate identification of high-risk populations is crucial for effective CVD prevention strategies.
- Standard laboratory-based models for CVD risk assessment can be resource-intensive and inaccessible in many low-resource environments.
Purpose of the Study:
- To compare the efficacy of non-laboratory CVD risk prediction models with standard laboratory-based models.
- To evaluate the performance of World Health Organization (WHO) and Iranian pooled-cohort CVD mortality models in identifying high-risk populations.
- To assess the potential of non-laboratory models to enhance healthcare system efficiency in resource-limited settings.
Main Methods:
- Analysis of a national sample of 121,672 individuals aged 40-70 from the PERSIAN cohort.
- Comparison of non-laboratory models (WHO, Iranian pooled-cohort) against a WHO laboratory-based model.
- Statistical analysis using Intra-class Correlation Coefficient (ICC) and Concordance Correlation Coefficient (CCC).
- Evaluation of sensitivity and specificity at various risk thresholds, with test reduction calculations based on the Iranian census.
Main Results:
- Both non-laboratory and laboratory-based models demonstrated similar trends in predicting CVD risk across age groups.
- Strong correlations (ICC: 94.4% men, 93.8% women) and concordance (CCC: 0.893 men, 0.883 women) were observed.
- A stepwise approach using non-laboratory models achieved high sensitivity (99.6%) and moderate specificity (52%), significantly reducing the number of required laboratory tests by over 16 million.
Conclusions:
- Non-laboratory CVD risk prediction models, when used in a stepwise approach, are effective in identifying high-risk populations in resource-limited settings.
- This strategy can significantly reduce the financial burden on healthcare systems and improve overall efficiency.
- Implementing non-laboratory models offers a promising solution for enhancing CVD screening and management in low-resource environments.
Objective:
We compared non-laboratory models' efficacy with standard laboratory-based model in identifying high-risk populations for cardiovascular disease (CVD) in resource-limited settings.
Methods:
A national sample of 121 672 individuals aged 40-70 from the PERSIAN cohort was analyzed. Non-laboratory models, including the World Health Organization (WHO) and Iranian pooled-cohort CVD mortality models, were compared with the WHO laboratory-based model. Intra-class correlation coefficient (ICC) and concordance correlation coefficient (CCC) were utilized. Sensitivity and specificity of non-laboratory models were evaluated against the laboratory-based one at various risk thresholds. The number of reduced tests in the stepwise approach was calculated considering the Iranian census.
Results:
Both non-laboratory and laboratory-based models showed similar trends in predicting CVD risks across age groups. Strong correlations and concordance were observed in both men (ICC: 94.4%, CCC:0.893) and women (ICC: 93.8%, CCC:0.883). Utilizing a 5% risk threshold for WHO non-laboratory and 2% for the Iranian pooled-cohort CVD mortality model as the initial step achieved high sensitivity (99.6%) and moderate specificity (52%) for identifying candidates for the second-step laboratory test. This approach effectively reduced the number of tests by 16 807 982.
Conclusion:
Non-laboratory models, in a stepwise approach, offer a promising strategy to alleviate strain on financial resources and enhance healthcare system efficiency in resource-limited countries.
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