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Comparing Non-Laboratory-Based and Laboratory-Based Cardiovascular Risk Predictions: Systematic Review and
Yihun Mulugeta Alemu1,2, Sisay M Alemu3, Nasser Bagheri1,4
1National Centre for Epidemiology and Population Health, College of Health and Medicine Australian National University Canberra Australia.
Health Science Reports
|August 1, 2026
Summary
Non-laboratory-based cardiovascular disease (CVD) risk equations show strong agreement with lab-based methods. While highly correlated, their interchangeability requires context-specific validation for accurate CVD risk assessment.
Area of Science:
- Cardiology
- Epidemiology
- Biostatistics
Background:
- Cardiovascular disease (CVD) is a leading global cause of death.
- Accurate CVD risk assessment is crucial for prevention and management.
- Discrepancies exist between laboratory-based and non-laboratory-based risk equations.
Purpose of the Study:
- To assess the agreement between non-laboratory-based and laboratory-based cardiovascular disease (CVD) risk equations.
- To evaluate the concordance of these equations across diverse global settings.
- To identify factors influencing the agreement between different CVD risk assessment tools.
Main Methods:
- Systematic literature search of PubMed, Scopus, Web of Science, ProQuest, and Google Scholar up to March 2025.
- Meta-analysis of 33 studies (243,587 participants) comparing laboratory-based and non-laboratory-based CVD risk equations.
- Agreement measured using Spearman correlation coefficient and Kappa statistics, analyzed with mixed-effects meta-regression.
Main Results:
- Pooled Spearman correlation was 0.954 and pooled kappa was 0.64, indicating strong agreement.
- Higher correlations observed in studies before 2000, high-income settings, and for equations predicting fatal outcomes only.
- Significant heterogeneity (I²=100% for correlation, I²=99% for kappa) noted across studies.
Conclusions:
- Non-laboratory-based CVD risk equations demonstrate substantial agreement with laboratory-based equations.
- Despite strong correlation, predictive equivalence is not guaranteed.
- Implementation and interchangeability of non-laboratory-based equations require external validation and recalibration based on specific contexts.
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