The Department of Endocrinology, 
Comparison of laboratory-based and non-laboratory-based cardiovascular risk prediction tools in rural India.
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Victoria, Australia.
- Cardiovascular Disease Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Victoria, Australia.
- Pre-clinical Critical Care Unit, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia.
- Rishi Valley Rural Health Centre, Chittoor, India.
- Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore, India.
- Peninsula Clinical School, Central Clinical School, Monash University, Frankston, Victoria, Australia.
Tropical medicine & international health : TM & IH Vol. 30 · Issue 1 · pp. 57-64
PMID 39660447 DOI 10.1111/tmi.14069
Cite This Article
Mulugeta Molla Birhanu, Ayse Zengin, Roger G Evans, Joosup Kim, Muideen T Olaiya, Michael A Riddell, Kartik Kalyanram, Kamakshi Kartik, Oduru Suresh, Nihal Thomas, Velandai K Srikanth, Amanda G Thrift. Comparison of laboratory-based and non-laboratory-based cardiovascular risk prediction tools in rural India. Tropical medicine & international health : TM & IH. 2025;30(1):57-64. doi:10.1111/tmi.14069
Abstract
BACKGROUND: Non-laboratory-based cardiovascular risk prediction tools are feasible alternatives to laboratory-based tools in low- and middle-income countries. However, their effectiveness compared to their laboratory-based counterparts has not been adequately tested.
AIM: We compared estimates from laboratory-based and non-laboratory-based risk prediction tools in a low- and middle-income country setting.
METHODS: Using a cross-sectional design, residents of the Rishi Valley region, Andhra Pradesh, India, were surveyed from 2012 to 2015. Ten-year absolute risk was compared for laboratory-based and non-laboratory-based Framingham Risk Score (FRS), World Health Organization-Risk Score (WHO-RS) and risk prediction tool for global populations (Globorisk). An agreement was assessed using ordinary least-products (OLP) regression (for RS) and quadratic weighted kappa (κ, for risk band).
RESULTS: Among 2847 participants aged 40-74 years, the mean age was 54.0 years. Cardiovascular RS increased with age and was greater in men than women in each age group. For all tools, regardless of whether laboratory or non-laboratory-based, over 80% of the participants were classified in the same risk band. There was strong agreement between laboratory-based and non-laboratory-based tools, greatest for the WHO-RS tools (OLP slope = 0.96, κ = 0.93) and least for the FRS (OLP slope = 0.84, κ = 0.88). The level of agreement was greater among women than men, less in those with hypercholesterolaemia or hypertension than those without, and was particularly poor among those with diabetes.
CONCLUSIONS: Non-laboratory-based Framingham, WHO-RS and Globorisk tools performed relatively well compared with their laboratory-based counterparts in rural India. However, they may be less useful for risk stratification when applied to individuals with diabetes.
Keywords
- cardiovascular disease
- low‐ and middle‐income countries
- prevention
- risk prediction
- risk score
