Agreement between laboratory-based and non-laboratory-based Framingham risk score in Southern Iran

The Framingham 10-year cardiovascular disease risk is measured by laboratory-based and non-laboratory-based models. This study aimed to determine the agreement between these two models in a large population in Southern Iran. In this study, the baseline data of 8138 individuals participated in the Pars cohort study were used. The participants had no history of cardiovascular disease or stroke. For the laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, systolic blood pressure (SBP) and treatment status, total cholesterol, and High-Density Lipoprotein. For the non-laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, SBP and treatment status, and Body Mass Index. The agreement between these two models was determined by Bland Altman plots for agreement between the scores and kappa statistic for agreement across the risk groups. Bland Altman plots showed that the limits of agreement were reasonable for females <60 years old (95% CI: -2.27-4.61%), but of concern for those <greater than or equal to>60 years old (95% CI: -3.45-9.67%), males <60 years old (95% CI: -2.05-8.91%), and males <greater than or equal to>60 years old (95% CI: -3.01-15.23%). The limits of agreement were wider for males >= 60 years old in comparison to other age groups. According to the risk groups, the agreement was better in females than in males, which was moderate for females <60 years old (kappa=0.57) and those <greater than or equal to>60 years old (kappa=0.51). The agreement was fair for the males <60 years old (kappa=0.39) and slight for those <greater than or equal to>60 years old (Kappa=0.14). The results showed that in overall participants, the agreement between the two risk scores was moderate according to risk grouping. Therefore, our results suggest that the non-laboratory-based risk model can be used in resource-limited settings where individuals cannot afford laboratory tests and extensive laboratories are not available.