An enhanced item-based FINDRISC model incorporating gender, systolic blood pressure, and total cholesterol achieved an AUC of 75.2%, showing comparable predictive performance for incident CHD to the Framingham non-laboratory risk score (AUC 73.3%).
Cohort (n=9,469)
No
Does the FINDRISC model predict incident CHD events as accurately as the Framingham non-laboratory model in adults aged 40-70?
An enhanced item-based FINDRISC model incorporating gender and systolic blood pressure performs comparably to the Framingham non-laboratory model for predicting CHD risk in an Iranian population.
Effect estimate: AUC 75.2% (95% CI 73-77)
Absolute Event Rate: 75.2% vs 73.3%
Background: Coronary heart disease is a leading cause of death worldwide, making early risk identification essential. This study compares the predictive performance of FINDRISC and the Framingham model in the Kharameh Cohort. Methods: This prospective cohort study included 9,469 participants aged 40– 70 years from the Kharameh cohort (a branch of the PERSIAN study) who were free of CHD at baseline and were followed for 6 years to identify incident CHD events. Data on FINDRISC components, as well as laboratory and demographic variables, were collected at enrollment. Logistic regression models were developed using the total FINDRISC score and its individual items, and their predictive performance was compared with the Framingham non‑laboratory risk score using 10‑fold cross‑validation and metrics including AUC‑ROC, sensitivity, and specificity. Results: During a six‑year follow‑up of 9,469 participants (mean age 51.6 years, 55.6% female), 540 incident CHD events (5.7%) were identified. The total FINDRISC score was significantly higher in individuals who developed CHD (11.35 vs. 9.59, P< 0.001). However, the total FINDRISC score alone showed weak discriminatory power (AUC=58.6%, 95% CI: 55.9– 61.3%). An item-based FINDRISC model demonstrated improved performance (AUC=71%, 95% CI: 68.9– 73%), and further enhancement with gender, systolic blood pressure, and total cholesterol yielded the highest predictive accuracy (AUC=75.2%, 95% CI: 73%– 77%). The non‑laboratory Framingham risk score (AUC=73.3%, 95% CI: 71.4– 75.1%) showed similar discriminatory performance compared with the enhanced item‑based FINDRISC models. Conclusion: The enhanced item-based FINDRISC model, incorporating gender and systolic blood pressure showed comparable performance to the Framingham non-laboratory model, providing a simple, accessible screening tool for the Iranian population. Keywords: coronary heart disease, risk prediction, FINDRISC, Framingham risk score
Hamedi et al. (Wed,) conducted a cohort in Coronary heart disease (CHD) risk prediction (n=9,469). Enhanced item-based FINDRISC model (incorporating gender, systolic blood pressure, and total cholesterol) vs. Framingham non-laboratory risk score was evaluated on Predictive accuracy for incident CHD (AUC-ROC) (AUC 75.2%, 95% CI 73-77). An enhanced item-based FINDRISC model incorporating gender, systolic blood pressure, and total cholesterol achieved an AUC of 75.2%, showing comparable predictive performance for incident CHD to the Framingham non-laboratory risk score (AUC 73.3%).