Why the study?
The study aimed to develop a CVD risk model using routine health checkup data from a large occupational cohort.
Can a risk prediction model based on routine health checkup data accurately predict 10-year cardiovascular disease risk in the Japanese working population?
Can a risk prediction model based on routine health checkup data accurately predict 10-year cardiovascular disease risk in the Japanese working population?
A newly developed risk prediction model using routine health checkup data accurately predicts 10-year CVD risk in the Japanese working population, facilitating workplace implementation.
May inform 10-year CVD risk stratification in Japanese workers; leaves open external validation before clinical adoption.
AIMS: This study aimed to develop a cardiovascular disease (CVD) risk model using data from a large occupational cohort. METHODS: A risk prediction model was developed using the routine health checkup data of 96,117 Japanese employees (84.0% men) who were 30-64 years of age and had no CVD at baseline. Cox proportional hazards regression models were employed to develop a risk model for assessing the 10-year CVD risk. Measures of discrimination and calibration were used to assess the predictive performance of the model and internal validation was used to examine potential overfitting. RESULTS: During a mean follow-up period of 6.7 years (range, 0.1-11.0 years), 422 cases of incident CVD were confirmed. The final model, which included predictor variables of age, smoking, diabetes, systolic blood pressure, and low- and high-density lipoprotein cholesterol levels, demonstrated a good predictive ability (Harrell's C-statistic, 0.796; 95% confidence interval, 0.775-0.817) with excellent calibration between observed and predicted values. Internal validation revealed minimal overfitting. CONCLUSIONS: The developed model can accurately predict the 10-year CVD risk. Because it is based on routine health checkup data, the prediction model can be easily implemented in the workplace. Further studies are required to assess the external validity and transferability of the proposed CVD risk model.
No takes yet. Share an insight, caveat, or question.
Hu et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: