J Korean Med Sci.  2024 Feb;39(5):e47. 10.3346/jkms.2024.39.e47.

Validation of the Framingham Diabetes Risk Model Using Community-Based KoGES Data

• Lee HA
• Park H
• Hong YS

• KMID: 2551977
• DOI: http://doi.org/10.3346/jkms.2024.39.e47

Abstract

Background
An 8-year prediction of the Framingham Diabetes Risk Model (FDRM) was proposed, but the predictor has a gap with current clinical standards. Therefore, we evaluated the validity of the original FDRM in Korean population data, developed a modified FDRM by redefining the predictors based on current knowledge, and evaluated the internal and external validity.
Methods
Using data from a community-based cohort in Korea (n = 5,409), we calculated the probability of diabetes through FDRM, and developed a modified FDRM based on modified definitions of hypertension (HTN) and diabetes. We also added clinical features related to diabetes to the predictive model. Model performance was evaluated and compared by area under the curve (AUC).
Results
During the 8-year follow-up, the cumulative incidence of diabetes was 8.5%. The modified FDRM consisted of age, obesity, HTN, hypo-high-density lipoprotein cholesterol, elevated triglyceride, fasting glucose, and hemoglobin A1c. The expanded clinical model added γ-glutamyl transpeptidase to the modified FDRM. The FDRM showed an estimated AUC of 0.71, and the model's performance improved to an AUC of 0.82 after applying the redefined predictor. Adding clinical features (AUC = 0.83) to the modified FDRM further improved in discrimination, but this was not maintained in the validation data set. External validation was evaluated on population-based cohort data and both modified models performed well, with AUC above 0.82.
Conclusion
The performance of FDRM in the Korean population was found to be acceptable for predicting diabetes, but it was improved when corrected with redefined predictors. The validity of the modified model needs to be further evaluated.

Keyword

Diabetes; Framingham Offspring Study; Probability; Risk Assessment

Figure

• 

  Fig. 1 Study summary.The data sources used in this study, predictive models evaluated, and variables included therein are presented.KoGES = Korean Genome and Epidemiology Study, KoGES-CAVAS = Korean Genome and Epidemiology Study-cardiovascular disease association study, FDRM = Framingham Diabetes Risk Model, HTN = hypertension, TG = triglyceride, HDL-C = high-density lipoprotein cholesterol, FBG = fasting blood glucose, BMI = body mass index, HbA1c = hemoglobin A1c, DM = diabetes mellitus, γ-GTP = γ-glutamyl transpeptidase.

• 

  Fig. 2 Relative importance of features included in the improved predictive models for diabetes. (A) Modified Framingham Diabetes Risk Model and (B) expanded clinical model.HTN was defied as blood pressure ≥ 140/90 mmHg or the use of antihypertensive drugs. Due to the skewed distribution, γ-GTP values were log-transformed. Hypo HDL-C was defined as HDL-C < 40 mg/dL for males and < 50 mg/dL for females. Age, log-transformed γ-GTP, and WBC were included as numerical variables; all of the other variables were binary.HbA1c = hemoglobin A1c, FBG = fasting blood glucose, TG = triglyceride, BMI = body mass index, HTN = hypertension, HDL-C = high-density lipoprotein cholesterol, WBC = white blood cell, γ-GTP = γ-glutamyl transpeptidase.

• 

  Fig. 3 Validation of the FDRM for predicting diabetes and comparison with the modified FDRM and expanded clinical model. (A) Derivation data, (B) internal validation data, (C) temporal validation data, and (D) external validation data.FDRM = Framingham Diabetes Risk Model.

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