A simple risk score effectively predicted type 2 diabetes in Iranian adult population: population-based cohort study.

BACKGROUND

Although several strategies to predict the development of diabetes have been developed the question is whether better scores can be developed without sacrificing simplicity.

METHODS

Data on 3242 participants of Tehran Lipid and Glucose Study aged ≥20 years, without diabetes at the baseline that completed a ~6-year follow-up were used to develop prediction models by running a series of logistic regression model. A simple score system was then developed based on the most important variables selected with forward stepwise approach.

RESULTS

During follow-up, 231 individuals developed diabetes. The area under the receiver operating characteristic curve for the score system based on the model including systolic blood pressure (SBP), family history of diabetes, waist-to-height ratio (WHtR), triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C) ≥3.5 and fasting plasma glucose (FPG) levels ≥5 mmol l(-1) was 0.83 (95% CI 0.80-0.86); the model discriminated subjects with substantial risk for diabetes, appreciably better than 2-h post-challenge plasma glucose (2h-PCPG) alone (0.78; 95% CI 0.75-0.82) (P < 0.001). Scoring ≥25 yielded a positive likelihood ratio of 3.27. FPG levels even in the presence of 2h-PCPG predicted incident diabetes.

CONCLUSION

We presented a simple model based on SBP, family history of diabetes, WHtR, TG/HDL-C and FPG; concluding that this approach is superior to relying exclusively on the 2h-PCPG for identifying individuals at high risk for developing diabetes in a Middle Eastern adult population.