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. 2011 Jul;65(7):613-20.
doi: 10.1136/jech.2009.102244. Epub 2010 Jun 1.

A population-based risk algorithm for the development of diabetes: development and validation of the Diabetes Population Risk Tool (DPoRT)

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A population-based risk algorithm for the development of diabetes: development and validation of the Diabetes Population Risk Tool (DPoRT)

Laura C Rosella et al. J Epidemiol Community Health. 2011 Jul.

Abstract

Background: National estimates of the upcoming diabetes epidemic are needed to understand the distribution of diabetes risk in the population and to inform health policy.

Objective: To create and validate a population-based risk prediction tool for incident diabetes using commonly collected national survey data.

Methods: With the use of a cohort design that links baseline risk factors to a validated population-based diabetes registry, a model (Diabetes Population Risk Tool (DPoRT)) was developed to predict 9-year risk for diabetes. The probability of developing diabetes was modelled using sex-specific Weibull survival functions for people > 20 years of age without diabetes (N=19,861). The model was validated in two external cohorts in Ontario (N=26,465) and Manitoba (N=9899). Predictive accuracy and model performance were assessed by comparing observed diabetes rates with predicted estimates. Discrimination and calibration were measured using a C statistic and Hosmer-Lemeshow χ² statistic (χ²(H-L)).

Results: Predictive factors included were body mass index, age, ethnicity, hypertension, immigrant status, smoking, education status and heart disease. DPoRT showed good discrimination (C=0.77-0.80) and calibration (χ²(H-L) < 20) in both external validation cohorts.

Conclusions: This algorithm can be used to estimate diabetes incidence and quantify the effect of interventions using routinely collected survey data.

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Conflict of interest statement

Competing interests: None.

Figures

Figure 1
Figure 1
Example use of the Diabetes Population Risk Tool to predict the 9-year risk of diabetes for a specific high-risk man.
Figure 2
Figure 2
Predicted 10 versus observed incidence of diabetes for men and women in two validation datasets across deciles or quintiles of risk. The x axis refer to quantile (decile or quintile) of predicted Diabetes Population Risk Tool (DPoRT). The y axis refers to the observed (bars) and DPoRT-predicted (dotted line) probability of developing Diabetes Mellitus (DM) in a 5-year period for Ontario and a 9-year period for Manitoba. Observed diabetes rates are physician-diagnosed diabetes rates in the same time period. CCHS, Canadian Community Health Survey; DPoRT, Diabetes Population Risk Tool; NPHS, National Population Health Survey.

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