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Type 2 diabetes risk equations most predictive for middle-aged patients
Risk equations are more accurate for predicting type 2 diabetes in middle-aged patients than for younger or older groups, researchers found.
“The development of simple yet accurate risk scores is important for risk stratification and prevention by clinical and public health interventions. … However, cohort studies in the USA have generally been limited to specific segments of the population age range,” Maria L. Alva, DPhil, health economist at RTI International in Washington, and colleagues wrote. “The most important sets of risk factors, as well as the relative and absolute risks, may vary considerably by age.”
The researchers used data from three studies to estimate diabetes risk in various age groups: the Coronary Artery Risk Development in Young Adults for patients aged 18 to 40 years (n = 6,912), the Atherosclerosis Risk in Communities equation for patients aged 45 to 64 years (n = 8,875), and the Cardiovascular Health Study for diabetes risk in patients aged 65 years or older (3,094). Alva and colleagues compared performance of simple equations, which relied on demographic information, with that of enhanced equations that used biomarkers, by age group.
Simple risk equations demonstrated an area under the receiver-operating curve (AUROC) of 0.72 for patients aged 18 to 30 years, 0.79 for those aged 28 to 40 years, 0.75 for patients aged 45 to 64 years and 0.69 for those aged 65 years and older, the researchers wrote.
Enhanced equations had better AUROCs, at 0.75 for those aged 18 to 30 years, 0.85 for patients aged 28 to 40 years, 0.85 for patients aged 45 to 64 years and 0.81 for patients 65 years and older.
When the researchers applied risk equations meant for younger populations to older patients, equations tended to underpredict diabetes risk; whereas equations centered on older patients overpredicted diabetes risk in younger populations, according to Alva and colleagues.
“This variability emphasizes the importance of using age-specific risk equations when assessing the need to screen for type 2 diabetes to improve accuracy of individual-level predictions,” the researchers wrote. “Using age-specific risk equations may be especially important for the development of practical risk stratification tools, as well as to provide more precise parameters for cost-effectiveness analyses.” – by Andy Polhamus
Disclosures: The authors report no relevant financial disclosures.