medwireNews: Testing high-risk children for islet autoantibodies twice, at the ages of 2 and 6 years, is sufficient to predict the majority of clinical cases of type 1 diabetes diagnosed by the age of 15, a study suggests.
“We showed that screening at just two early ages detected four of five cases of future childhood type 1 diabetes and might be practical for public health implementation,” say William Hagopian (Pacific Northwest Research Institute, Seattle, Washington, USA) and co-researchers.
The team found that screening children with high genetic risk at these young ages identified those who developed diabetes when very young, but also those with slower-progressing disease, who developed diabetes in later childhood, a relatively long time after first autoantibody detection.
The study involved participants of the Finnish Type 1 Diabetes Prediction and Prevention study, the Swedish Diabetes Prediction in Skåne Study, the Diabetes Autoimmunity Study in the Young from Colorado, USA, the Diabetes Evaluation in Washington study, and the German BABYDIAB cohort.
This gave data on 672 children who developed diabetes by the age of 15 years and 6050 who were followed up to that age but remained free of the condition. They each had a median of 18 samples analyzed for autoantibodies.
The researchers found that screening at two ages gave more accurate results than screening at one age. The best result came from screening for any autoantibodies at the ages of 2 and 6 years, which detected 82% of all cases (sensitivity), and 79% of the children who had autoantibodies at one of these ages went on to develop diabetes by the age of 15 (positive predictive value; PPV).
“We believe this PPV is acceptably high for initial paediatric screening, especially when complemented by timely follow-up evaluation,” write Hagopian and team in The Lancet Diabetes & Endocrinology.
They note, however, that the sensitivities and PPVs varied somewhat between countries, suggesting that their screening approach “might require adjustment by country on the basis of population-specific disease characteristics.”
In a linked commentary, Maria Redondo (Texas Children's Hospital, Houston, USA) calls the results “acceptable for a screening strategy, in which the individuals ascertained would receive education, additional testing to refine the prediction, and monitoring for progression to clinical disease.”
However, she queried whether the approach “could work in the general population because all the participants in the combined dataset had genetic risk factors for the disease or a relative with type 1 diabetes, in whom performance is expected to be higher.”
And she added: “Furthermore, most participants were of northern European ancestry and, given the known differences in type 1 diabetes epidemiology and pathogenesis, other ancestries must be studied.”
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