Prediction models for celiac disease development in children from high-risk families: Data from the PreventCD cohort

Background and aims: Screening for celiac disease (CD) is recommended in children with affected first-degree relatives (FDR). However, the frequency of screening and at what age remain unknown. Aims: to detect variables influencing the risk of CD-development and develop and validate clinical prediction models to provide individualized screening advice. Methods: Analysis of prospective data from the ten years follow-up of the PreventCD-birth cohort involving 944 genetically predisposed children with CD-FDR. Variables significantly influencing the CD-risk were combined to determine a risk score. Landmark analyses were performed at different ages. Prediction models were created by multivariable Cox proportional hazards regression analyses, backward elimination and Harrell's c-index for discrimination. Validation was done using data from the independent NeoCel cohort. Results: In March 2019, the median follow-up was 8.3 years (22 days-12.0 years); 135/944 children developed CD (mean age 4.3years (1.1-11.4). CD developed significantly more often in girls (p=0.005) and in HLA-DQ2 homozygous individuals (8-year cumulative incidence 35.4% versus maximum of the other HLA-risk groups 18.2% [P<0.001]). The effect of homozygosity DR3-DQ2/DR7-DQ2 on CD-developing was only present in girls (interaction p=0.04). The prediction models showed good fitting in the validation cohort (Cox regression 0.81(0.54)). To calculate a personalized risk of CD-development and provide screening advice, we designed the Prediction application https://hputter.shinyapps.io/preventcd/. Conclusion: Children with CD-FDR develop CD early in life, and their risk depends on gender, age and HLA-DQ:all factors which are important for a sound screening advice. These children should be screened early in life, including HLA-DQ2/8-typing, and if genetically predisposed to CD, should get further personalized screening advice using our Prediction app.