1. Frailty modeling under a selective sampling protocol: an application to type 1 diabetes related autoantibodies
- Author
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Jorma Ilonen, Heikki Hyöty, Riitta Veijola, Mikael Knip, Somnath Datta, Jorma Toppari, Suvi M. Virtanen, Jaakko Nevalainen, Tampere University, Health Sciences, BioMediTech, Department of Paediatrics, Tays Research Services, HUS Children and Adolescents, Children's Hospital, Lastentautien yksikkö, and University of Helsinki
- Subjects
Statistics and Probability ,Oncology ,incomplete data ,YOUNG-CHILDREN ,medicine.medical_specialty ,Multivariate statistics ,type 1 diabetes ,Epidemiology ,AUTOIMMUNITY ,PROGRESSION ,030209 endocrinology & metabolism ,SUSCEPTIBILITY ,01 natural sciences ,Cohort Studies ,Correlation ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,multivariate survival analysis ,Risk Factors ,Internal medicine ,111 Mathematics ,medicine ,Humans ,0101 mathematics ,correlated data ,Autoantibodies ,RISK ,Type 1 diabetes ,Frailty ,Mechanism (biology) ,business.industry ,Autoantibody ,medicine.disease ,3142 Public health care science, environmental and occupational health ,Regression ,3. Good health ,HLA ,3141 Health care science ,Diabetes Mellitus, Type 1 ,PATTERNS ,3111 Biomedicine ,business ,Cohort study - Abstract
In studies following selective sampling protocols for secondary outcomes, conventional analyses regarding their appearance could provide misguided information. In the large type 1 diabetes prevention and prediction (DIPP) cohort study monitoring type 1 diabetes-associated autoantibodies, we propose to model their appearance via a multivariate frailty model, which incorporates a correlation component that is important for unbiased estimation of the baseline hazards under the selective sampling mechanism. As further advantages, the frailty model allows for systematic evaluation of the association and the differences in regression parameters among the autoantibodies. We demonstrate the properties of the model by a simulation study and the analysis of the autoantibodies and their association with background factors in the DIPP study, in which we found that high genetic risk is associated with the appearance of all the autoantibodies, whereas the association with sex and urban municipality was evident for IA-2A and IAA autoantibodies. publishedVersion
- Published
- 2021
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