Competing Risks Model to Evaluate Dropout Dynamics Among the Type 1 Diabetes Patients Registered with the Changing Diabetes in Children (CDiC) Program

Abstract

Understanding the survival dynamics of registered patients on a disease control program is a vital issue for the success of program objectives. Dropout of registered patients from such a program is a critical issue, hindering the effectiveness of the program. This study aimed to identify the risk factors of dropout of patients who were registered on the Changing Diabetes in Children (CDiC) program, taking a case of Uganda. Survival analysis was done by integrating competing risk of factors associated with attrition from the CDiC program. The data for the study was obtained from patients with type 1 diabetes mellitus (T1DM) registered during 2009-2018 at health units with specialized pediatric diabetes clinics from various regions in Uganda. The study considered follow-up data of 1132 children with T1DM. Our analysis revealed that the Body Mass Index (BMI) significantly influences dropout time, with patients classified as underweight showing higher hazards than those with normal BMI. Moreover, when considering competing risks, dropout hazards increased. Comparing the Cox model with the Fine and Gray model shows the latter exhibiting a smaller AIC value, which indicates its superiority in the time-to-dropout analysis. Thus, utilizing methods that integrate competing risks for CDiC dropout analysis is preferable and recommended for related studies. These findings provide actionable insights for enhancing CDiC program efficacy.