Background: The subjective experiences of individuals living with diabetes is commonly assessed with patient-reported outcomes (PROs; eg, depression symptoms, wellbeing, health-related quality of life [HRQOL], and diabetes-related distress). Cluster analyses have identified novel diabetes subtypes differing in phenotypic and metabolic characteristics. We aimed to investigate associations between these subtypes and PROs and whether subtype predicted PROs 5 years later.
Methods: Baseline (<12 months after a diabetes diagnosis) and 5-year follow-up data were collected from German Diabetes Study (GDS) participants. Multiple regressions were applied to analyse associations between diabetes subtypes and depression symptoms (Center for Epidemiologic Studies Depression Scale), wellbeing (WHO-5), HRQOL (SF-36), and diabetes-related distress (Problem Areas in Diabetes Scale).
Findings: Cluster analyses at baseline (n=1391) identified participants with severe autoimmune diabetes (SAID, 417 [30%]), severe insulin-deficient diabetes (SIDD, 33 [2%]), severe insulin-resistant diabetes (SIRD, 150 [11%]), mild obesity-related diabetes (MOD, 354 [25%]), and mild age-related diabetes (MARD, 437 [31%]). At baseline, multiple regression analyses showed that participants with SIRD had higher depression symptoms than participants with MARD and lower physical HRQOL than all other subtypes. Participants with SAID reported higher depression symptoms and lower mental HRQOL than participants with MARD, higher physical HRQOL than participants with MARD and MOD, and higher diabetes-related distress than most other subtypes. At the 5-year follow-up, clustering predicted no statistically significant changes in PROs after adjustment for multiple testing, whereas descriptive analyses demonstrated that individuals with SIRD were more likely to experience clinically relevant depression symptoms (16% vs 6%) and low wellbeing (31% vs 14%), respectively, than individuals with MARD.
Interpretation: Diabetes subtypes already differ in PROs at diabetes diagnosis. Our analyses had limited predictive power during follow-up. However, our findings suggest that clustering could predict future changes in depression symptoms.
Funding: The GDS was initiated and financed by the German Diabetes Center, which is funded by the German Federal Ministry of Health, the Ministry of Culture and Science of the state of North Rhine-Westphalia, and by the German Federal Ministry of Education and Research to the German Center for Diabetes Research.
Translation: For the German translation of the abstract see Supplementary Materials section.
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.