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Identification of Patient Clusters with Distinct Disease Progression Patterns Utilizing a Nationwide Finnish
Kim Nygård1,2, Riitta Ryhänen3, Aaron Kortteenniemi2,4
1City of Helsinki, Helsinki, Finland.
Summary
Personalized care for type 2 diabetes (T2D) is crucial due to high variability. This study identified five patient clusters with distinct disease progression patterns, highlighting the need for comprehensive management including cardiovascular health.
Area of Science:
- Endocrinology
- Public Health
- Clinical Research
Background:
- Type 2 diabetes (T2D) presents with significant clinical variability, necessitating personalized patient care strategies.
- Understanding disease progression patterns is key to optimizing management for the large T2D population.
Purpose of the Study:
- To characterize Finnish patients with T2D, detailing their clinical features, treatment modalities, and disease trajectories.
- To identify distinct patient clusters based on the occurrence of diabetes-related complications and their progression over time.
Main Methods:
- A nationwide cohort of 302,987 adult patients with incident T2D in Finland (2010-2019) was analyzed.
- Data were sourced from national registers and healthcare providers (1996-2021).
- Likelihood-based growth mixture modeling was employed to define patient clusters based on 22 predefined endpoints.
Main Results:
- Five clusters emerged: stable (C1), mild (C2), moderate (C3), rapid (C4), and extremely rapid progression (C5).
- Complication rates varied significantly, with C5 showing a rapid increase in cardiovascular complications and other adverse events.
- Notably, a substantial proportion of patients in rapid progression clusters (C4 and C5) were not on T2D medication.
Conclusions:
- Early diagnosis of comorbidities, especially cardiovascular complications, alongside incident T2D indicates a poor prognosis.
- A comprehensive diabetes care approach, integrating cardiovascular disease management with glycemic control, is strongly supported by these findings.
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