American Diabetes Association
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Potential Value of Identifying Type 2 Diabetes Subgroups for Guiding Intensive Treatment: A Comparison of Novel Data-Driven Clustering to Risk-driven Subgroups

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posted on 2023-05-08, 20:04 authored by Xinyu Li, Anoukh van Giessen, James Altunkaya, Roderick C. Slieker, Joline W.J. Beulens, Leen M. ‘t Hart, Ewan R. Pearson, Petra J. M. Elders, Talitha L. Feenstra, Jose Leal



To estimate the impact on lifetime health and economic outcomes of different methods of stratifying individuals with type 2 diabetes, followed by guideline-based treatment intensification, targeting BMI and LDL in addition to HbA1c. 


We divided 2,935 newly diagnosed individuals from the Hoorn Diabetes Care System (DCS) cohort into five RHAPSODY data-driven clustering subgroups (based on age, BMI, HbA1c, C-peptide and HDL) and four risk-driven subgroups using fixed cut-offs for HbA1c and risk of cardiovascular disease based on guidelines. The UKPDS Outcomes Model 2 estimated discounted expected lifetime complication costs and quality-adjusted life-years (QALYs) for each subgroup and across all individuals. Gains from treatment intensification were compared to “care-as-usual” as observed in DCS. A sensitivity analysis was conducted based on Ahlqvist’s subgroups.


Under care-as-usual, prognosis in the RHAPSODY data-driven subgroups ranged from 7.9 to 12.6 QALYs. Prognosis in the risk-driven subgroups ranged from 6.8 to 12.0 QALYs. Compared to homogenous type 2 diabetes, treatment for individuals in high-risk subgroups could cost 22.0% and 25.3% more and still be cost-effective for data-driven and risk-driven subgroups respectively. Targeting BMI and LDL in addition to HbA1c might deliver up to ten-fold increases in QALYs gained.


Risk-driven subgroups better discriminated regarding prognosis. Both stratification methods supported stratified treatment intensification, with the risk-driven subgroups being somewhat better in identifying individuals with the most potential to benefit from intensive treatment. Irrespective of stratification approach, better cholesterol and weight control showed substantial potential for health gains. 


This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115881 (RHAPSODY). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This work is supported by the Swiss State Secretariat for Education‚ Research and Innovation (SERI) under contract number 16.0097. The opinions expressed and arguments employed herein do not necessarily reflect the official views of these funding bodies. The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the manuscript.