The potential of precision diabetology for type 2 diabetes treatment—evidence from a meta-regression for all-cause mortality from large cardiovascular outcome trials
Kuss O, Roden M, Schlesinger S, Hoyer A (2024)
Acta Diabetologica.


**Aims**
Two prerequisites must be met for the precision treatment approach to be beneficial for treated individuals. First, there must be treatment heterogeneity; second, in case of treatment heterogeneity, clinical predictors to identify people who would benefit from one treatment more than from others must be available. There is an established meta-regression approach to assess these two prerequisites that relies on measuring the variability of a clinical outcome after treatment in placebo-controlled randomised trials. We recently applied this approach to the treatment of type 2 diabetes for the clinical outcomes of glycaemic control and body weight and repeat it for the clinical outcome of all-cause mortality.
**Methods**
We performed a meta-regression analysis using digitalized individual participant information on time to death from 10 large cardiovascular outcome trials (7563 deaths from 99,746 participants) on DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT-2 inhibitors with respect to the variability of all-cause mortality and its potential predictors after treatment.
**Results**
The adjusted difference in log(SD) values of time to death between the verum and placebo arms was −0.036 (95%-CI: −0.059; −0.013), showing larger variability of time to death in the placebo arms. No clinical predictors were found to explain treatment heterogeneity.
**Conclusions**
This analysis suggests that the potential of the precision treatment approach in type 2 diabetes is low, at least with regard to improvement of all-cause mortality in population with high cardiovascular risk. This extends our previous findings for the clinical outcomes of glycaemic control and body weight.
Zitieren

Daten bereitgestellt von European Bioinformatics Institute (EBI)
Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
References
Daten bereitgestellt von Europe PubMed Central.
Markieren/ Markierung löschen
Markierte Publikationen
Web of Science
Dieser Datensatz im Web of Science®PMID: 39666113
PubMed | Europe PMC