Time for clinical decision support systems tailoring individual patient therapy to improve renal and cardiovascular outcomes in diabetes and nephropathy
- PMID: 32162661
- PMCID: PMC7066539
- DOI: 10.1093/ndt/gfaa013
Time for clinical decision support systems tailoring individual patient therapy to improve renal and cardiovascular outcomes in diabetes and nephropathy
Abstract
The current guideline treatment for patients with diabetes and nephropathy to lower the high risk of renal and cardiovascular (CV) morbidity and mortality is based on results of clinical studies that have tested new drugs in large groups of patients with diabetes and high renal/CV risk. Although this has delivered breakthrough therapies like angiotensin receptor blockers, the residual renal/CV risk remains extremely high. Many subsequent trials have tried to further reduce this residual renal/CV risk, without much success. Post hoc analyses have indicated that these failures are, at least partly, due to a large variability in response between and within the patients. The current 'group approach' to designing and evaluating new drugs, as well as group-oriented drug registration and guideline recommendations, does not take this individual response variation into account. Like with antibiotics and cancer treatment, a more individual approach is warranted to effectively optimize individual results. New tools to better evaluate the individual risk change have been developed for improved clinical trial design and to avoid trial failures. One of these tools, the composite multiple parameter response efficacy score , is based on monitoring changes in all available risk factors and integrating them into a prediction of ultimate renal and CV risk reduction. This score has also been modelled into a clinical decision support system for use in monitoring and changing the therapy in individual patients to protect them from renal/CV events. In conclusion, future treatment of renal/CV risk in diabetes should transition from an era of 'one size fits all' into the new era of 'a fit for each size'.
Keywords: diabetes; kidney; personalized medicine; response variation.
© The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA.
Figures
References
-
- DCCT_Research_Group, The Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 1993; 329: 977–986 - PubMed
-
- Lewis EJ, Hunsicker LG, Bain RP. et al.; The Collaborative Study Group. The effect of angiotensin-converting-enzyme inhibition on diabetic nephropathy. N Engl J Med 1993; 329: 1456–1462 - PubMed
-
- Brenner BM, Cooper ME, de Zeeuw D. et al. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med 2001; 345: 861–869 - PubMed
-
- Lewis EJ, Hunsicker LG, Clarke WR. et al. Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med 2001; 345: 851–860 - PubMed
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical
