External validation of prognostic models for chronic kidney disease among type 2 diabetes
Issued Date
2022-07-01
Resource Type
ISSN
11218428
eISSN
17246059
Scopus ID
2-s2.0-85122691941
Pubmed ID
34997924
Journal Title
Journal of Nephrology
Volume
35
Issue
6
Start Page
1637
End Page
1653
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Nephrology Vol.35 No.6 (2022) , 1637-1653
Suggested Citation
Saputro S.A., Pattanateepapon A., Pattanaprateep O., Aekplakorn W., McKay G.J., Attia J., Thakkinstian A. External validation of prognostic models for chronic kidney disease among type 2 diabetes. Journal of Nephrology Vol.35 No.6 (2022) , 1637-1653. 1653. doi:10.1007/s40620-021-01220-w Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/85783
Title
External validation of prognostic models for chronic kidney disease among type 2 diabetes
Other Contributor(s)
Abstract
Background: Various prognostic models have been derived to predict chronic kidney disease (CKD) development in type 2 diabetes (T2D). However, their generalisability and predictive performance in different populations remain largely unvalidated. This study aimed to externally validate several prognostic models of CKD in a T2D Thai cohort. Methods: A nationwide survey was linked with hospital databases to create a prospective cohort of patients with diabetes (n = 3416). We undertook a systematic review to identify prognostic models and traditional metrics (i.e., discrimination and calibration) to compare model performance for CKD prediction. We updated prognostic models by including additional clinical parameters to optimise model performance in the Thai setting. Results: Six relevant previously published models were identified. At baseline, C-statistics ranged from 0.585 (0.565–0.605) to 0.786 (0.765–0.806) for CKD and 0.657 (0.610–0.703) to 0.760 (0.705–0.816) for end-stage renal disease (ESRD). All original CKD models showed fair calibration with Observed/Expected (O/E) ratios ranging from 0.999 (0.975–1.024) to 1.009 (0.929–1.090). Hosmer–Lemeshow tests indicated a good fit for all models. The addition of routine clinical factors (i.e., glucose level and oral diabetes medications) enhanced model prediction by improved C-statistics of Low’s of 0.114 for CKD and Elley’s of 0.025 for ESRD. Conclusions: All models showed moderate discrimination and fair calibration. Updating models to include routine clinical factors substantially enhanced their accuracy. Low’s (developed in Singapore) and Elley’s model (developed in New Zealand), outperformed the other models evaluated. These models can assist clinicians to improve the risk-stratification of diabetic patients for CKD and/or ESRD in the regions settings are similar to Thailand. Graphical abstract: [Figure not available: see fulltext.]