Association of Systolic and Diastolic Blood Pressure with the Risk of End-Stage Renal Disease in Older Type 2 Diabetes Mellitus Patients without Cardiovascular Disease: A Nationwide Population-Based Study (Diabetes Metab J 2025;49:1308-17)

Zhi Wang; Leping Shao

doi:10.4093/dmj.2025.0962

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Letter Association of Systolic and Diastolic Blood Pressure with the Risk of End-Stage Renal Disease in Older Type 2 Diabetes Mellitus Patients without Cardiovascular Disease: A Nationwide Population-Based Study (Diabetes Metab J 2025;49:1308-17): Zhi Wang, Leping Shao; Diabetes & Metabolism Journal 2026;50(2):416-417.
DOI: https://doi.org/10.4093/dmj.2025.0962
Published online: March 1, 2026

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Department of Nephrology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China

Corresponding author: Leping Shao

Department of Nephrology, The First Affiliated Hospital of XiamenUniversity, School of Medicine, Xiamen University, Xiamen, China E-mail: lepingshao@xmu.edu.cn

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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See the reply "Association of Systolic and Diastolic Blood Pressure with the Risk of End-Stage Renal Disease in Older Type 2 Diabetes Mellitus Patients without Cardiovascular Disease: A Nationwide Population-Based Study (Diabetes Metab J 2025;49:1308-17)" in Volume 50 on page 430.

See the article "Association of Systolic and Diastolic Blood Pressure with the Risk of End-Stage Renal Disease in Older Type 2 Diabetes Mellitus Patients without Cardiovascular Disease: A Nationwide Population-Based Study" on page 1308.

We read with great interest the recent article by Hong et al. [1] titled “Association of systolic and diastolic blood pressure with the risk of end-stage renal disease in older type 2 diabetes mellitus patients without cardiovascular disease: a nationwide population-based study” in Diabetes & Metabolism Journal. The study’s use of the South Korean National Health Insurance Database provides a valuable, population-based analysis of this important clinical question. However, we would like to highlight a potential methodological limitation regarding the analysis.

First, the study uses the Cox proportional hazards (CoxPH) model to estimate risks. The validity of this model depends on its core proportional hazards (PH) assumption, which states that the effect of a covariate remains constant over the entire follow-up period [2]. If this assumption is violated, the model may not provide unbiased estimates of the coefficients, and its predictions could be unreliable. Therefore, we suggest assessing the PH assumption for the association between covariates and mortality risk using Schoenfeld residuals or other methods [3]. If the residuals show a systematic pattern over time, it would indicate that the covariate’s effect may be time-dependent. When the PH assumption does not hold, using a stratified Cox model, a Cox model with time-varying effects, or an accelerated failure time model would be more appropriate than the standard CoxPH model [4,5]. Verifying and discussing this key assumption would greatly enhance readers’ confidence in the robustness of the findings.

Second, the analysis does not appear to adequately account for the competing risk of mortality. standard Kaplan-Meier estimates of cumulative incidence may be biased, as the method assumes that different event types are independent [6]. The study cohort, consisting of diabetic patients aged 65 and older, remains at high risk for cardiovascular mortality during the 9-year follow-up, even after excluding individuals with a prior history of stroke or myocardial infarction. This approach is susceptible to competing risk bias, which can be substantial in a population with high mortality. Given this, the investigators might also consider trying statistical methods designed for competing risks data. For example, using Gray’s test to compare cumulative incidence curves between groups and exploring regression modeling directly on the cumulative incidence function (e.g., the Fine-Gray model) could provide a supplementary perspective for the interpretation of the results [6,7].

In conclusion, we believe that a re-evaluation considering the potential impact of the competing risk and the PH assumption is necessary.

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CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

REFERENCES

1. Hong S, Han K, Park KY, Lee CB, Kim DS, Park JH, et al. Association of systolic and diastolic blood pressure with the risk of end-stage renal disease in older type 2 diabetes mellitus patients without cardiovascular disease: a nationwide population-based study. Diabetes Metab J 2025;49:1308-17.Article PubMed PMC PDF
2. Sheng A, Ghosh SK. Effects of proportional hazard assumption on variable selection methods for censored data. Stat Biopharm Res 2020;12:199-209.Article PubMed PMC
3. Xue X, Xie X, Gunter M, Rohan TE, Wassertheil-Smoller S, Ho GY, et al. Testing the proportional hazards assumption in case-cohort analysis. BMC Med Res Methodol 2013;13:88.Article PubMed PMC PDF
4. Blythe R, Parsons R, Barnett AG, Cook D, McPhail SM, White NM. Prioritising deteriorating patients using time-to-event analysis: prediction model development and internal-external validation. Crit Care 2024;28:247.Article PubMed PMC PDF
5. Lee KH, Rondeau V, Haneuse S. Accelerated failure time models for semi-competing risks data in the presence of complex censoring. Biometrics 2017;73:1401-12.Article PubMed PMC PDF
6. Kim HT. Cumulative incidence in competing risks data and competing risks regression analysis. Clin Cancer Res 2007;13(2 Pt 1):559-65.Article PubMed PDF
7. Gregson J, Pocock SJ, Anker SD, Bhatt DL, Packer M, Stone GW, et al. Competing risks in clinical trials: do they matter and how should we account for them? J Am Coll Cardiol 2024;84:1025-37.PubMed

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Association of Systolic and Diastolic Blood Pressure with the Risk of End-Stage Renal Disease in Older Type 2 Diabetes Mellitus Patients without Cardiovascular Disease: A Nationwide Population-Based Study (Diabetes Metab J 2025;49:1308-17)

Diabetes Metab J. 2026;50(2):416-417. Published online March 1, 2026

DOI: https://doi.org/10.4093/dmj.2025.0962

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Wang Z, Shao L. Association of Systolic and Diastolic Blood Pressure with the Risk of End-Stage Renal Disease in Older Type 2 Diabetes Mellitus Patients without Cardiovascular Disease: A Nationwide Population-Based Study (Diabetes Metab J 2025;49:1308-17). Diabetes Metab J. 2026;50(2):416-417.

DOI: https://doi.org/10.4093/dmj.2025.0962.

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