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Association of Uterine Leiomyoma with Type 2 Diabetes Mellitus in Young Women: A Population-Based Cohort Study (Diabetes Metab J 2024;48:1105-13)
Zhenzhi Qin1,2, Yan Xu1orcidcorresp_icon
Diabetes & Metabolism Journal 2024;48(6):1179-1180.
DOI: https://doi.org/10.4093/dmj.2024.0552
Published online: November 21, 2024
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1Department of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, China

2Department of Pharmacology, Qingdao University School of Pharmacy, Qingdao, China

corresp_icon Corresponding author: Yan Xu orcid Department of Nephrology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao 266003, China E-mail: xuyan@qdu.edu.cn

Copyright © 2024 Korean Diabetes Association

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 Uterine Leiomyoma with Type 2 Diabetes Mellitus in Young Women: A Population-Based Cohort Study (Diabetes Metab J 2024;48:1105-13)" in Volume 48 on page 1183.
See the article "Association of Uterine Leiomyoma with Type 2 Diabetes Mellitus in Young Women: A Population-Based Cohort Study" on page 1105.
We read with great interest the recent article by Sung et al. [1] titled “Association of uterine leiomyoma with type 2 diabetes mellitus in young women: a population-based cohort study” in Diabetes Metabolism Journal. The study found that young women with uterine leiomyoma had a higher risk of developing type 2 diabetes mellitus (T2DM), and undergoing myomectomy appeared to reduce this risk. However, we note several biases in the use of the cox proportional hazards (CoxPH) model that the authors did not address.
The established criteria may result in mixed censoring outcomes, i.e., right-censoring and interval-censoring events [2,3]. Events of T2DM diagnosed through medical records could result in interval-censoring if they occurred between follow-up visits, and right-censoring for diagnosed between the end of follow-up and the time of data analysis. The CoxPH model primarily handles right-censored data. In contrast, the accelerated failure time (AFT) model is often preferred for scenarios involving various types of censored data [4]. The AFT model can effectively handle left-censored, right-censored, and interval-censored data by appropriately adjusting the likelihood function [5]. By using the ‘survival’ and ‘icenReg’ packages, mixed censored data can be fitted and analyzed, and event times can be estimated [6].
Moreover, the CoxPH model requires the proportional hazards assumption, meaning that covariate effects are constant over time [7]. If this assumption is violated, the model may not provide unbiased estimates of the coefficients, and the predictions may not be reliable. The authors should utilize Schoenfeld residuals or alternative methods to evaluate the proportional hazards assumption for the association between covariates and the risk of T2DM. Schoenfeld residuals are calculated as the differences between the observed and expected values of covariates at each failure time [8]. If the residuals exhibit a systematic change over time, it suggests that the effect of the covariate may be time-dependent. When the proportional hazards assumption does not hold, authors should use a stratified cox model, a cox model with time-varying effects, or an AFT model instead of the standard CoxPH model [4,9].
In conclusion, we believe that a re-evaluation considering the potential impact of censoring events and the proportional hazards assumption is necessary. Further research is anticipated to provide more empirical data and clearer insights into this field.

CONFLICTS OF INTEREST

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

FUNDING

This work was supported by the Taishan Scholar Program of Shandong Province (grant number tstp20230665); the National Natural Science Foundation of China (grant numbers 82270724); the Qingdao Key Health Discipline Development Fund; and the Qingdao Key Clinical Specialty Elite Discipline.

  • 1. Sung JH, Kim KS, Han K, Park CY. Association of uterine leiomyoma with type 2 diabetes mellitus in young women: a population-based cohort study. Diabetes Metab J 2024;48:1105-13.PubMed
  • 2. Thomas LE, Turakhia MP, Pencina MJ. Competing risks, treatment switching, and informative censoring. JAMA Cardiol 2021;6:871-3.ArticlePubMed
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  • 9. 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.ArticlePubMedPMCPDF

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        Association of Uterine Leiomyoma with Type 2 Diabetes Mellitus in Young Women: A Population-Based Cohort Study (Diabetes Metab J 2024;48:1105-13)
        Diabetes Metab J. 2024;48(6):1179-1180.   Published online November 21, 2024
        DOI: https://doi.org/10.4093/dmj.2024.0552
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      DOI: https://doi.org/10.4093/dmj.2024.0552.
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