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Peer-reviewedCC BY-NC-ND 4.0Cardiovascular Diabetology

Estimated glucose disposal rate outperforms other insulin resistance surrogate indices in predicting cardiometabolic disease and major adverse cardiovascular events in metabolic dysfunction-associated steatotic liver disease: insights from UK Biobank

  • Zhikang Wu1,2
  • Yiqing Zhang1,3
  • Xin Tan1,2
  • Xinyu Zhou1,2
  • Xiangyu Wang1,2
  • Hezi Jiang1,2
  • Lei Chang1,2
  • Anchen Xu1,2
  • Huimin Fan1,4
  • Yafeng Zhou1,2
4 affiliations
  1. 1Department of Cardiology, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Medical Center of Soochow University, Suzhou, People’s Republic of China
  2. 2Institute for Hypertension, Soochow University, Suzhou, People’s Republic of China
  3. 3Department of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou City, Jiangsu Province, People’s Republic of China
  4. 4Center of Translational Medicine and Clinical Laboratory, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Medical Center of Soochow University, Suzhou, People’s Republic of China
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Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) has rapidly evolved into a pressing global health issue, exacting a formidable and escalating toll on public disease burden. Insulin resistance (IR) serves as a shared pathophysiological pathway for MASLD and cardiometabolic dysfunction. However, the associations between IR surrogate indices, cardiometabolic disease (CMD) and major adverse cardiovascular events (MACE) in MASLD, particularly the comparative predictive performance of these indicators, have yet to be fully elucidated.

Methods: This large-scale prospective study incorporated 127,195 and 149,402 individuals with MASLD from UK Biobank in CMD and MACE cohort, respectively. Kaplan–Meier analysis was employed to estimate CMD and MACE risks across different IR indices quartiles. Cox regression model and restricted cubic splines (RCS) curve were performed to investigate the associations between IR-related indices, CMD and MACE in MASLD, with threshold effect analysis detecting potential inflection points upon observed nonlinear relationships. Additionally, receiver operating characteristic (ROC) analysis and Harrell’s C-index, along with net reclassification index (NRI) and integrated discrimination improvement (IDI), were utilized to compare the predictive capability of estimated glucose disposal rate (eGDR) and other IR indices. Furthermore, subgroup and sensitivity analysis were conducted to validate the robustness of primary findings.

Results: During a median follow-up time of 13.67 and 13.92 years, 29,089 CMD (22.87%) and 15,445 (10.34%) MACE occurred, respectively. Kaplan–Meier curves indicated the risks of CMD and MACE increased progressively in parallel with descending eGDR quartiles (log-rank test, P < 0.001). After multivariable adjustment, eGDR was significantly associated with incident CMD (per 1 SD, HR = 0.70, 95% confidence interval [CI] 0.69–0.72) and MACE (per 1 SD, HR = 0.82, 95% CI 0.80–0.84), which held true across subgroup and sensitivity analyses. RCS analysis revealed the nonlinear associations between eGDR, CMD and MACE, while turning points were identified at 5.377 and 5.215. Notably, eGDR outperformed other IR surrogate indices in predictions for CMD and MACE overall, as corroborated by all evaluation metrics (AUC, Harrell’s C-index, NRI and IDI).

Conclusions: eGDR demonstrated significant relationships with CMD and MACE in MASLD, yielding comparatively better predictive performance across diverse IR surrogate indices, which suggested its potential clinical utility.

Graphical abstract:

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12933-026-03274-1.

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Cite

BibTeXRIS
BibTeX
@article{wu2026estimated,
  title = {{Estimated glucose disposal rate outperforms other insulin resistance surrogate indices in predicting cardiometabolic disease and major adverse cardiovascular events in metabolic dysfunction-associated steatotic liver disease: insights from UK Biobank}},
  author = {Zhikang Wu and Yiqing Zhang and Xin Tan and Xinyu Zhou and Xiangyu Wang and Hezi Jiang and Lei Chang and Anchen Xu and Huimin Fan and Yafeng Zhou},
  journal = {Cardiovascular Diabetology},
  year = {2026},
  month = jul,
  doi = {10.1186/s12933-026-03274-1},
  url = {https://doi.org/10.1186/s12933-026-03274-1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Estimated glucose disposal rate outperforms other insulin resistance surrogate indices in predicting cardiometabolic disease and major adverse cardiovascular events in metabolic dysfunction-associated steatotic liver disease: insights from UK Biobank
AU  - Zhikang Wu
AU  - Yiqing Zhang
AU  - Xin Tan
AU  - Xinyu Zhou
AU  - Xiangyu Wang
AU  - Hezi Jiang
AU  - Lei Chang
AU  - Anchen Xu
AU  - Huimin Fan
AU  - Yafeng Zhou
PY  - 2026
DA  - 2026/07/28
JO  - Cardiovascular Diabetology
DO  - 10.1186/s12933-026-03274-1
UR  - https://doi.org/10.1186/s12933-026-03274-1
AB  - Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) has rapidly evolved into a pressing global health issue, exacting a formidable and escalating toll on public disease burden. Insulin resistance (IR) serves as a shared pathophysiological pathway for MASLD and cardiometabolic dysfunction. However, the associations between IR surrogate indices, cardiometabolic disease (CMD) and major adverse cardiovascular events (MACE) in MASLD, particularly the comparative predictive performance of these indicators, have yet to be fully elucidated.  Methods: This large-scale prospective study incorporated 127,195 and 149,402 individuals with MASLD from UK Biobank in CMD and MACE cohort, respectively. Kaplan–Meier analysis was employed to estimate CMD and MACE risks across different IR indices quartiles. Cox regression model and restricted cubic splines (RCS) curve were performed to investigate the associations between IR-related indices, CMD and MACE in MASLD, with threshold effect analysis detecting potential inflection points upon observed nonlinear relationships. Additionally, receiver operating characteristic (ROC) analysis and Harrell’s C-index, along with net reclassification index (NRI) and integrated discrimination improvement (IDI), were utilized to compare the predictive capability of estimated glucose disposal rate (eGDR) and other IR indices. Furthermore, subgroup and sensitivity analysis were conducted to validate the robustness of primary findings.  Results: During a median follow-up time of 13.67 and 13.92 years, 29,089 CMD (22.87%) and 15,445 (10.34%) MACE occurred, respectively. Kaplan–Meier curves indicated the risks of CMD and MACE increased progressively in parallel with descending eGDR quartiles (log-rank test, P < 0.001). After multivariable adjustment, eGDR was significantly associated with incident CMD (per 1 SD, HR = 0.70, 95% confidence interval [CI] 0.69–0.72) and MACE (per 1 SD, HR = 0.82, 95% CI 0.80–0.84), which held true across subgroup and sensitivity analyses. RCS analysis revealed the nonlinear associations between eGDR, CMD and MACE, while turning points were identified at 5.377 and 5.215. Notably, eGDR outperformed other IR surrogate indices in predictions for CMD and MACE overall, as corroborated by all evaluation metrics (AUC, Harrell’s C-index, NRI and IDI).  Conclusions: eGDR demonstrated significant relationships with CMD and MACE in MASLD, yielding comparatively better predictive performance across diverse IR surrogate indices, which suggested its potential clinical utility.  Graphical abstract:  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12933-026-03274-1.
SN  - 1475-2840
ER  -