Abstract
Aims
To evaluate major osteoporotic fracture (MOF) risk among type 2 diabetes patients
treated with sodium-glucose cotransporter-2 inhibitors (SGLT2i) across eGFR and albuminuria
categories.
Methods
A population-based cohort of type 2 diabetes patients started on SGLT2i or dipeptidyl
peptidase-4 inhibitors (DPP4i) during 2007–2020 was identified from Hong Kong Hospital
Authority database. One-to-one propensity score matching was applied to match each
SGLT2i user with one DPP4i user. The primary outcomes were 180- and 365-day risks
of MOF. Cox proportional hazard regression models were used to estimate hazard ratios
(HR).
Results
A total of 28,696 patients (14,348 in each group) were included. Over 180-day follow-up,
MOF occurred in 25 (0.17 %) SGLT2i users and 24 (0.17 %) DPP4i users (incidence of
4.07 and 3.63/1,000 person-years, respectively). At 365 days, MOF occurred in 43 (0.30 %)
SGLT2i users and 44 (0.31 %) DPP4i users (incidence of 4.16 and 3.64/1,000 person-years,
respectively). Risks of MOF were comparable between two groups at both 180 days (HR = 1.13,
95 %CI 0.65–1.98, P = 0.67) and 365 days (HR = 1.15, 95 %CI 0.75–1.75, P = 0.52).
Subgroup analyses were consistent across age, sex, eGFR, albuminuria, or KDIGO categories.
Conclusions
Our study did not reveal a statistically significant increase in fracture risk with
SGLT2i use compared with DPP4i among type 2 diabetes patients, across eGFR and albuminuria
categories.
Keywords
Abbreviations:
ASMD (Absolute standardised mean difference), BMI (Body mass index), CCI (Charlson Comorbidity Index), CI (Confidence interval), DBP (Diastolic blood pressure), DPP4i (Dipeptidyl-peptidase 4 inhibitors), eGFR (Estimated glomerular filtration rate), ESKD (End-stage kidney disease), HbA1c (Haemoglobin A1c), HDL-C (High-density lipoprotein cholesterol), HR (Hazard ratio), ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification), ICPC-2 (International Classification of Primary Care, Second Edition), KDIGO (Kidney Disease Improving Global Outcomes), LDL-C (Low-density lipoprotein cholesterol), MICE (Multiple imputation by chained equation), PDC (Proportion of days covered), SBP (Systolic blood pressure), SD (Standard deviation), SGLT2i (Sodium-glucose cotransporter-2 inhibitor), TC (Total cholesterol), TZD (Thiazolidinedione), UACR (Urine albumin/creatinine ratio)To read this article in full you will need to make a payment
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References
- HbA1c variability, in addition to mean HbA1c, predicts incident hip fractures in Chinese people with type 2 diabetes.Osteoporos Int. Oct 2020; 31: 1955-1964https://doi.org/10.1007/s00198-020-05395-z
- Excess mortality for operated geriatric hip fracture in Hong Kong.Hong Kong Med J. Feb 2016; 22: 6-10https://doi.org/10.12809/hkmj154568
International Diabetes Federation. “IDF Diabetes Atlas 11th Edition.” https://diabetesatlas.org (accessed 9 December, 2022).
- Diagnosis and management of bone fragility in diabetes: an emerging challenge.Osteoporos Int. Dec 2018; 29: 2585-2596https://doi.org/10.1007/s00198-018-4650-2
- Bone fragility in patients with diabetes mellitus: A consensus statement from the working group of the Italian Diabetes Society (SID), Italian Society of Endocrinology (SIE), Italian Society of Gerontology and Geriatrics (SIGG), Italian Society of Orthopaedics and Traumatology (SIOT).Nutr Metab Cardiovasc Dis. 2021; 31: 1375-1390https://doi.org/10.1016/j.numecd.2021.01.019
- Hip Fracture Risk According to Diabetic Kidney Disease Phenotype in a Korean Population.Endocrinol Metab (Seoul). Feb 2022; 37: 148-158https://doi.org/10.3803/EnM.2021.1315
- SGLT2 inhibitors and GLP-1 receptor agonists: established and emerging indications.Lancet. 2021; 398: 262-276https://doi.org/10.1016/s0140-6736(21)00536-5
- Kidney outcomes associated with sodium-glucose cotransporter 2 inhibitors versus glucagon-like peptide 1 receptor agonists: A real-world population-based analysis.EClinicalMedicine. Aug 2022; 50101510https://doi.org/10.1016/j.eclinm.2022.101510
K. B. Filion et al., “Sodium glucose cotransporter 2 inhibitors and risk of major adverse cardiovascular events: multi-database retrospective cohort study,” BMJ, vol. 370, p. m3342, Sep 23 2020, doi: 10.1136/bmj.m3342.
- Kidney and heart failure outcomes associated with SGLT2 inhibitor use.Nat Rev Nephrol. May 2022; 18: 294-306https://doi.org/10.1038/s41581-022-00535-6
- The Extraglycemic Effect of SGLT-2is on Mineral and Bone Metabolism and Bone Fracture.Front Endocrinol (Lausanne). 2022; 13918350https://doi.org/10.3389/fendo.2022.918350
- Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes.N Engl J Med. 2017; 377: 644-657https://doi.org/10.1056/NEJMoa1611925
- Sodium-glucose cotransporter 2 inhibitors do not increase the risk of fractures in real-world clinical practice in Korea: A national observational cohort study.J Diabetes Investig. Jun 2022; 13: 986-996https://doi.org/10.1111/jdi.13768
- Rationale, design and baseline characteristics of the CANagliflozin cardioVascular Assessment Study-Renal (CANVAS-R): A randomized, placebo-controlled trial.Diabetes Obes Metab. Mar 2017; 19: 387-393https://doi.org/10.1111/dom.12829
- Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes.N Engl J Med. 2019; 380: 347-357https://doi.org/10.1056/NEJMoa1812389
- Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes.N Engl J Med. 2015; 373: 2117-2128https://doi.org/10.1056/NEJMoa1504720
- Lack of evidence for a harmful effect of sodium-glucose co-transporter 2 (SGLT2) inhibitors on fracture risk among type 2 diabetes patients: a network and cumulative meta-analysis of randomized controlled trials.Diabetes Obes Metab. Dec 2016; 18: 1199-1206https://doi.org/10.1111/dom.12742
M. Zhuo et al., “Association of Sodium-Glucose Cotransporter-2 Inhibitors With Fracture Risk in Older Adults With Type 2 Diabetes,” JAMA Netw Open, vol. 4, no. 10, p. e2130762, Oct 1 2021, doi: 10.1001/jamanetworkopen.2021.30762.
- Fracture Risk of Sodium-Glucose Cotransporter-2 Inhibitors in Chronic Kidney Disease.Clin J Am Soc Nephrol. Jun 2022; 17: 835-842https://doi.org/10.2215/CJN.16171221
- Risk of fracture with dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, or sodium-glucose cotransporter-2 inhibitors in real-world use: systematic review and meta-analysis of observational studies.Osteoporos Int. Oct 2019; 30: 1923-1940https://doi.org/10.1007/s00198-019-04968-x
- ACE (Angiotensin-Converting Enzyme) Inhibitors/Angiotensin Receptor Blockers Are Associated With Lower Colorectal Cancer Risk: A Territory-Wide Study With Propensity Score Analysis.Hypertension. Sep 2020; 76: 968-975https://doi.org/10.1161/HYPERTENSIONAHA.120.15317
- Validity of major osteoporotic fracture diagnosis codes in the Clinical Data Analysis and Reporting System in Hong Kong.Pharmacoepidemiol Drug Saf. Aug 2017; 26: 973-976https://doi.org/10.1002/pds.4208
- Evaluation of Fracture Risk Among Patients With Type 2 Diabetes and Nonvalvular Atrial Fibrillation Receiving Different Oral Anticoagulants.Diabetes Care. 2022; 45: 2620-2627https://doi.org/10.2337/dc22-0664
- Diabetes Management in Chronic Kidney Disease: Synopsis of the 2020 KDIGO Clinical Practice Guideline.Ann Intern Med. Mar 2021; 174: 385-394https://doi.org/10.7326/M20-5938
P. Royston and I. White, “Multiple Imputation by Chained Equations (MICE): Implementation inStata,” Journal of Statistical Software, vol. 45, no. 4, 2011, doi: 10.18637/jss.v045.i04.
- Multiple imputation using chained equations: Issues and guidance for practice.Stat Med. 2011; 30: 377-399https://doi.org/10.1002/sim.4067
- Statistical criteria for selecting the optimal number of untreated subjects matched to each treated subject when using many-to-one matching on the propensity score.Am J Epidemiol. 2010; 172: 1092-1097https://doi.org/10.1093/aje/kwq224
- An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.Multivariate Behav Res. May 2011; 46: 399-424https://doi.org/10.1080/00273171.2011.568786
- Fracture Risk After Initiation of Use of Canagliflozin: A Cohort Study.Ann Intern Med. 2019; 170: 155-163https://doi.org/10.7326/M18-0567
- Diabetes, bone and glucose-lowering agents: clinical outcomes.Diabetologia. Jul 2017; 60: 1170-1179https://doi.org/10.1007/s00125-017-4283-6
- Long-term study of patients with type 2 diabetes and moderate renal impairment shows that dapagliflozin reduces weight and blood pressure but does not improve glycemic control.Kidney Int. Apr 2014; 85: 962-971https://doi.org/10.1038/ki.2013.356
- Renal, Cardiovascular, and Safety Outcomes of Canagliflozin by Baseline Kidney Function: A Secondary Analysis of the CREDENCE Randomized Trial.J Am Soc Nephrol. May 2020; 31: 1128-1139https://doi.org/10.1681/ASN.2019111168
- Dapagliflozin in Patients with Chronic Kidney Disease.N Engl J Med. 2020; 383: 1436-1446https://doi.org/10.1056/NEJMoa2024816
The EMPA-KIDNEY Collaborative Group, et al. Empagliflozin in patients with chronic kidney disease. N Engl J Med Nov;4:2022. doi: 10.1056/NEJMoa2204233.
- Chronic Kidney Disease Increases the Risk of Hip Fracture: A Prospective Cohort Study in Korean Adults.J Bone Miner Res. Jul 2020; 35: 1313-1321https://doi.org/10.1002/jbmr.3997
Article info
Publication history
Published online: February 11, 2023
Accepted:
February 8,
2023
Received in revised form:
January 22,
2023
Received:
December 18,
2022
Identification
Copyright
© 2023 Elsevier B.V. All rights reserved.
