Use of Potentially Nephrotoxic Drugs in Type 2 Diabetes Patients on SGLT2i: A Trajectories Analysis
Corresponding Author
Lanting Yang
Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
Correspondence:
Lanting Yang ([email protected])
Search for more papers by this authorJingchuan Guo
Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, Florida, USA
Search for more papers by this authorSandra L Kane-Gill
Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorNico Gabriel
Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
Search for more papers by this authorKerry M Empey
Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorKangho Suh
Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorLevent Kirisci
Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorInmaculada Hernandez
Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
Search for more papers by this authorCorresponding Author
Lanting Yang
Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
Correspondence:
Lanting Yang ([email protected])
Search for more papers by this authorJingchuan Guo
Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, Florida, USA
Search for more papers by this authorSandra L Kane-Gill
Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorNico Gabriel
Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
Search for more papers by this authorKerry M Empey
Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorKangho Suh
Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorLevent Kirisci
Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Search for more papers by this authorInmaculada Hernandez
Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA
Search for more papers by this authorFunding: The authors received no specific funding for this work.
ABSTRACT
Purpose
To characterize trajectories of nephrotoxic potential (NxP) drug use among older adults with Type 2 Diabetes (T2D) treated with SGLT2is and identify associated patient characteristics.
Methods
Using 2012–2019 Medicare data, we selected patients with T2D who filled at least one prescription for SGLT2is. Index date was the date of the first SGLT2i prescription filled. We quantified the number of drugs with NxP used every month during the first 12 months following the index date. The monthly counts of drugs with NxP were incorporated into the group-based trajectory model to identify groups with similar drug use patterns. Finally, we performed a multinomial logistic regression model to examine the association between patient characteristics and group membership.
Results
The study cohort comprised 8811 Medicare beneficiaries with T2D who initiated SGLT2i during the study period with the mean age 67.5 ± 10.6 years. We identified 3 trajectories NxP drug use: no (n = 2142, 24%), low (n = 4752, 54%) and high (n = 1917, 22%) use of drugs with NxP, with patients falling into these categories based on the number of drugs with NxP they used over the time: no drugs, one drug, or two or more drugs. Age, gender, low-income subsidy eligibility and clinical characteristics were associated with group membership.
Conclusions
We successfully identified three trajectory groups, with a substantial proportion of patients showing low use of drugs with NxP. Both social and clinical factors were associated with the use of NxP drugs.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
The data are not available for transfer as per data use agreement.
Supporting Information
| Filename | Description |
|---|---|
| pds70098-sup-0001-Supinfo.docxWord 2007 document , 20.6 KB |
Data S1. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
References
- 1K. Iglay, H. Hannachi, P. Joseph Howie, et al., “Prevalence and Co-Prevalence of Comorbidities Among Patients With Type 2 Diabetes Mellitus,” Current Medical Research and Opinion 32 (2016): 1243–1252, https://doi.org/10.1185/03007995.2016.1168291.
- 2M. Afkarian, L. R. Zelnick, Y. N. Hall, et al., “Clinical Manifestations of Kidney Disease Among US Adults With Diabetes, 1988-2014,” Journal of the American Medical Association 316 (2016): 602–610, https://doi.org/10.1001/jama.2016.10924.
- 3S. M. Doshi and A. N. Friedman, “Diagnosis and Management of Type 2 Diabetic Kidney Disease,” Clinical Journal of the American Society of Nephrology 12 (2017): 1366–1373, https://doi.org/10.2215/cjn.11111016.
- 4C. Triplitt, “Drug Interactions of Medications Commonly Used in Diabetes,” Diabetes Spectrum: A Publication of the American Diabetes Association 19 (2006): 202–211, https://doi.org/10.2337/diaspect.19.4.202.
10.2337/diaspect.19.4.202 Google Scholar
- 5S. Kumari, S. Jain, and S. Kumar, “Effects of Polypharmacy in Elderly Diabetic Patients: A Review,” Cureus 14 (2022): e29068, https://doi.org/10.7759/cureus.29068.
- 6S. Toth-Manikowski and M. G. Atta, “Diabetic Kidney Disease: Pathophysiology and Therapeutic Targets,” Journal of Diabetes Research 2015 (2015): 697010, https://doi.org/10.1155/2015/697010.
- 7Z. K. Yousif, J. D. Koola, E. Macedo, et al., “Clinical Characteristics and Outcomes of Drug-Induced Acute Kidney Injury Cases,” Kidney International Reports 8 (2023): 2333–2344, https://doi.org/10.1016/j.ekir.2023.07.037.
- 8A. Kaur, G. S. Sharma, and D. R. Kumbala, “Acute Kidney Injury in Diabetic Patients: A Narrative Review,” Medicine 102 (2023): e33888, https://doi.org/10.1097/md.0000000000033888.
- 9M. P. Baruah, B. M. Makkar, V. B. Ghatnatti, and K. Mandal, “Sodium Glucose co-Transporter-2 Inhibitor: Benefits Beyond Glycemic Control,” Indian Journal of Endocrinology and Metabolism 23 (2019): 140–149, https://doi.org/10.4103/ijem.IJEM_160_17.
- 10V. Vallon, “The Mechanisms and Therapeutic Potential of SGLT2 Inhibitors in Diabetes Mellitus,” Annual Review of Medicine 66 (2015): 255–270, https://doi.org/10.1146/annurev-med-051013-110046.
- 11H. Hussein, F. Zaccardi, K. Khunti, et al., “Efficacy and Tolerability of Sodium-Glucose Co-Transporter-2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists: A Systematic Review and Network Meta-Analysis,” Diabetes, Obesity and Metabolism 22 (2020): 1035–1046, https://doi.org/10.1111/dom.14008.
- 12L. Yang, N. Gabriel, I. Hernandez, et al., “Identifying Patients at Risk of Acute Kidney Injury Among Medicare Beneficiaries With Type 2 Diabetes Initiating SGLT2 Inhibitors: A Machine Learning Approach,” Frontiers in Pharmacology 13 (2022): 834743, https://doi.org/10.3389/fphar.2022.834743.
- 13T. A. Zelniker and E. Braunwald, “Cardiac and Renal Effects of Sodium-Glucose co-Transporter 2 Inhibitors in Diabetes: JACC State-Of-The-Art Review,” Journal of the American College of Cardiology 72 (2018): 1845–1855, https://doi.org/10.1016/j.jacc.2018.06.040.
- 14A. J. Scheen, “Sodium-Glucose Cotransporter Type 2 Inhibitors for the Treatment of Type 2 Diabetes Mellitus,” Nature Reviews Endocrinology 16 (2020): 556–577, https://doi.org/10.1038/s41574-020-0392-2.
- 15B. Neal, V. Perkovic, K. W. Mahaffey, et al., “Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes,” New England Journal of Medicine 377 (2017): 644–657, https://doi.org/10.1056/NEJMoa1611925.
- 16B. Zinman, C. Wanner, J. M. Lachin, et al., “Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes,” New England Journal of Medicine 373 (2015): 2117–2128, https://doi.org/10.1056/NEJMoa1504720.
- 17W.-H. Chen, Y. Li, L. Yang, et al., “Geographic Variation and Racial Disparities in Adoption of Newer Glucose-Lowering Drugs With Cardiovascular Benefits Among US Medicare Beneficiaries With Type 2 Diabetes,” PLoS One 19 (2024): e0297208, https://doi.org/10.1371/journal.pone.0297208.
- 18A. Cohen, K. Ioannidis, A. Ehrlich, et al., “Mechanism and Reversal of Drug-Induced Nephrotoxicity on a Chip,” Science Translational Medicine 13 (2021): 582, https://doi.org/10.1126/scitranslmed.abd6299.
- 19M. A. Perazella and L. A. Juncos, “Drug-Induced Osmotic Nephropathy: Add SGLT2-Inhibitors to the List?,” Kidney360 3 (2022): 550–553, https://doi.org/10.34067/KID.0007882021.
- 20L. Yang, N. Gabriel, J. Bian, et al., “Individual and Social Determinants of Adherence to Sodium-Glucose Cotransporter 2 Inhibitor Therapy: A Trajectory Analysis,” Journal of Managed Care and Specialty Pharmacy 29 (2023): 1242–1251, https://doi.org/10.18553/jmcp.2023.29.11.1242.
- 21W. Huang, M. M. Ahmed, E. J. Morris, et al., “Trajectories of Sacubitril/Valsartan Adherence Among Medicare Beneficiaries With Heart Failure,” JACC: Advances 3 (2024): 100958, https://doi.org/10.1016/j.jacadv.2024.100958.
- 22D. S. Nagin, “Group-Based Trajectory Modeling: An Overview,” Annals of Nutrition and Metabolism 65 (2014): 205–210, https://doi.org/10.1159/000360229.
- 23D. S. Nagin and C. L. Odgers, “Group-Based Trajectory Modeling in Clinical Research,” Annual Review of Clinical Psychology 6 (2010): 109–138, https://doi.org/10.1146/annurev.clinpsy.121208.131413.
- 24 Service CfMaM, “Chronic Conditions Data Warehouse Data Dictionaries,” (2020), https://www2.ccwdata.org/web/guest/data-dictionaries.
- 25L. Yang, N. Gabriel, I. Hernandez, A. G. Winterstein, and J. Guo, “Using Machine Learning to Identify Diabetes Patients With Canagliflozin Prescriptions at High-Risk of Lower Extremity Amputation Using Real-World Data,” Pharmacoepidemiology and Drug Safety 30 (2021): 644–651, https://doi.org/10.1002/pds.5206.
- 26B. A. Stottlemyer, K. Z. Abebe, P. M. Palevsky, et al., “Expert Consensus on the Nephrotoxic Potential of 195 Medications in the Non-Intensive Care Setting: A Modified Delphi Method,” Drug Safety 46 (2023): 677–687, https://doi.org/10.1007/s40264-023-01312-5.
- 27Y. Qiao, C. C. Steve Tsang, K. C. Hohmeier, et al., “Association Between Medication Adherence and Healthcare Costs Among Patients Receiving the Low-Income Subsidy,” Value in Health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research 23 (2020): 1210–1217, https://doi.org/10.1016/j.jval.2020.06.005.
- 28 Headquarters THJKFF, “Low-Income Assistance Under the Medicare Drug Benefit,” (2013), https://www-kff-org.pitt.idm.oclc.org/wp-content/uploads/2013/01/7327-05.pdf.
- 29L. Yang, M. Brooks, N. Glynn, Y. Zhang, S. Saba, and I. Hernandez, “Real-World Direct Comparison of the Effectiveness and Safety of Apixaban, Dabigatran, Rivaroxaban, and Warfarin in Medicare Beneficiaries With Atrial Fibrillation,” American Journal of Cardiology 126 (2020): 126–136, https://doi.org/10.1016/j.amjcard.2020.03.034.
- 30M. M. Redfield and B. A. Borlaug, “Heart Failure With Preserved Ejection Fraction: A Review,” Journal of the American Medical Association 329 (2023): 827–838, https://doi.org/10.1001/jama.2023.2020.
- 31S. D. Navaneethan, S. Zoungas, M. L. Caramori, et al., “Diabetes Management in Chronic Kidney Disease: Synopsis of the KDIGO 2022 Clinical Practice Guideline Update,” Annals of Internal Medicine 176 (2023): 381–387, https://doi.org/10.7326/m22-2904.
- 32Z. Szekeres, K. Toth, and E. Szabados, “The Effects of SGLT2 Inhibitors on Lipid Metabolism,” Metabolites 11 (2021): 11, https://doi.org/10.3390/metabo11020087.
- 33D. L. Paterson, J. M. Robson, and M. M. Wagener, “Risk Factors for Toxicity in Elderly Patients Given Aminoglycosides Once Daily,” Journal of General Internal Medicine 13 (1998): 735–739, https://doi.org/10.1046/j.1525-1497.1998.00224.x.
- 34F. C. Enevoldsen, C. F. Christiansen, and S. K. Jensen, “Twenty-Three-Year Trends in the Use of Potentially Nephrotoxic Drugs in Denmark,” Clinical Epidemiology 15 (2023): 275–287, https://doi.org/10.2147/clep.S397415.
- 35Y. Ingrasciotta, J. Sultana, F. Giorgianni, et al., “The Burden of Nephrotoxic Drug Prescriptions in Patients With Chronic Kidney Disease: A Retrospective Population-Based Study in Southern Italy,” PLoS One 9 (2014): e89072, https://doi.org/10.1371/journal.pone.0089072.
- 36S. Ehrmann, J. Helms, A. Joret, et al., “Nephrotoxic Drug Burden Among 1001 Critically Ill Patients: Impact on Acute Kidney Injury,” Annals of Intensive Care 9 (2019): 106, https://doi.org/10.1186/s13613-019-0580-1.
- 37F. Chang, A. M. O'Hare, Y. Miao, and M. A. Steinman, “Use of Renally Inappropriate Medications in Older Veterans: A National Study,” Journal of the American Geriatrics Society 63 (2015): 2290–2297, https://doi.org/10.1111/jgs.13790.
- 38M. Heinjoki, M. Karjalainen, J. Saltevo, et al., “Kidney Function and Nephrotoxic Drug Use Among Older Home-Dwelling Persons With or Without Diabetes in Finland,” BMC Nephrology 21 (2020): 11, https://doi.org/10.1186/s12882-020-1684-4.
- 39M. B. Slater, A. Gruneir, P. A. Rochon, A. W. Howard, G. Koren, and C. S. Parshuram, “Identifying High-Risk Medications Associated With Acute Kidney Injury in Critically Ill Patients: A Pharmacoepidemiologic Evaluation,” Paediatric Drugs 19 (2017): 59–67, https://doi.org/10.1007/s40272-016-0205-1.
- 40S. Orth, M. Nowicki, A. Wiecek, and E. Ritz, “Nephroprotective Effect of ACE Inhibitors,” Drugs 46, no. Suppl 2 (1993): 189–195; discussion 195-186, https://doi.org/10.2165/00003495-199300462-00029.
- 41Y. Lytvyn, K. Kimura, N. Peter, et al., “Renal and Vascular Effects of Combined SGLT2 and Angiotensin-Converting Enzyme Inhibition,” Circulation 146 (2022): 450–462, https://doi.org/10.1161/circulationaha.122.059150.
- 42K. K. Loboz and G. M. Shenfield, “Drug Combinations and Impaired Renal Function—the 'Triple Whammy',” British Journal of Clinical Pharmacology 59 (2005): 239–243, https://doi.org/10.1111/j.0306-5251.2004.2188.x.
- 43F. Lapi, L. Azoulay, H. Yin, S. J. Nessim, and S. Suissa, “Concurrent Use of Diuretics, Angiotensin Converting Enzyme Inhibitors, and Angiotensin Receptor Blockers With Non-Steroidal Anti-Inflammatory Drugs and Risk of Acute Kidney Injury: Nested Case-Control Study,” BMJ 346 (2013): e8525, https://doi.org/10.1136/bmj.e8525.
- 44V. Adhiyaman, M. Asghar, A. Oke, A. D. White, and I. U. Shah, “Nephrotoxicity in the Elderly due to Co-Prescription of Angiotensin Converting Enzyme Inhibitors and Nonsteroidal Anti-Inflammatory Drugs,” Journal of the Royal Society of Medicine 94 (2001): 512–514, https://doi.org/10.1177/014107680109401005.
- 45T. Dreischulte, D. R. Morales, S. Bell, and B. Guthrie, “Combined Use of Nonsteroidal Anti-Inflammatory Drugs With Diuretics and/or Renin-Angiotensin System Inhibitors in the Community Increases the Risk of Acute Kidney Injury,” Kidney International 88 (2015): 396–403, https://doi.org/10.1038/ki.2015.101.
