Active-comparator restricted disproportionality analysis for pharmacovigilance signal detection studies of chronic disease medications: An example using sodium/glucose cotransporter 2 inhibitors.


Journal

British journal of clinical pharmacology
ISSN: 1365-2125
Titre abrégé: Br J Clin Pharmacol
Pays: England
ID NLM: 7503323

Informations de publication

Date de publication:
02 2023
Historique:
revised: 25 11 2021
received: 05 10 2021
accepted: 03 12 2021
pubmed: 30 12 2021
medline: 18 1 2023
entrez: 29 12 2021
Statut: ppublish

Résumé

Disproportionality analysis is a common pharmacovigilance tool to detect safety signals of type 2 diabetes medications from spontaneous drug reporting databases. The aim was to demonstrate the impact of using active-comparator restricted disproportionality analysis (ACR-DA), wherein the reference group is restricted to reports with a clinically appropriate active comparator. Using reports from the Food and Drug Administration Adverse Event Reporting System, we assessed if sodium/glucose cotransporter 2 (SGLT2) inhibitors are associated with higher reporting of 5 potential adverse events: acute kidney injury, genitourinary tract infections, diabetic ketoacidosis, fractures, and amputations. For each adverse event, we calculated the proportional reporting ratio (PRR) and adjusted reporting odds ratio (aROR [95% confidence interval, CI]) using 3 types of reference groups: no SGLT2 inhibitor (background risk reference), other diabetes drugs (therapeutic class reference), and dipeptidyl peptidase 4 inhibitors (active comparator reference). Based on ACR-DA, we did not detect a safety signal for acute kidney injury (PRR 0.92 [0.81-1.04]; aROR 0.78 [95% CI 0.72-0.85]) or fractures (PRR 0.44[95% CI 0.17-1.15]; aROR 0.74 [95% CI 0.61-0.91]) associated with SGLT2 inhibitors compared to dipeptidyl peptidase 4 inhibitors. However, we detected safety signals for genitourinary tract infections (PRR 2.75[2.02-3.76]; aROR 2.54[2.26-2.86], diabetic ketoacidosis (PRR 63.85[39.37-103.53; aROR 91.49[70.66-118.48]), and amputations (PRR 52.60 [19.66-140.75]; aROR 22.64 [15.32-33.42]. The use of the proposed ACR-DA to detect safety signals of type 2 diabetes medications may reduce false positive safety signals through careful selection of the comparator which is expected to reduce channelling bias.

Identifiants

pubmed: 34964156
doi: 10.1111/bcp.15178
doi:

Substances chimiques

Dipeptidyl-Peptidase IV Inhibitors 0
Sodium-Glucose Transporter 2 Inhibitors 0
Glucose IY9XDZ35W2
Sodium 9NEZ333N27

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

431-439

Informations de copyright

© 2021 British Pharmacological Society.

Références

Montastruc JL, Sommet A, Bagheri H, Lapeyre-Mestre M. Benefits and strengths of the disproportionality analysis for identification of adverse drug reactions in a pharmacovigilance database. Br J Clin Pharmacol. 2011;72(6):905-908.
Dias P, Penedones A, Alves C, Ribeiro CF, Marques FB. The Role of Disproportionality Analysis of Pharmacovigilance Databases in Safety Regulatory Actions: a Systematic Review. Curr Drug Saf. 2015;10(3):234-250.
Caster O, Aoki Y, Gattepaille LM, Grundmark B. Disproportionality Analysis for Pharmacovigilance Signal Detection in Small Databases or Subsets: Recommendations for Limiting False-Positive Associations. Drug Saf. 2020;43(5):479-487.
Michel C, Scosyrev E, Petrin M, Schmouder R. Can Disproportionality Analysis of Post-marketing Case Reports be Used for Comparison of Drug Safety Profiles? Clin Drug Investig. 2017;37(5):415-422.
Wisniewski AF, Bate A, Bousquet C, et al. Good Signal Detection Practices: Evidence from IMI PROTECT. Drug Saf. 2016;39(6):469-490.
Schneeweiss S, Patrick AR, Stürmer T, et al. Increasing levels of restriction in pharmacoepidemiologic database studies of elderly and comparison with randomized trial results. Med Care. 2007;45(10 Supl 2):S131-S142.
Secrest MH, Platt RW, Dormuth CR, et al. Extreme restriction design as a method for reducing confounding by indication in pharmacoepidemiologic research. Pharmacoepidemiol Drug Saf. 2020;29(Suppl 1):26-34.
Lund JL, Richardson DB, Stürmer T. The active comparator, new user study design in pharmacoepidemiology: historical foundations and contemporary application. Curr Epidemiol Rep. 2015;2(4):221-228.
Grundmark B, Holmberg L, Garmo H, Zethelius B. Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area. Eur J Clin Pharmacol. 2014;70(5):627-635.
Ado Moumouni AN, Robin P, Hillaire-Buys D, Faillie JL. SGLT-2 inhibitors and ketoacidosis: a disproportionality analysis in the World Health Organization's adverse drug reactions database. Fundam Clin Pharmacol. 2018;32(2):216-226.
Perlman A, Heyman SN, Matok I, Stokar J, Muszkat M, Szalat A. Acute renal failure with sodium-glucose-cotransporter-2 inhibitors: Analysis of the FDA adverse event report system database. Nutr Metab Cardiovasc Dis. 2017;27(12):1108-1113.
Fadini GP, Avogaro A. SGLT2 inhibitors and amputations in the US FDA Adverse Event Reporting System. Lancet Diabetes Endocrinol. 2017;5(9):680-681.
Zhao B, Shen J, Zhao J, Pan H. Do sodium-glucose cotransporter 2 inhibitors lead to fracture risk? A pharmacovigilance real-world study. J Diabetes Investig. 2021;12(8):1400-1407.
Patorno E, Patrick AR, Garry EM, et al. Observational studies of the association between glucose-lowering medications and cardiovascular outcomes: addressing methodological limitations. Diabetologia. 2014;57(11):2237-2250.
Alexander SP, Kelly E, Mathie A, et al. THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: Transporters. Br J Pharmacol. 2021;178(Suppl 1):S412-S513.
Ni L, Yuan C, Chen G, Zhang C, Wu X. SGLT2i: beyond the glucose-lowering effect. Cardiovasc Diabetol. 2020;19(1):98.
Lo KB, Gul F, Ram P, et al. The Effects of SGLT2 Inhibitors on Cardiovascular and Renal Outcomes in Diabetic Patients: A Systematic Review and Meta-Analysis. Cardiorenal Med. 2020;10(1):1-10.
Pelletier R, Ng K, Alkabbani W, Labib Y, Mourad N, Gamble JM. Adverse events associated with sodium glucose co-transporter 2 inhibitors: an overview of quantitative systematic reviews. Ther Adv Drug Saf. 2021;12:2042098621989134.
MedEffect Canada. Summary safety review-sodium glucose cotransporter 2 (SGLT-2) Inhibitors INVOKANA (canagliflozin) and FORXIGA (dapagliflozin)-evaluation of a potential risk of acute kidney injury. https://www.canada.ca/en/health-canada/services/drugs-health-products/medeffect-canada/safety-reviews/summary-safety-review-sodium-glucose-cotransporter-2-sglt2-inhibitors-invokana-canagliflozin-forxiga-dapagliflozinl-risk.html (October 2015; accessed 2 August 2019).
MedEffect Canada. Summary safety review-SGLT2 inhibitors (canagliflozin, dapagliflozin, empagliflozin)-assessing the potential risk of bone-related side effects. https://www.canada.ca/en/health-canada/services/drugs-health-products/medeffect-canada/safety-reviews/summary-safety-review-sglt2-inhibitors-canagliflozin-dapagliflozin-empagliflozin-risk-bone.html (November 2016; accessed 2 August 2019).
MedEffect Canada. Summary safety review-SGLT-2 inhibitors (canagliflozin, dapagliflozin, empagliflozin)-assessing the risk of the body producing high levels of acids in the blood (diabetic ketoacidosis). https://www.canada.ca/en/health-canada/services/drugs-health-products/medeffect-canada/safety-reviews/summary-safety-review-sglt2-inhibitors-canagliflozin-dapagliflozin-empagliflozin.html (May 2016; accessed 2 August 2019).
US Food and Drug Administration. FDA confirms increased risk of leg and foot amputations with the diabetes medicine canagliflozin (Invokana, Invokamet, Invokamet XR). https://www.fda.gov/media/104870/download (May 16, 2017; accessed 2 August 2019).
US Food and Drug Administration. FDA revises labels of SGLT2 inhibitors for diabetes to include warnings about too much acid in the blood and serious urinary tract infections. https://www.fda.gov/media/94822/download (May 2015; accessed 28 March 2020).
European Medicines Agency. SGLT2 inhibitors: PRAC makes recommendations to minimise risk of diabetic ketoacidosis. https://www.ema.europa.eu/en/documents/referral/sglt2-inhibitors-article-20-procedure-prac-makes-recommendations-minimise-risk-diabetic-ketoacidosis_en.pdf (February 2016; accessed 18 March 2020).
Alkabbani W, Pelletier R, Gamble JM. Sodium/Glucose Cotransporter 2 Inhibitors and the Risk of Diabetic Ketoacidosis: An Example of Complementary Evidence for Rare Adverse Events. Am J Epidemiol. 2021;190(8):1572-1581.
Li D, Wang T, Shen S, Fang Z, Dong Y, Tang H. Urinary tract and genital infections in patients with type 2 diabetes treated with sodium-glucose co-transporter 2 inhibitors: A meta-analysis of randomized controlled trials. Diabetes Obes Metab. 2017;19(3):348-355.
Liu J, Li L, Li S, et al. Effects of SGLT2 inhibitors on UTIs and genital infections in type 2 diabetes mellitus: a systematic review and meta-analysis. Sci Rep. 2017;7(1):2824.
Dave CV, Schneeweiss S, Patorno E. Comparative risk of genital infections associated with sodium-glucose co-transporter-2 inhibitors. Diabetes Obes Metab. 2019;21(2):434-438.
McGovern AP, Hogg M, Shields BM, et al. Risk factors for genital infections in people initiating SGLT2 inhibitors and their impact on discontinuation. BMJ Open Diabetes Res Care. 2020;8(1):e001238.
Lega IC, Bronskill SE, Campitelli MA, et al. Sodium glucose cotransporter 2 inhibitors and risk of genital mycotic and urinary tract infection: a population-based study of older women and men with diabetes. Diabetes Obes Metab. 2019;21(11):2394-2404.
Chang HY, Singh S, Mansour O, Baksh S, Alexander GC. Association Between Sodium-Glucose Cotransporter 2 Inhibitors and Lower Extremity Amputation Among Patients With Type 2 Diabetes. JAMA Intern Med. 2018;178(9):1190-1198.
Heyward J, Mansour O, Olson L, Singh S, Alexander GC. Association between sodium-glucose cotransporter 2 (SGLT2) inhibitors and lower extremity amputation: A systematic review and meta-analysis. PLoS ONE. 2020;15(6):e0234065.
Yu OHY, Dell'Aniello S, Shah BR, et al. Canadian Network for Observational Drug Effect Studies (CNODES) Investigators. Sodium-Glucose Cotransporter 2 Inhibitors and the Risk of Below-Knee Amputation: A Multicenter Observational Study. Diabetes Care. 2020;43(10):2444-2452.
Ueda P, Svanström H, Melbye M, et al. Sodium glucose cotransporter 2 inhibitors and risk of serious adverse events: nationwide register based cohort study. BMJ. 2018;14(363):k4365.
Iskander C, Cherney DZ, Clemens KK, et al. Use of sodium-glucose cotransporter-2 inhibitors and risk of acute kidney injury in older adults with diabetes: a population-based cohort study. CMAJ. 2020;192(14):E351-E360.
Nadkarni GN, Ferrandino R, Chang A, et al. Acute Kidney Injury in Patients on SGLT2 Inhibitors: A Propensity-Matched Analysis. Diabetes Care. 2017;40(11):1479-1485.
Abrahami D, Douros A, Yin H, Yu OHY, Azoulay L. Sodium-Glucose Cotransporter 2 Inhibitors and the Risk of Fractures Among Patients With Type 2 Diabetes. Diabetes Care. 2019;42(9):e150-e152.
Food and Drug Administration. FDA AEs reporting system (FAERS) public dashboard. https://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Surveillance/AdverseDrugEffects/ucm070093.htm. Published September 2017. Accessed June 9, 2021.
Wu B, Hu Q, Tian F, Wu F, Li Y, Xu T. A pharmacovigilance study of association between proton pump inhibitor and dementia event based on FDA adverse event reporting system data. Sci Rep. 2021;11(1):10709.
Evans SJ, Waller PC, Davis S. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf. 2001;10(6):483-486.
Rothman KJ, Lanes S, Sacks ST. The reporting odds ratio and its advantages over the proportional reporting ratio. Pharmacoepidemiol Drug Saf. 2004;13(8):519-523.
Raschi E, Parisotto M, Forcesi E, et al. Adverse events with sodium-glucose co-transporter-2 inhibitors: A global analysis of international spontaneous reporting systems. Nutr Metab Cardiovasc Dis. 2017;27(12):1098-1107.
Arora A, Jalali RK, Vohora D. Relevance of the Weber effect in contemporary pharmacovigilance of oncology drugs. Ther Clin Risk Manag. 2017;13:1195-1203.
Beulah E, Reddy N, Subeesh V, Maheswari E, Pudi C. Weber effect: an extended analysis for ten years of reporting trends in FDA Adverse Event Reporting System (FAERS). Value Health. 2018;21:S369.
Faillie JL. Case-non-case studies: Principle, methods, bias and interpretation. Therapie. 2019;74(2):225-232.
Bégaud B, Dangoumau J. Pharmacoepidemiology: definitions, problems, methodology. Therapie. 2000;55(1):113-117.
Neha R, Subeesh V, Beulah E, Gouri N, Maheswari E. Existence of Notoriety Bias in FDA Adverse Event Reporting System Database and Its Impact on Signal Strength. Hosp Pharm. 2021;56(3):152-158.
McCoy RG, Van Houten HK, Deng Y, et al. Comparison of Diabetes Medications Used by Adults With Commercial Insurance vs Medicare Advantage, 2016 to 2019. JAMA Netw Open. 2021;4(2):e2035792.
Shin H, Schneeweiss S, Glynn RJ, Patorno E. Trends in First-Line Glucose-Lowering Drug Use in Adults With Type 2 Diabetes in Light of Emerging Evidence for SGLT-2i and GLP-1RA. Diabetes Care. 2021;44(8):1774-1782.
Dave CV, Schneeweiss S, Wexler DJ, Brill G, Patorno E. Trends in Clinical Characteristics and Prescribing Preferences for SGLT2 Inhibitors and GLP-1 Receptor Agonists, 2013-2018. Diabetes Care. 2020;43(4):921-924.
Noguchi Y, Tachi T, Teramachi H. Detection algorithms and attentive points of safety signal using spontaneous reporting systems as a clinical data source. Brief Bioinform. 2021;22(6):1-14.
Pham M, Cheng F, Ramachandran K. A Comparison Study of Algorithms to Detect Drug-Adverse Event Associations: Frequentist, Bayesian, and Machine-Learning Approaches. Drug Saf. 2019;42(6):743-750.
Dijkstra L, Garling M, Foraita R, Pigeot I. Adverse drug reaction or innocent bystander? A systematic comparison of statistical discovery methods for spontaneous reporting systems. Pharmacoepidemiol Drug Saf. 2020;29(4):396-403.

Auteurs

Wajd Alkabbani (W)

School of Pharmacy, University of Waterloo, Kitchener, ON, Canada.

John-Michael Gamble (JM)

School of Pharmacy, University of Waterloo, Kitchener, ON, Canada.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH