Early potential safety signals for gliptins and gliflozins using real-world pharmacy data compared to spontaneous reporting

BACKGROUND: Dipeptidyl peptidase 4 inhibitors (DPP4i, gliptins) and sodium-glucose co-transporter 2 inhibitors (SGLT2i, gliflozins) are two oral antidiabetic drug classes that have been widely used in recent decades. Their pharmacological actions have led to the identification of new adverse drug reactions and contraindications. In this context, ambulatory real-world data (RWD) analysis has the potential to detect early signals of suspected adverse drug reactions (ADR) that complement or anticipate risk events. METHODS: We conducted an exploratory pharmacovigilance study based on a multicentre observational cross-sectional survey with retrospective 6-month recall in community pharmacies among patients treated with DPP4i or SGLT2i, using metformin as a control. Candidate drug-event signals identified in the pharmacy dataset collected in 2021 were compared with spontaneous reporting data from the Spanish Agency of Medicines and Medical Devices repository in 2022 and 2024. A validated adaptation of the Bayesian Confidence Propagation Neural Network (BCPNN) methodology was applied in all analyses. RESULTS: Exploratory signals identified in the community pharmacy dataset included sitagliptin-dry mouth (FDR 0.059), empagliflozin-asthenia (0.067), linagliptin-bone fracture (0.077), linagliptin-renal impairment (0.082), dapagliflozin-hyperglycemia (0.088), canagliflozin-pruritus (0.092), dapagliflozin-urinary tract infection (0.096), and alogliptin-exanthematic eruptions (0.100). Some of these findings were already described in the Summaries of Product Characteristics (SmPC), whereas others were not and later showed greater convergence with spontaneous reporting patterns in 2024. These findings should be interpreted as exploratory statistical signals for follow-up, particularly when based on small numbers of reports. CONCLUSIONS: Community pharmacy real-world data may contribute to the early identification of potential safety signals that complement spontaneous reporting systems. Signals detected near the exploratory threshold should be interpreted cautiously and considered candidates for monitoring and further investigation rather than confirmed adverse drug reactions.

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Journal
PLoS ONE
Published
2026-06-25
DOI
https://doi.org/10.1371/journal.pone.0352399
Primary Topic
Pharmacovigilance and Adverse Drug Reactions
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article
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article

Early potential safety signals for gliptins and gliflozins using real-world pharmacy data compared to spontaneous reporting

Carlos Treceño Lobato, María-Isabel Jiménez-Serranía, Sara-Maria Martinez-Gonzalez, Javier Herradon-Muñoz
PLoS ONE
Pharmacovigilance and Adverse Drug Reactions
article

Early potential safety signals for gliptins and gliflozins using real-world pharmacy data compared to spontaneous reporting

Carlos Treceño Lobato, María-Isabel Jiménez-Serranía, Sara-Maria Martinez-Gonzalez, Javier Herradon-Muñoz
article en

Abstract

BACKGROUND: Dipeptidyl peptidase 4 inhibitors (DPP4i, gliptins) and sodium-glucose co-transporter 2 inhibitors (SGLT2i, gliflozins) are two oral antidiabetic drug classes that have been widely used in recent decades. Their pharmacological actions have led to the identification of new adverse drug reactions and contraindications. In this context, ambulatory real-world data (RWD) analysis has the potential to detect early signals of suspected adverse drug reactions (ADR) that complement or anticipate risk events. METHODS: We conducted an exploratory pharmacovigilance study based on a multicentre observational cross-sectional survey with retrospective 6-month recall in community pharmacies among patients treated with DPP4i or SGLT2i, using metformin as a control. Candidate drug-event signals identified in the pharmacy dataset collected in 2021 were compared with spontaneous reporting data from the Spanish Agency of Medicines and Medical Devices repository in 2022 and 2024. A validated adaptation of the Bayesian Confidence Propagation Neural Network (BCPNN) methodology was applied in all analyses. RESULTS: Exploratory signals identified in the community pharmacy dataset included sitagliptin-dry mouth (FDR 0.059), empagliflozin-asthenia (0.067), linagliptin-bone fracture (0.077), linagliptin-renal impairment (0.082), dapagliflozin-hyperglycemia (0.088), canagliflozin-pruritus (0.092), dapagliflozin-urinary tract infection (0.096), and alogliptin-exanthematic eruptions (0.100). Some of these findings were already described in the Summaries of Product Characteristics (SmPC), whereas others were not and later showed greater convergence with spontaneous reporting patterns in 2024. These findings should be interpreted as exploratory statistical signals for follow-up, particularly when based on small numbers of reports. CONCLUSIONS: Community pharmacy real-world data may contribute to the early identification of potential safety signals that complement spontaneous reporting systems. Signals detected near the exploratory threshold should be interpreted cautiously and considered candidates for monitoring and further investigation rather than confirmed adverse drug reactions.

PLoS ONEVol. 21(6)
Universidad Europea Miguel de Cervantes (ES), Technological Institute of Castilla y León (ES), Junta de Castilla y León (ES)
Good health and well-being
Openalex Percentile: Top 9%
Pharmacovigilance and Adverse Drug Reactions
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