ArticleAge and ageing2026
Prescription cascades associated with acetylcholinesterase inhibitors use: a high-throughput sequence symmetry analysis.
Article in Age and ageing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAcetylcholinesterase inhibitors (AChEIs), are commonly prescribed for dementia and can cause adverse drug events that may lead to new prescriptions, known as prescription cascades. We aimed to identify potential AChEI-induced prescription cascades using high-throughput sequence symmetry analysis (SSA).
methodsPatients aged ≥18 years with 365 days of prior observation initiating AChEIs (donepezil, rivastigmine, or galantamine) were identified from the Clinical Practice Research Datalink GOLD (2002-2022). We screened 510 drug classes and 1213 individual ingredients initiated within ±180 days of AChEI initiation (365 days in sensitivity analyses). Crude and adjusted sequence ratios (ASRs) were calculated, and positive signals were reviewed for clinical plausibility.
resultsWe identified 66 155 AChEI initiators (median age 81 years [IQR 76-85]; 62.8% female). Among ATC classes and individual ingredients, 51 and 46 signals were positive with 28 (55%) and 22 (48%) classified as potential prescription cascades after review. Gastrointestinal drugs showed positive signals including antipropulsives (ASR 1.50 [99% CI 1.28-1.75]), loperamide (ASR 1.52 [1.30-1.77]) and cyclizine (ASR 2.10 [1.72-2.59]). Positive signals were also observed nervous system drugs such as benzodiazepine derivatives (ASR 1.83 [1.55-2.16]) and respiratory drugs including corticosteroids (ASR 1.66 [1.33-2.08]) and glucocorticoids (ASR 1.54 [1.30-1.83]). Most positive signals remained in sensitivity analysis.
conclusionsThese findings suggest potential AChEI-related prescription cascades consistent with gastrointestinal, neuropsychiatric, dermatological and respiratory adverse effects. While findings require further validation, this study demonstrates the utility of high-throughput signal detection to support pharmacovigilance in high-risk populations.
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