Evidence map›Paper›PMID 41701303›Full record

ArticleInternational journal of clinical pharmacy2026

Dose-dependent relationships in potential prescribing cascades: a cohort study using community pharmacy dispensing data.

Ruveyda Gündogan-Yilmaz, Sadaf Wahedi, Johanna H M Driessen, Atiya Mohammad, Petra Denig, Fatma Karapinar-Carkit

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Article in International journal of clinical pharmacy, 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ruveyda Gündogan-Yilmaz *Department of Clinical Pharmacy, OLVG, Amsterdam, The Netherlands.
Sadaf Wahedi *Department of Clinical Pharmacy, OLVG, Amsterdam, The Netherlands.
Johanna H M DriessenDepartment of Clinical Pharmacy and Toxicology, Maastricht University Medical Center+, Maastricht, The Netherlands.
Atiya MohammadDepartment of Clinical Pharmacy, OLVG, Amsterdam, The Netherlands.
Petra DenigDepartment of Clinical Pharmacy and Pharmacology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands.
Fatma Karapinar-CarkitDepartment of Clinical Pharmacy, OLVG, Amsterdam, The Netherlands. f.karapinar@mumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPrescribing cascades occur when new medications are initiated to treat adverse drug reactions (ADRs) caused by an initial medication (index). Although using lower dose of the index medication is often recommended as a general strategy to address adverse drug reactions that may trigger potential prescribing cascades, evidence supporting a dose-dependent relationship for many prescribing cascades is limited.

aimThe aim was to examine the dose-dependent relationship across a range of index medications related to various potential prescribing cascades, for which the dose-dependent relationship between the index medication and the ADR was not yet known.

methodA cohort study was conducted using prescription sequence symmetry analysis with data from over 600 Dutch community pharmacies (2015-2020). We assessed 18 potential prescribing cascades involving ACE inhibitors (ACEIs), statins, antidepressants, dihydropyridine calcium channel blockers (DCCBs), and other drug classes. Index medication doses were categorized based on the World Health Organization (WHO) Defined Daily Dose (DDD) into low (< 0.50 DDD), medium (0.50-1.50 DDD), and high (> 1.50 DDD). The adjusted sequence ratio (aSR) quantified the likelihood of marker drug initiation after vs. before the index drug, corrected for prescribing trends; aSR > 1 indicated a potential prescribing cascade.

resultsTwelve of the 18 potential prescribing cascades showed a dose-dependent relationship. All angiotensin converting enzyme inhibitor (ACEI) related cascades demonstrated increasing aSRs with higher doses. ACEIs associated with cough showed increasing aSRs, from 0.86 to 2.09 at low dose to 1.29 to 2.78 at high dose across four cascades. Dose-dependent relationships were also found for statins, antidepressants, and DCCBs. No such relationship was observed for cascades involving proton pump inhibitors, diuretics, and non-steroidal anti-inflammatory drugs.

conclusionMedication dose can play a significant role in potential prescribing cascades. Healthcare professionals should be aware of the potential contribution of dose to prescribing cascade development. The study design precludes causal inference, and confirmation is needed to support further clinical recommendations.

Indexed as

Community Pharmacy ServicesDrug PrescriptionsDrug-Related Side Effects and Adverse ReactionsPractice Patterns, Pharmacists'Cohort StudiesDose-Response Relationship, DrugHumansNetherlandsDrug prescriptionsDrug-related adverse reactionsPharmacoepidemiologyPolypharmacyPrescribing cascades

Identifiers

PMID41701303
PMCPMC13176057

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.