Evidence map›Paper›PMID 35172017›Full record

ArticlePaediatric and perinatal epidemiology2022

Prescribed medicine use and extent of off-label use according to age in a nationwide sample of Australian children.

Andrea L Schaffer, Claudia Bruno, Nicholas A Buckley, Rose Cairns, Melisa Litchfield, Simon Paget, Helga Zoega, Natasha Nassar, Sallie-Anne Pearson

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Paediatric and perinatal epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Andrea L SchafferCentre for Big Data Research in Health, UNSW Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-3701-4997
Claudia BrunoCentre for Big Data Research in Health, UNSW Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-7789-3415
Nicholas A BuckleyBiomedical Informatics and Digital Health, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-6326-4711
Rose CairnsNSW Poisons Information Centre, The Children's Hospital at Westmead, Sydney, New South Wales, Australia.ORCID 0000-0002-8946-5079
Melisa LitchfieldCentre for Big Data Research in Health, UNSW Sydney, Sydney, New South Wales, Australia.ORCID 0000-0003-0002-7724
Simon PagetThe Children's Hospital at Westmead Clinical School, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-6605-3330
Helga ZoegaCentre for Big Data Research in Health, UNSW Sydney, Sydney, New South Wales, Australia.ORCID 0000-0003-0761-9028
Natasha NassarThe Children's Hospital at Westmead Clinical School, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-3720-9655
Sallie-Anne PearsonCentre for Big Data Research in Health, UNSW Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-7137-6855
The University of Sydney · AUUNSW Sydney · AUUniversity of Iceland · IS

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedicine prescribing for children is impacted by a lack of paediatric-specific dosing, efficacy and safety data for many medicines.

objectivesTo estimate the prevalence of medicine use among children and the rate of 'off-label' prescribing according to age at dispensing.

methodsWe used population-wide primarily outpatient dispensing claims data for 15% of Australian children (0-17 years), 2013-2017 (n = 840,190). We estimated prescribed medicine use and 'off-label' medicine use according to the child's age (<1 year, 1-5 years, 6-11 years, 12-17 years) defined as medicines without age-appropriate dose recommendations in regulator-approved product information. Within off-label medicines, we also identified medicines with and without age-specific dose recommendations in a national prescribing guide, the Australian Medicines Handbook Children's Dosing Companion (AMH CDC).

resultsThe overall dispensing rate was 2.0 dispensings per child per year. The medicines with the highest average yearly prevalence were systemic antibiotics (435.3 per 1000 children), greatest in children 1-5 years (546.9 per 1000). Other common medicine classes were systemic corticosteroids (92.7 per 1000), respiratory medicines (91.2 per 1000), acid-suppressing medicines in children <1 year (47.2 per 1000), antidepressants in children 12-17 years (40.3 per 1000) and psychostimulants in children 6-11 years (27.0 per 1000). We identified 12.2% of dispensings as off-label based on age, but 66.3% of these had age-specific dosing recommendations in the AMH CDC. Among children <1 year, off-label dispensings were commonly acid-suppressing medicines (35.5%) and topical hydrocortisone (33.1%); in children 6-11 years, off-label prescribing of clonidine (16.0%) and risperidone (13.1%) was common. Off-label dispensings were more likely to be prescribed by a specialist (21.7%) than on-label dispensings (7.5%).

conclusionsPrescribed medicine use is common in children, with off-label dispensings for medicines without paediatric-specific dosing guidelines concentrated in classes such as acid-suppressing medicines and psychotropics. Our findings highlight a need for better evidence to support best-practice prescribing.

Indexed as

Anti-Bacterial AgentsOff-Label UseAustraliaChildHumansInfantPractice Patterns, Physicians'PrevalenceAnti-Bacterial Agentsattention deficit disorder with hyperactivityAustraliagastroesophageal refluxpaediatricspharmacoepidemiology

Identifiers

PMID35172017
PMCPMC9540111
OpenAlexW4212859908

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.