Evidence map›Paper›PMID 37667327›Full record

ArticleDiagnostic and prognostic research2023

Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis.

Jeroen Hoogland, Toshihiko Takada, Maarten van Smeden, Maroeska M Rovers, An I de Sutter, Daniel Merenstein, Laurent Kaiser, Helena Liira, Paul Little, Heiner C Bucher and 3 more

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Article in Diagnostic and prognostic research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jeroen HooglandJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands. j.hoogland@amsterdamumc.nl.ORCID http://orcid.org/0000-0002-2397-6052
Toshihiko TakadaJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Maarten van SmedenJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Maroeska M RoversRadboud Institute for Health Sciences (RIHS), Radboud University Medical Center, Nijmegen, The Netherlands.
An I de SutterDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Daniel MerensteinDepartment of Family Medicine, Georgetown University Medical Center, Washington, DC, USA.
Laurent KaiserDepartment of Medicine, Division of Infectious Diseases, University Hospital Geneva, Geneva, Switzerland.
Helena LiiraDepartment of General Practice, School of Primary, Aboriginal and Rural Health Care, University of Western Australia, Perth, Australia.
Paul LittlePrimary Care & Population Sciences Unit, Aldermoor Health Centre, University of Southampton, Southampton, UK.
Heiner C BucherDivision of Clinical Epidemiology, Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland.
Karel G M MoonsJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Johannes B ReitsmaJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Roderick P VenekampJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

Funding

ZonMw 91618026
6 · The paper itself

Abstract

backgroundA previous individual participant data meta-analysis (IPD-MA) of antibiotics for adults with clinically diagnosed acute rhinosinusitis (ARS) showed a marginal overall effect of antibiotics, but was unable to identify patients that are most likely to benefit from antibiotics when applying conventional (i.e. univariable or one-variable-at-a-time) subgroup analysis. We updated the systematic review and investigated whether multivariable prediction of patient-level prognosis and antibiotic treatment effect may lead to more tailored treatment assignment in adults presenting to primary care with ARS.

methodsAn IPD-MA of nine double-blind placebo-controlled trials of antibiotic treatment (n=2539) was conducted, with the probability of being cured at 8-15 days as the primary outcome. A logistic mixed effects model was developed to predict the probability of being cured based on demographic characteristics, signs and symptoms, and antibiotic treatment assignment. Predictive performance was quantified based on internal-external cross-validation in terms of calibration and discrimination performance, overall model fit, and the accuracy of individual predictions.

resultsResults indicate that the prognosis with respect to risk of cure could not be reliably predicted (c-statistic 0.58 and Brier score 0.24). Similarly, patient-level treatment effect predictions did not reliably distinguish between those that did and did not benefit from antibiotics (c-for-benefit 0.50).

conclusionsIn conclusion, multivariable prediction based on patient demographics and common signs and symptoms did not reliably predict the patient-level probability of cure and antibiotic effect in this IPD-MA. Therefore, these characteristics cannot be expected to reliably distinguish those that do and do not benefit from antibiotics in adults presenting to primary care with ARS.

Indexed as

Acute rhinosinusitisAntibiotic treatmentIndividualized treatment effectIndividual participant data meta-analysisPredictionRandomized controlled trial

Identifiers

PMID37667327
PMCPMC10478354

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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.