Accuracy of signs, symptoms and blood tests for diagnosing acute bacterial rhinosinusitis and CT-confirmed acute rhinosinusitis in adults: protocol of an individual patient data meta-analysis

Roderick Venekamp; Jens Georg Hansen; Johannes B Reitsma; Mark H Ebell; Morten Lindbaek

doi:10.1136/bmjopen-2020-040988

Accuracy of signs, symptoms and blood tests for diagnosing acute bacterial rhinosinusitis and CT-confirmed acute rhinosinusitis in adults: protocol of an individual patient data meta-analysis

Roderick Venekamp, Jens Georg Hansen, Johannes B Reitsma, Mark H Ebell, Morten Lindbaek

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Abstract

INTRODUCTION: This protocol outlines a diagnostic individual patient data (IPD) meta-analysis aimed at developing simple prediction models based on readily available signs, symptoms and blood tests to accurately predict acute bacterial rhinosinusitis and CT-confirmed (fluid level or total opacification in any sinus) acute rhinosinusitis (ARS) in adults presenting to primary care with clinically diagnosed ARS, target conditions associated with antibiotic benefit.

METHODS AND ANALYSIS: The systematic searches of PubMed and Embase of a review on the accuracy of signs and symptoms for diagnosing ARS in ambulatory care will be updated to April 2020 to identify relevant studies. Authors of eligible studies will be contacted and invited to provide IPD. Methodological quality of the studies will be assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Candidate predictor selection will be based on knowledge from existing literature, clinical reasoning and availability. Multivariable logistic regression analyses will be used to develop prediction models aimed at calculating absolute risk estimates. Large unexplained between-study heterogeneity in predictive accuracy of the models will be explored and may lead to either model adjustment or derivation of separate context-specific models. Calibration and discrimination will be evaluated to assess the models' performance. Bootstrap resampling techniques will be used to assess internal validation and to inform on possible adjustment for overfitting. In addition, we aim to perform internal-external cross-validation procedures.

ETHICS AND DISSEMINATION: In this IPD meta-analysis, no identifiable patient data will be used. As such, the Medical Research Involving Humans Subject Act does not apply, and official ethical approval is not required. Findings will be published in international peer-reviewed journals and presented at scientific conferences.

PROSPERO REGISTRATION NUMBER: PROSPERO CRD42020175659.

Original language	English
Article number	e040988
Pages (from-to)	1-7
Journal	BMJ Open
Volume	10
Issue number	11
DOIs	https://doi.org/10.1136/bmjopen-2020-040988
Publication status	Published - 3 Nov 2020

Keywords

epidemiology
otolaryngology
primary care

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10.1136/bmjopen-2020-040988

e040988.fullFinal published version, 344 KB

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title = "Accuracy of signs, symptoms and blood tests for diagnosing acute bacterial rhinosinusitis and CT-confirmed acute rhinosinusitis in adults: protocol of an individual patient data meta-analysis",

abstract = "INTRODUCTION: This protocol outlines a diagnostic individual patient data (IPD) meta-analysis aimed at developing simple prediction models based on readily available signs, symptoms and blood tests to accurately predict acute bacterial rhinosinusitis and CT-confirmed (fluid level or total opacification in any sinus) acute rhinosinusitis (ARS) in adults presenting to primary care with clinically diagnosed ARS, target conditions associated with antibiotic benefit.METHODS AND ANALYSIS: The systematic searches of PubMed and Embase of a review on the accuracy of signs and symptoms for diagnosing ARS in ambulatory care will be updated to April 2020 to identify relevant studies. Authors of eligible studies will be contacted and invited to provide IPD. Methodological quality of the studies will be assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Candidate predictor selection will be based on knowledge from existing literature, clinical reasoning and availability. Multivariable logistic regression analyses will be used to develop prediction models aimed at calculating absolute risk estimates. Large unexplained between-study heterogeneity in predictive accuracy of the models will be explored and may lead to either model adjustment or derivation of separate context-specific models. Calibration and discrimination will be evaluated to assess the models' performance. Bootstrap resampling techniques will be used to assess internal validation and to inform on possible adjustment for overfitting. In addition, we aim to perform internal-external cross-validation procedures.ETHICS AND DISSEMINATION: In this IPD meta-analysis, no identifiable patient data will be used. As such, the Medical Research Involving Humans Subject Act does not apply, and official ethical approval is not required. Findings will be published in international peer-reviewed journals and presented at scientific conferences.PROSPERO REGISTRATION NUMBER: PROSPERO CRD42020175659.",

keywords = "epidemiology, otolaryngology, primary care",

author = "Roderick Venekamp and Hansen, {Jens Georg} and Reitsma, {Johannes B} and Ebell, {Mark H} and Morten Lindbaek",

note = "Funding Information: Funding This study was supported by The Netherlands Organisation for Health Research and Development (grant 91618026). The funder did not participate in the design of the study and will have no role in the study conduct, data analysis, interpretation and publication of the data. Publisher Copyright: {\textcopyright} 2020 American Institute of Physics Inc.. All rights reserved.",

year = "2020",

month = nov,

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doi = "10.1136/bmjopen-2020-040988",

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volume = "10",

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Accuracy of signs, symptoms and blood tests for diagnosing acute bacterial rhinosinusitis and CT-confirmed acute rhinosinusitis in adults: protocol of an individual patient data meta-analysis. / Venekamp, Roderick; Hansen, Jens Georg; Reitsma, Johannes B et al.
In: BMJ Open, Vol. 10, No. 11, e040988, 03.11.2020, p. 1-7.

Research output: Contribution to journal › Article › Academic › peer-review

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AU - Hansen, Jens Georg

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AU - Ebell, Mark H

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N1 - Funding Information: Funding This study was supported by The Netherlands Organisation for Health Research and Development (grant 91618026). The funder did not participate in the design of the study and will have no role in the study conduct, data analysis, interpretation and publication of the data. Publisher Copyright: © 2020 American Institute of Physics Inc.. All rights reserved.

PY - 2020/11/3

Y1 - 2020/11/3

N2 - INTRODUCTION: This protocol outlines a diagnostic individual patient data (IPD) meta-analysis aimed at developing simple prediction models based on readily available signs, symptoms and blood tests to accurately predict acute bacterial rhinosinusitis and CT-confirmed (fluid level or total opacification in any sinus) acute rhinosinusitis (ARS) in adults presenting to primary care with clinically diagnosed ARS, target conditions associated with antibiotic benefit.METHODS AND ANALYSIS: The systematic searches of PubMed and Embase of a review on the accuracy of signs and symptoms for diagnosing ARS in ambulatory care will be updated to April 2020 to identify relevant studies. Authors of eligible studies will be contacted and invited to provide IPD. Methodological quality of the studies will be assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Candidate predictor selection will be based on knowledge from existing literature, clinical reasoning and availability. Multivariable logistic regression analyses will be used to develop prediction models aimed at calculating absolute risk estimates. Large unexplained between-study heterogeneity in predictive accuracy of the models will be explored and may lead to either model adjustment or derivation of separate context-specific models. Calibration and discrimination will be evaluated to assess the models' performance. Bootstrap resampling techniques will be used to assess internal validation and to inform on possible adjustment for overfitting. In addition, we aim to perform internal-external cross-validation procedures.ETHICS AND DISSEMINATION: In this IPD meta-analysis, no identifiable patient data will be used. As such, the Medical Research Involving Humans Subject Act does not apply, and official ethical approval is not required. Findings will be published in international peer-reviewed journals and presented at scientific conferences.PROSPERO REGISTRATION NUMBER: PROSPERO CRD42020175659.

AB - INTRODUCTION: This protocol outlines a diagnostic individual patient data (IPD) meta-analysis aimed at developing simple prediction models based on readily available signs, symptoms and blood tests to accurately predict acute bacterial rhinosinusitis and CT-confirmed (fluid level or total opacification in any sinus) acute rhinosinusitis (ARS) in adults presenting to primary care with clinically diagnosed ARS, target conditions associated with antibiotic benefit.METHODS AND ANALYSIS: The systematic searches of PubMed and Embase of a review on the accuracy of signs and symptoms for diagnosing ARS in ambulatory care will be updated to April 2020 to identify relevant studies. Authors of eligible studies will be contacted and invited to provide IPD. Methodological quality of the studies will be assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Candidate predictor selection will be based on knowledge from existing literature, clinical reasoning and availability. Multivariable logistic regression analyses will be used to develop prediction models aimed at calculating absolute risk estimates. Large unexplained between-study heterogeneity in predictive accuracy of the models will be explored and may lead to either model adjustment or derivation of separate context-specific models. Calibration and discrimination will be evaluated to assess the models' performance. Bootstrap resampling techniques will be used to assess internal validation and to inform on possible adjustment for overfitting. In addition, we aim to perform internal-external cross-validation procedures.ETHICS AND DISSEMINATION: In this IPD meta-analysis, no identifiable patient data will be used. As such, the Medical Research Involving Humans Subject Act does not apply, and official ethical approval is not required. Findings will be published in international peer-reviewed journals and presented at scientific conferences.PROSPERO REGISTRATION NUMBER: PROSPERO CRD42020175659.

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Accuracy of signs, symptoms and blood tests for diagnosing acute bacterial rhinosinusitis and CT-confirmed acute rhinosinusitis in adults: protocol of an individual patient data meta-analysis

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