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

BACKGROUND: A 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...

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Autores principales: Hoogland, Jeroen, Takada, Toshihiko, van Smeden, Maarten, Rovers, Maroeska M., de Sutter, An I., Merenstein, Daniel, Kaiser, Laurent, Liira, Helena, Little, Paul, Bucher, Heiner C., Moons, Karel G. M., Reitsma, Johannes B., Venekamp, Roderick P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478354/
https://www.ncbi.nlm.nih.gov/pubmed/37667327
http://dx.doi.org/10.1186/s41512-023-00154-0
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author Hoogland, Jeroen
Takada, Toshihiko
van Smeden, Maarten
Rovers, Maroeska M.
de Sutter, An I.
Merenstein, Daniel
Kaiser, Laurent
Liira, Helena
Little, Paul
Bucher, Heiner C.
Moons, Karel G. M.
Reitsma, Johannes B.
Venekamp, Roderick P.
author_facet Hoogland, Jeroen
Takada, Toshihiko
van Smeden, Maarten
Rovers, Maroeska M.
de Sutter, An I.
Merenstein, Daniel
Kaiser, Laurent
Liira, Helena
Little, Paul
Bucher, Heiner C.
Moons, Karel G. M.
Reitsma, Johannes B.
Venekamp, Roderick P.
author_sort Hoogland, Jeroen
collection PubMed
description BACKGROUND: A 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. METHODS: An 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. RESULTS: Results 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). CONCLUSIONS: In 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41512-023-00154-0.
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spelling pubmed-104783542023-09-06 Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis Hoogland, Jeroen Takada, Toshihiko van Smeden, Maarten Rovers, Maroeska M. de Sutter, An I. Merenstein, Daniel Kaiser, Laurent Liira, Helena Little, Paul Bucher, Heiner C. Moons, Karel G. M. Reitsma, Johannes B. Venekamp, Roderick P. Diagn Progn Res Research BACKGROUND: A 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. METHODS: An 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. RESULTS: Results 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). CONCLUSIONS: In 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41512-023-00154-0. BioMed Central 2023-09-05 /pmc/articles/PMC10478354/ /pubmed/37667327 http://dx.doi.org/10.1186/s41512-023-00154-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Hoogland, Jeroen
Takada, Toshihiko
van Smeden, Maarten
Rovers, Maroeska M.
de Sutter, An I.
Merenstein, Daniel
Kaiser, Laurent
Liira, Helena
Little, Paul
Bucher, Heiner C.
Moons, Karel G. M.
Reitsma, Johannes B.
Venekamp, Roderick P.
Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis
title Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis
title_full Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis
title_fullStr Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis
title_full_unstemmed Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis
title_short Prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis
title_sort prognosis and prediction of antibiotic benefit in adults with clinically diagnosed acute rhinosinusitis: an individual participant data meta-analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478354/
https://www.ncbi.nlm.nih.gov/pubmed/37667327
http://dx.doi.org/10.1186/s41512-023-00154-0
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