Cargando…

Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods

BACKGROUND: Thresholds for statistical significance when assessing meta-analysis results are being insufficiently demonstrated by traditional 95% confidence intervals and P-values. Assessment of intervention effects in systematic reviews with meta-analysis deserves greater rigour. METHODS: Methodolo...

Descripción completa

Detalles Bibliográficos
Autores principales: Jakobsen, Janus Christian, Wetterslev, Jørn, Winkel, Per, Lange, Theis, Gluud, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4251848/
https://www.ncbi.nlm.nih.gov/pubmed/25416419
http://dx.doi.org/10.1186/1471-2288-14-120
_version_ 1782347102096982016
author Jakobsen, Janus Christian
Wetterslev, Jørn
Winkel, Per
Lange, Theis
Gluud, Christian
author_facet Jakobsen, Janus Christian
Wetterslev, Jørn
Winkel, Per
Lange, Theis
Gluud, Christian
author_sort Jakobsen, Janus Christian
collection PubMed
description BACKGROUND: Thresholds for statistical significance when assessing meta-analysis results are being insufficiently demonstrated by traditional 95% confidence intervals and P-values. Assessment of intervention effects in systematic reviews with meta-analysis deserves greater rigour. METHODS: Methodologies for assessing statistical and clinical significance of intervention effects in systematic reviews were considered. Balancing simplicity and comprehensiveness, an operational procedure was developed, based mainly on The Cochrane Collaboration methodology and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) guidelines. RESULTS: We propose an eight-step procedure for better validation of meta-analytic results in systematic reviews (1) Obtain the 95% confidence intervals and the P-values from both fixed-effect and random-effects meta-analyses and report the most conservative results as the main results. (2) Explore the reasons behind substantial statistical heterogeneity using subgroup and sensitivity analyses (see step 6). (3) To take account of problems with multiplicity adjust the thresholds for significance according to the number of primary outcomes. (4) Calculate required information sizes (≈ the a priori required number of participants for a meta-analysis to be conclusive) for all outcomes and analyse each outcome with trial sequential analysis. Report whether the trial sequential monitoring boundaries for benefit, harm, or futility are crossed. (5) Calculate Bayes factors for all primary outcomes. (6) Use subgroup analyses and sensitivity analyses to assess the potential impact of bias on the review results. (7) Assess the risk of publication bias. (8) Assess the clinical significance of the statistically significant review results. CONCLUSIONS: If followed, the proposed eight-step procedure will increase the validity of assessments of intervention effects in systematic reviews of randomised clinical trials. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2288-14-120) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4251848
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-42518482014-12-03 Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods Jakobsen, Janus Christian Wetterslev, Jørn Winkel, Per Lange, Theis Gluud, Christian BMC Med Res Methodol Correspondence BACKGROUND: Thresholds for statistical significance when assessing meta-analysis results are being insufficiently demonstrated by traditional 95% confidence intervals and P-values. Assessment of intervention effects in systematic reviews with meta-analysis deserves greater rigour. METHODS: Methodologies for assessing statistical and clinical significance of intervention effects in systematic reviews were considered. Balancing simplicity and comprehensiveness, an operational procedure was developed, based mainly on The Cochrane Collaboration methodology and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) guidelines. RESULTS: We propose an eight-step procedure for better validation of meta-analytic results in systematic reviews (1) Obtain the 95% confidence intervals and the P-values from both fixed-effect and random-effects meta-analyses and report the most conservative results as the main results. (2) Explore the reasons behind substantial statistical heterogeneity using subgroup and sensitivity analyses (see step 6). (3) To take account of problems with multiplicity adjust the thresholds for significance according to the number of primary outcomes. (4) Calculate required information sizes (≈ the a priori required number of participants for a meta-analysis to be conclusive) for all outcomes and analyse each outcome with trial sequential analysis. Report whether the trial sequential monitoring boundaries for benefit, harm, or futility are crossed. (5) Calculate Bayes factors for all primary outcomes. (6) Use subgroup analyses and sensitivity analyses to assess the potential impact of bias on the review results. (7) Assess the risk of publication bias. (8) Assess the clinical significance of the statistically significant review results. CONCLUSIONS: If followed, the proposed eight-step procedure will increase the validity of assessments of intervention effects in systematic reviews of randomised clinical trials. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2288-14-120) contains supplementary material, which is available to authorized users. BioMed Central 2014-11-21 /pmc/articles/PMC4251848/ /pubmed/25416419 http://dx.doi.org/10.1186/1471-2288-14-120 Text en © Jakobsen et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Correspondence
Jakobsen, Janus Christian
Wetterslev, Jørn
Winkel, Per
Lange, Theis
Gluud, Christian
Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods
title Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods
title_full Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods
title_fullStr Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods
title_full_unstemmed Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods
title_short Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods
title_sort thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods
topic Correspondence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4251848/
https://www.ncbi.nlm.nih.gov/pubmed/25416419
http://dx.doi.org/10.1186/1471-2288-14-120
work_keys_str_mv AT jakobsenjanuschristian thresholdsforstatisticalandclinicalsignificanceinsystematicreviewswithmetaanalyticmethods
AT wetterslevjørn thresholdsforstatisticalandclinicalsignificanceinsystematicreviewswithmetaanalyticmethods
AT winkelper thresholdsforstatisticalandclinicalsignificanceinsystematicreviewswithmetaanalyticmethods
AT langetheis thresholdsforstatisticalandclinicalsignificanceinsystematicreviewswithmetaanalyticmethods
AT gluudchristian thresholdsforstatisticalandclinicalsignificanceinsystematicreviewswithmetaanalyticmethods