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...
Autores principales: | , , , , |
---|---|
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 |