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Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review
BACKGROUND: Systematic reviews should provide trustworthy guidance to decision-makers, but their credibility is challenged by the selective reporting of trial results and outcomes. Some trials are not published, and even among clinical trials that are published partially (e.g., as conference abstrac...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4630908/ https://www.ncbi.nlm.nih.gov/pubmed/26525044 http://dx.doi.org/10.1186/s13643-015-0134-z |
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author | Mayo-Wilson, Evan Hutfless, Susan Li, Tianjing Gresham, Gillian Fusco, Nicole Ehmsen, Jeffrey Heyward, James Vedula, Swaroop Lock, Diana Haythornthwaite, Jennifer Payne, Jennifer L. Cowley, Theresa Tolbert, Elizabeth Rosman, Lori Twose, Claire Stuart, Elizabeth A. Hong, Hwanhee Doshi, Peter Suarez-Cuervo, Catalina Singh, Sonal Dickersin, Kay |
author_facet | Mayo-Wilson, Evan Hutfless, Susan Li, Tianjing Gresham, Gillian Fusco, Nicole Ehmsen, Jeffrey Heyward, James Vedula, Swaroop Lock, Diana Haythornthwaite, Jennifer Payne, Jennifer L. Cowley, Theresa Tolbert, Elizabeth Rosman, Lori Twose, Claire Stuart, Elizabeth A. Hong, Hwanhee Doshi, Peter Suarez-Cuervo, Catalina Singh, Sonal Dickersin, Kay |
author_sort | Mayo-Wilson, Evan |
collection | PubMed |
description | BACKGROUND: Systematic reviews should provide trustworthy guidance to decision-makers, but their credibility is challenged by the selective reporting of trial results and outcomes. Some trials are not published, and even among clinical trials that are published partially (e.g., as conference abstracts), many are never published in full. Although there are many potential sources of published and unpublished data for systematic reviews, there are no established methods for choosing among multiple reports or data sources about the same trial. METHODS: We will conduct systematic reviews of the effectiveness and safety of two interventions following the Institute of Medicine (IOM) guidelines: (1) gabapentin for neuropathic pain and (2) quetiapine for bipolar depression. For the review of gabapentin, we will include adult participants with neuropathic pain who do not require ventilator support. For the review of quetiapine, we will include adult participants with acute bipolar depression (excluding mixed or rapid cycling episodes). We will compare these drugs (used alone or in combination with other interventions) with placebo or with the same intervention alone; direct comparisons with other medications will be excluded. For each review, we will conduct highly sensitive electronic searches, and the results of the searches will be assessed by two independent reviewers. Outcomes, study characteristics, and risk of bias ratings will be extracted from multiple reports by two individuals working independently, stored in a publicly available database (Systematic Review Data Repository) and analyzed using commonly available statistical software. In each review, we will conduct a series of meta-analyses using data from different sources to determine how the results are affected by the inclusion of data from multiple published sources (e.g., journal articles and conference abstracts) as well as unpublished aggregate data (e.g., “clinical study reports”) and individual participant data (IPD). We will identify patient-centered outcomes in each report and identify differences in the reporting of these outcomes across sources. SYSTEMATIC REVIEW REGISTRATION: CRD42015014037, CRD42015014038 |
format | Online Article Text |
id | pubmed-4630908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46309082015-11-04 Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review Mayo-Wilson, Evan Hutfless, Susan Li, Tianjing Gresham, Gillian Fusco, Nicole Ehmsen, Jeffrey Heyward, James Vedula, Swaroop Lock, Diana Haythornthwaite, Jennifer Payne, Jennifer L. Cowley, Theresa Tolbert, Elizabeth Rosman, Lori Twose, Claire Stuart, Elizabeth A. Hong, Hwanhee Doshi, Peter Suarez-Cuervo, Catalina Singh, Sonal Dickersin, Kay Syst Rev Protocol BACKGROUND: Systematic reviews should provide trustworthy guidance to decision-makers, but their credibility is challenged by the selective reporting of trial results and outcomes. Some trials are not published, and even among clinical trials that are published partially (e.g., as conference abstracts), many are never published in full. Although there are many potential sources of published and unpublished data for systematic reviews, there are no established methods for choosing among multiple reports or data sources about the same trial. METHODS: We will conduct systematic reviews of the effectiveness and safety of two interventions following the Institute of Medicine (IOM) guidelines: (1) gabapentin for neuropathic pain and (2) quetiapine for bipolar depression. For the review of gabapentin, we will include adult participants with neuropathic pain who do not require ventilator support. For the review of quetiapine, we will include adult participants with acute bipolar depression (excluding mixed or rapid cycling episodes). We will compare these drugs (used alone or in combination with other interventions) with placebo or with the same intervention alone; direct comparisons with other medications will be excluded. For each review, we will conduct highly sensitive electronic searches, and the results of the searches will be assessed by two independent reviewers. Outcomes, study characteristics, and risk of bias ratings will be extracted from multiple reports by two individuals working independently, stored in a publicly available database (Systematic Review Data Repository) and analyzed using commonly available statistical software. In each review, we will conduct a series of meta-analyses using data from different sources to determine how the results are affected by the inclusion of data from multiple published sources (e.g., journal articles and conference abstracts) as well as unpublished aggregate data (e.g., “clinical study reports”) and individual participant data (IPD). We will identify patient-centered outcomes in each report and identify differences in the reporting of these outcomes across sources. SYSTEMATIC REVIEW REGISTRATION: CRD42015014037, CRD42015014038 BioMed Central 2015-11-02 /pmc/articles/PMC4630908/ /pubmed/26525044 http://dx.doi.org/10.1186/s13643-015-0134-z Text en © Mayo-Wilson et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 | Protocol Mayo-Wilson, Evan Hutfless, Susan Li, Tianjing Gresham, Gillian Fusco, Nicole Ehmsen, Jeffrey Heyward, James Vedula, Swaroop Lock, Diana Haythornthwaite, Jennifer Payne, Jennifer L. Cowley, Theresa Tolbert, Elizabeth Rosman, Lori Twose, Claire Stuart, Elizabeth A. Hong, Hwanhee Doshi, Peter Suarez-Cuervo, Catalina Singh, Sonal Dickersin, Kay Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review |
title | Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review |
title_full | Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review |
title_fullStr | Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review |
title_full_unstemmed | Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review |
title_short | Integrating multiple data sources (MUDS) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review |
title_sort | integrating multiple data sources (muds) for meta-analysis to improve patient-centered outcomes research: a protocol for a systematic review |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4630908/ https://www.ncbi.nlm.nih.gov/pubmed/26525044 http://dx.doi.org/10.1186/s13643-015-0134-z |
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