Año 2024 / Volumen 116 / Número 3
Editorial
Biostatistics for gastroenterologists. Part III - Mastering meta-analysis for beginners

121-123

DOI: 10.17235/reed.2023.10123/2023

Elena Stallings,

Resumen
Meta-analysis combines data from multiple independent studies to derive robust conclusions. This article provides an insightful guide to conducting meta-analyses with a particular focus on gastroenterology studies. The process of conducting a meta-analysis involves several systematic steps. Firstly, formulating a clear research question using the PICO format. Subsequently, a comprehensive literature search is conducted using databases like PubMed and Embase, followed by the establishment of inclusion and exclusion criteria to select eligible studies. Data extraction, quality assessment, and statistical analysis using suitable software are then undertaken. Key aspects of performing the meta-analysis include choosing between fixed-effects and random-effects models based on heterogeneity levels among studies. Calculating summary effect sizes and visualizing results through forest plots aid in interpreting outcomes effectively. This article emphasizes the significance of meta-analysis in evidence synthesis, illustrating its role in enhancing decision-making processes by providing more comprehensive and reliable conclusions. It quantifies relationships between variables, resolves conflicting findings, and increases statistical power by aggregating data. Meta-analysis stands as an indispensable tool in research and decision-making, requiring collaboration with statisticians for methodological rigor and accuracy.
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Bibliografía
1. Elmunzer BJ, Singal AG, Sussman JB, Deshpande AR, Sussman DA, Conte ML, Dwamena BA, Rogers MA, Schoenfeld PS, Inadomi JM, Saini SD, Waljee AK. Comparing the effectiveness of competing tests for reducing colorectal cancer mortality: a network meta-analysis. Gastrointest Endosc. 2015 Mar;81(3):700-709.e3.
2. Sterne J A C, Savović J, Page M J, Elbers R G, Blencowe N S, Boutron I et al. RoB 2: a revised tool for assessing risk of bias in randomised trials BMJ 2019; 366 :l4898
3. Sterne J A, Hernán M A, Reeves B C, Savović J, Berkman N D, Viswanathan M et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions BMJ 2016; 355 :i4919
4. Stallings E. Biostatistics for gastroenterologists. Part I. Rev Esp Enferm Dig. 2023 Apr;115(4):157-159.
5. Dettori JR, Norvell DC, Chapman JR. Seeing the Forest by Looking at the Trees: How to Interpret a Meta-Analysis Forest Plot. Global Spine J. 2021 May;11(4):614-616.
6. Dettori JR, Norvell DC, Chapman JR. Fixed-Effect vs Random-Effects Models for Meta-Analysis: 3 Points to Consider. Global Spine J. 2022 Sep;12(7):1624-1626. doi: 10.1177/21925682221110527. Epub 2022 Jun 20.
7. Review Manager Web (RevMan Web). The Cochrane Collaboration, (2023). Available at revman.cochrane.org
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Biostatistics for gastroenterologists. Part I

DOI: 10.17235/reed.2023.9494/2023

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Stallings E. Biostatistics for gastroenterologists. Part III - Mastering meta-analysis for beginners . 10123/2023


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Ficha Técnica

Recibido: 27/11/2023

Aceptado: 28/11/2023

Prepublicado: 14/12/2023

Publicado: 04/03/2024

Tiempo de prepublicación: 17 días

Tiempo de edición del artículo: 98 días


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