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Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection
BACKGROUND: Public health and clinical recommendations are established from systematic reviews and retrospective meta-analyses combining effect sizes, traditionally, from aggregate data and more recently, using individual participant data (IPD) of published studies. However, trials often have outcom...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919738/ https://www.ncbi.nlm.nih.gov/pubmed/36774497 http://dx.doi.org/10.1186/s12884-023-05366-2 |
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author | Gernand, Alison D. Gallagher, Kelly Bhandari, Nita Kolsteren, Patrick Lee, Anne CC Shafiq, Yasir Taneja, Sunita Tielsch, James M. Abate, Firehiwot Workneh Baye, Estifanos Berhane, Yemane Chowdhury, Ranadip Dailey-Chwalibóg, Trenton de Kok, Brenda Dhabhai, Neeta Jehan, Fyezah Kang, Yunhee Katz, Joanne Khatry, Subarna Lachat, Carl Mazumder, Sarmila Muhammad, Ameer Nisar, Muhammad Imran Sharma, Sitanshi Martin, Leigh A. Upadhyay, Ravi Prakash Christian, Parul |
author_facet | Gernand, Alison D. Gallagher, Kelly Bhandari, Nita Kolsteren, Patrick Lee, Anne CC Shafiq, Yasir Taneja, Sunita Tielsch, James M. Abate, Firehiwot Workneh Baye, Estifanos Berhane, Yemane Chowdhury, Ranadip Dailey-Chwalibóg, Trenton de Kok, Brenda Dhabhai, Neeta Jehan, Fyezah Kang, Yunhee Katz, Joanne Khatry, Subarna Lachat, Carl Mazumder, Sarmila Muhammad, Ameer Nisar, Muhammad Imran Sharma, Sitanshi Martin, Leigh A. Upadhyay, Ravi Prakash Christian, Parul |
author_sort | Gernand, Alison D. |
collection | PubMed |
description | BACKGROUND: Public health and clinical recommendations are established from systematic reviews and retrospective meta-analyses combining effect sizes, traditionally, from aggregate data and more recently, using individual participant data (IPD) of published studies. However, trials often have outcomes and other meta-data that are not defined and collected in a standardized way, making meta-analysis problematic. IPD meta-analysis can only partially fix the limitations of traditional, retrospective, aggregate meta-analysis; prospective meta-analysis further reduces the problems. METHODS: We developed an initiative including seven clinical intervention studies of balanced energy-protein (BEP) supplementation during pregnancy and/or lactation that are being conducted (or recently concluded) in Burkina Faso, Ethiopia, India, Nepal, and Pakistan to test the effect of BEP on infant and maternal outcomes. These studies were commissioned after an expert consultation that designed recommendations for a BEP product for use among pregnant and lactating women in low- and middle-income countries. The initiative goal is to harmonize variables across studies to facilitate IPD meta-analyses on closely aligned data, commonly called prospective meta-analysis. Our objective here is to describe the process of harmonizing variable definitions and prioritizing research questions. A two-day workshop of investigators, content experts, and advisors was held in February 2020 and harmonization activities continued thereafter. Efforts included a range of activities from examining protocols and data collection plans to discussing best practices within field constraints. Prior to harmonization, there were many similar outcomes and variables across studies, such as newborn anthropometry, gestational age, and stillbirth, however, definitions and protocols differed. As well, some measurements were being conducted in several but not all studies, such as food insecurity. Through the harmonization process, we came to consensus on important shared variables, particularly outcomes, added new measurements, and improved protocols across studies. DISCUSSION: We have fostered extensive communication between investigators from different studies, and importantly, created a large set of harmonized variable definitions within a prospective meta-analysis framework. We expect this initiative will improve reporting within each study in addition to providing opportunities for a series of IPD meta-analyses. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-05366-2. |
format | Online Article Text |
id | pubmed-9919738 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99197382023-02-12 Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection Gernand, Alison D. Gallagher, Kelly Bhandari, Nita Kolsteren, Patrick Lee, Anne CC Shafiq, Yasir Taneja, Sunita Tielsch, James M. Abate, Firehiwot Workneh Baye, Estifanos Berhane, Yemane Chowdhury, Ranadip Dailey-Chwalibóg, Trenton de Kok, Brenda Dhabhai, Neeta Jehan, Fyezah Kang, Yunhee Katz, Joanne Khatry, Subarna Lachat, Carl Mazumder, Sarmila Muhammad, Ameer Nisar, Muhammad Imran Sharma, Sitanshi Martin, Leigh A. Upadhyay, Ravi Prakash Christian, Parul BMC Pregnancy Childbirth Research BACKGROUND: Public health and clinical recommendations are established from systematic reviews and retrospective meta-analyses combining effect sizes, traditionally, from aggregate data and more recently, using individual participant data (IPD) of published studies. However, trials often have outcomes and other meta-data that are not defined and collected in a standardized way, making meta-analysis problematic. IPD meta-analysis can only partially fix the limitations of traditional, retrospective, aggregate meta-analysis; prospective meta-analysis further reduces the problems. METHODS: We developed an initiative including seven clinical intervention studies of balanced energy-protein (BEP) supplementation during pregnancy and/or lactation that are being conducted (or recently concluded) in Burkina Faso, Ethiopia, India, Nepal, and Pakistan to test the effect of BEP on infant and maternal outcomes. These studies were commissioned after an expert consultation that designed recommendations for a BEP product for use among pregnant and lactating women in low- and middle-income countries. The initiative goal is to harmonize variables across studies to facilitate IPD meta-analyses on closely aligned data, commonly called prospective meta-analysis. Our objective here is to describe the process of harmonizing variable definitions and prioritizing research questions. A two-day workshop of investigators, content experts, and advisors was held in February 2020 and harmonization activities continued thereafter. Efforts included a range of activities from examining protocols and data collection plans to discussing best practices within field constraints. Prior to harmonization, there were many similar outcomes and variables across studies, such as newborn anthropometry, gestational age, and stillbirth, however, definitions and protocols differed. As well, some measurements were being conducted in several but not all studies, such as food insecurity. Through the harmonization process, we came to consensus on important shared variables, particularly outcomes, added new measurements, and improved protocols across studies. DISCUSSION: We have fostered extensive communication between investigators from different studies, and importantly, created a large set of harmonized variable definitions within a prospective meta-analysis framework. We expect this initiative will improve reporting within each study in addition to providing opportunities for a series of IPD meta-analyses. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-05366-2. BioMed Central 2023-02-11 /pmc/articles/PMC9919738/ /pubmed/36774497 http://dx.doi.org/10.1186/s12884-023-05366-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Gernand, Alison D. Gallagher, Kelly Bhandari, Nita Kolsteren, Patrick Lee, Anne CC Shafiq, Yasir Taneja, Sunita Tielsch, James M. Abate, Firehiwot Workneh Baye, Estifanos Berhane, Yemane Chowdhury, Ranadip Dailey-Chwalibóg, Trenton de Kok, Brenda Dhabhai, Neeta Jehan, Fyezah Kang, Yunhee Katz, Joanne Khatry, Subarna Lachat, Carl Mazumder, Sarmila Muhammad, Ameer Nisar, Muhammad Imran Sharma, Sitanshi Martin, Leigh A. Upadhyay, Ravi Prakash Christian, Parul Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection |
title | Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection |
title_full | Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection |
title_fullStr | Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection |
title_full_unstemmed | Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection |
title_short | Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses – finding and creating similarities in variables and data collection |
title_sort | harmonization of maternal balanced energy-protein supplementation studies for individual participant data (ipd) meta-analyses – finding and creating similarities in variables and data collection |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919738/ https://www.ncbi.nlm.nih.gov/pubmed/36774497 http://dx.doi.org/10.1186/s12884-023-05366-2 |
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