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Study design flaws and statistical challenges in evaluating fertility treatments
Health interventions should be tested before being introduced into clinical practice, to find out whether they work and whether they are harmful. However, research studies will only provide reliable answers to these questions if they are appropriately designed and analysed. But these are not trivial...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bioscientifica Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812412/ https://www.ncbi.nlm.nih.gov/pubmed/35128452 http://dx.doi.org/10.1530/RAF-21-0015 |
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author | Wilkinson, Jack Stocking, Katie |
author_facet | Wilkinson, Jack Stocking, Katie |
author_sort | Wilkinson, Jack |
collection | PubMed |
description | Health interventions should be tested before being introduced into clinical practice, to find out whether they work and whether they are harmful. However, research studies will only provide reliable answers to these questions if they are appropriately designed and analysed. But these are not trivial tasks. We review some methodological challenges that arise when evaluating fertility interventions and explain the implications for a non-statistical audience. These include flexibility in outcomes and analyses; use of surrogate outcomes instead of live birth; use of inappropriate denominators; evaluating cumulative outcomes and time to live birth; allowing each patient or couple to contribute to a research study more than once. We highlight recurring errors and present solutions. We conclude by highlighting the importance of collaboration between clinical and methodological experts, as well as people with experience of subfertility, for realising high-quality research. LAY SUMMARY: We do research to find out whether fertility treatments are beneficial and to make sure they don’t cause harm. However, research will only provide reliable answers if it is done properly. It is not unusual for researchers to make mistakes when they are designing research studies and analysing the data that we get from them. In this review, we describe some of the mistakes people make when they do research about fertility treatments and explain how to avoid them. These include challenges which arise due to the large number of things that can be measured and reported when looking to see if fertility treatments work; failure to check whether the treatment increases the number of live births; failing to include all study participants in calculations;challenges in studies where participants may have more than one treatment attempt. We conclude by highlighting the importance of collaboration between clinical and methodological experts, as well as people with experience of fertility problems. |
format | Online Article Text |
id | pubmed-8812412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Bioscientifica Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-88124122022-02-04 Study design flaws and statistical challenges in evaluating fertility treatments Wilkinson, Jack Stocking, Katie Reprod Fertil Commentary Health interventions should be tested before being introduced into clinical practice, to find out whether they work and whether they are harmful. However, research studies will only provide reliable answers to these questions if they are appropriately designed and analysed. But these are not trivial tasks. We review some methodological challenges that arise when evaluating fertility interventions and explain the implications for a non-statistical audience. These include flexibility in outcomes and analyses; use of surrogate outcomes instead of live birth; use of inappropriate denominators; evaluating cumulative outcomes and time to live birth; allowing each patient or couple to contribute to a research study more than once. We highlight recurring errors and present solutions. We conclude by highlighting the importance of collaboration between clinical and methodological experts, as well as people with experience of subfertility, for realising high-quality research. LAY SUMMARY: We do research to find out whether fertility treatments are beneficial and to make sure they don’t cause harm. However, research will only provide reliable answers if it is done properly. It is not unusual for researchers to make mistakes when they are designing research studies and analysing the data that we get from them. In this review, we describe some of the mistakes people make when they do research about fertility treatments and explain how to avoid them. These include challenges which arise due to the large number of things that can be measured and reported when looking to see if fertility treatments work; failure to check whether the treatment increases the number of live births; failing to include all study participants in calculations;challenges in studies where participants may have more than one treatment attempt. We conclude by highlighting the importance of collaboration between clinical and methodological experts, as well as people with experience of fertility problems. Bioscientifica Ltd 2021-06-17 /pmc/articles/PMC8812412/ /pubmed/35128452 http://dx.doi.org/10.1530/RAF-21-0015 Text en © The authors https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Commentary Wilkinson, Jack Stocking, Katie Study design flaws and statistical challenges in evaluating fertility treatments |
title | Study design flaws and statistical challenges in evaluating fertility treatments |
title_full | Study design flaws and statistical challenges in evaluating fertility treatments |
title_fullStr | Study design flaws and statistical challenges in evaluating fertility treatments |
title_full_unstemmed | Study design flaws and statistical challenges in evaluating fertility treatments |
title_short | Study design flaws and statistical challenges in evaluating fertility treatments |
title_sort | study design flaws and statistical challenges in evaluating fertility treatments |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812412/ https://www.ncbi.nlm.nih.gov/pubmed/35128452 http://dx.doi.org/10.1530/RAF-21-0015 |
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