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Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses
OBJECTIVES: Within cost-effectiveness models, prevalence figures can inform transition probabilities. The methodological quality of studies can inform the choice of prevalence figures but no single obvious candidate tool exists for assessing quality of the observational epidemiological studies for s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497530/ https://www.ncbi.nlm.nih.gov/pubmed/32938593 http://dx.doi.org/10.1136/bmjopen-2020-037324 |
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author | Glasgow, Matthew J Edlin, Richard Harding, Jane E |
author_facet | Glasgow, Matthew J Edlin, Richard Harding, Jane E |
author_sort | Glasgow, Matthew J |
collection | PubMed |
description | OBJECTIVES: Within cost-effectiveness models, prevalence figures can inform transition probabilities. The methodological quality of studies can inform the choice of prevalence figures but no single obvious candidate tool exists for assessing quality of the observational epidemiological studies for selecting prevalence estimates. We aimed to compare different tools to assess the risk of bias of studies reporting prevalence, and develop and compare possible numerical scoring systems using these tools to set a threshold for inclusion of reports of prevalence in an economic analysis of neonatal hypoglycaemia. DESIGN: Assessments of bias using two tools (Joanna Briggs Institute (JBI) Checklist for Prevalence Studies and a modified version of Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I)) were compared for 18 studies relevant to a single setting (neonatal hypoglycaemia). Inclusions of studies for use in a decision analysis model were considered based on summary scores derived from these tools. RESULTS: Both tools were considered easy to use and produced dispersed scores for each of the 40 study–outcome combinations. The modified ROBINS-I scores were more skewed than the JBI scores, particularly at higher thresholds. The studies selected for inclusion are generally the same using either tool; if 50% was used as the cut-off threshold using the Applicable Score both tools would yield the same results. However, the JBI tool is shorter and may be easier to interpret and apply to studies that do not involve a control group, while the modified ROBINS-I tool assesses more methodological detail in studies that include a control group. CONCLUSION: Both tools performed well for systematically assessing studies that report on outcome prevalence and provided similar discrimination between studies for risk of bias. This convergent validity supports use of both tools for the purpose of assessing risk of bias and selecting studies that report prevalence for inclusion in economic analyses. |
format | Online Article Text |
id | pubmed-7497530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-74975302020-09-28 Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses Glasgow, Matthew J Edlin, Richard Harding, Jane E BMJ Open Health Economics OBJECTIVES: Within cost-effectiveness models, prevalence figures can inform transition probabilities. The methodological quality of studies can inform the choice of prevalence figures but no single obvious candidate tool exists for assessing quality of the observational epidemiological studies for selecting prevalence estimates. We aimed to compare different tools to assess the risk of bias of studies reporting prevalence, and develop and compare possible numerical scoring systems using these tools to set a threshold for inclusion of reports of prevalence in an economic analysis of neonatal hypoglycaemia. DESIGN: Assessments of bias using two tools (Joanna Briggs Institute (JBI) Checklist for Prevalence Studies and a modified version of Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I)) were compared for 18 studies relevant to a single setting (neonatal hypoglycaemia). Inclusions of studies for use in a decision analysis model were considered based on summary scores derived from these tools. RESULTS: Both tools were considered easy to use and produced dispersed scores for each of the 40 study–outcome combinations. The modified ROBINS-I scores were more skewed than the JBI scores, particularly at higher thresholds. The studies selected for inclusion are generally the same using either tool; if 50% was used as the cut-off threshold using the Applicable Score both tools would yield the same results. However, the JBI tool is shorter and may be easier to interpret and apply to studies that do not involve a control group, while the modified ROBINS-I tool assesses more methodological detail in studies that include a control group. CONCLUSION: Both tools performed well for systematically assessing studies that report on outcome prevalence and provided similar discrimination between studies for risk of bias. This convergent validity supports use of both tools for the purpose of assessing risk of bias and selecting studies that report prevalence for inclusion in economic analyses. BMJ Publishing Group 2020-09-16 /pmc/articles/PMC7497530/ /pubmed/32938593 http://dx.doi.org/10.1136/bmjopen-2020-037324 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Health Economics Glasgow, Matthew J Edlin, Richard Harding, Jane E Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses |
title | Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses |
title_full | Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses |
title_fullStr | Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses |
title_full_unstemmed | Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses |
title_short | Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses |
title_sort | comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses |
topic | Health Economics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497530/ https://www.ncbi.nlm.nih.gov/pubmed/32938593 http://dx.doi.org/10.1136/bmjopen-2020-037324 |
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