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 se...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2020-09-01
|
| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/10/9/e037324.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841554095556526080 |
|---|---|
| author | Jane E Harding Richard Edlin Matthew J Glasgow |
| author_facet | Jane E Harding Richard Edlin Matthew J Glasgow |
| author_sort | Jane E Harding |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-45f14056c6914c7789f42ae16cf43f52 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2020-09-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-45f14056c6914c7789f42ae16cf43f522025-01-08T20:10:09ZengBMJ Publishing GroupBMJ Open2044-60552020-09-0110910.1136/bmjopen-2020-037324Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analysesJane E Harding0Richard Edlin1Matthew J Glasgow21 Liggins Institute, University of Auckland, Auckland, New ZealandHealth Systems, School of Population Health, University of Auckland, Auckland, New ZealandLiggins Institute, The University of Auckland, Auckland, New ZealandObjectives 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.https://bmjopen.bmj.com/content/10/9/e037324.full |
| spellingShingle | Jane E Harding Richard Edlin Matthew J Glasgow Comparison of risk-of-bias assessment approaches for selection of studies reporting prevalence for economic analyses BMJ Open |
| 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 |
| url | https://bmjopen.bmj.com/content/10/9/e037324.full |
| work_keys_str_mv | AT janeeharding comparisonofriskofbiasassessmentapproachesforselectionofstudiesreportingprevalenceforeconomicanalyses AT richardedlin comparisonofriskofbiasassessmentapproachesforselectionofstudiesreportingprevalenceforeconomicanalyses AT matthewjglasgow comparisonofriskofbiasassessmentapproachesforselectionofstudiesreportingprevalenceforeconomicanalyses |