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Research article
Which interactions matter in economic evaluations? A systematic review and simulation study
Helen A Dakin
University of Oxford
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3255-748X
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: We aimed to assess the magnitude of interactions in costs, quality-adjusted life-years (QALYs) and net benefits within a sample of published economic evaluations of factorial randomised controlled trials (RCTs), evaluate the impact that different analytical methods would have had on the results and compare the performance of different criteria for identifying which interactions should be taken into account.
Methods: We conducted a systematic review of full economic evaluations conducted alongside factorial RCTs and reviewed the methods used in different studies, as well as the incidence, magnitude, statistical significance, and type of interactions observed within the trials. We developed the interaction-effect ratio as a measure of the magnitude of interactions relative to main effects. For those studies reporting sufficient data, we assessed whether changing the form of analysis to ignore or include interactions would have changed the conclusions. We evaluated how well different criteria for identifying which interactions should be taken into account in the analysis would perform in practice, using simulated data generated to match the summary statistics of the studies identified in the review.
Results: Large interactions for economic endpoints occurred frequently within the 40 studies identified in the review, although interactions rarely changed the conclusions.
Conclusions: Simulation work demonstrated that in analyses of factorial RCTs, taking account of all interactions or including interactions above a certain size (regardless of statistical significance) minimised the opportunity cost from adopting treatments that do not in fact have the highest true net benefit.
Keywords
Factorial randomised controlled trial; economic evaluation; cost-effectiveness analysis; systematic review; interactions; simulation.
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CURRENT STATUS: Under Review
Version 3
Posted 15 Apr, 2020
No community comments so far
Editor assigned
On 12 Apr, 2020
Submission checks complete
On 11 Apr, 2020
Editor invited
On 11 Apr, 2020
No comments provided
Reviewer #1 agreed
On 01 Apr, 2020
Review #1 received
Received 01 Apr, 2020
Editorial decision: Minor revision
On 01 Apr, 2020
Reviewers invited
Invitations sent on 12 Mar, 2020
Editor assigned
On 11 Mar, 2020
Submission checks complete
On 10 Mar, 2020
Editor invited
On 10 Mar, 2020
No comments provided
Editorial decision: Major revision
On 14 Feb, 2020
Review #2 received
Received 29 Jan, 2020
Reviewer #2 agreed
On 12 Dec, 2019
Review #1 received
Received 26 Oct, 2019
Reviewer #1 agreed
On 09 Oct, 2019
Reviewers invited
Invitations sent on 25 Sep, 2019
Submission checks complete
On 28 Aug, 2019
Editor invited
On 28 Aug, 2019
Editor assigned
On 26 Aug, 2019
First submitted
On 21 Aug, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Economics & Outcomes Research
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This preprint is under consideration at BMC Medical Research Methodology. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Which interactions matter in economic evaluations? A systematic review and simulation study
Helen A Dakin
University of Oxford
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3255-748X
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 3
Posted 15 Apr, 2020
No community comments so far
Editor assigned
On 12 Apr, 2020
Submission checks complete
On 11 Apr, 2020
Editor invited
On 11 Apr, 2020
No comments provided
Reviewer #1 agreed
On 01 Apr, 2020
Review #1 received
Received 01 Apr, 2020
Editorial decision: Minor revision
On 01 Apr, 2020
Reviewers invited
Invitations sent on 12 Mar, 2020
Editor assigned
On 11 Mar, 2020
Submission checks complete
On 10 Mar, 2020
Editor invited
On 10 Mar, 2020
No comments provided
Editorial decision: Major revision
On 14 Feb, 2020
Review #2 received
Received 29 Jan, 2020
Reviewer #2 agreed
On 12 Dec, 2019
Review #1 received
Received 26 Oct, 2019
Reviewer #1 agreed
On 09 Oct, 2019
Reviewers invited
Invitations sent on 25 Sep, 2019
Submission checks complete
On 28 Aug, 2019
Editor invited
On 28 Aug, 2019
Editor assigned
On 26 Aug, 2019
First submitted
On 21 Aug, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Health Economics & Outcomes Research
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: We aimed to assess the magnitude of interactions in costs, quality-adjusted life-years (QALYs) and net benefits within a sample of published economic evaluations of factorial randomised controlled trials (RCTs), evaluate the impact that different analytical methods would have had on the results and compare the performance of different criteria for identifying which interactions should be taken into account.
Methods: We conducted a systematic review of full economic evaluations conducted alongside factorial RCTs and reviewed the methods used in different studies, as well as the incidence, magnitude, statistical significance, and type of interactions observed within the trials. We developed the interaction-effect ratio as a measure of the magnitude of interactions relative to main effects. For those studies reporting sufficient data, we assessed whether changing the form of analysis to ignore or include interactions would have changed the conclusions. We evaluated how well different criteria for identifying which interactions should be taken into account in the analysis would perform in practice, using simulated data generated to match the summary statistics of the studies identified in the review.
Results: Large interactions for economic endpoints occurred frequently within the 40 studies identified in the review, although interactions rarely changed the conclusions.
Conclusions: Simulation work demonstrated that in analyses of factorial RCTs, taking account of all interactions or including interactions above a certain size (regardless of statistical significance) minimised the opportunity cost from adopting treatments that do not in fact have the highest true net benefit.
Figure 1