See the published version of this preprint at BMC Medical Research Methodology.
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Research article
Jean Raymond
Centre Hospitalier de L'Universite de Montreal
Corresponding Author
ORCiD: https://orcid.org/0000-0003-1978-4274
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Clinical uncertainty and equipoise are vague notions that play important roles in contemporary problems of medical care and research, including the design and conduct of pragmatic clinical trials. Our goal was to show how the reliability study methods normally used to assess diagnostic tests can be applied to particular management decisions to measure the degree of clinical uncertainty and equipoise regarding the use of rival management options prior to the conduct of randomized trials.
Methods: We first illustrate how we have used the reliability study methodology to measure uncertainty in clinical decision-making regarding mechanical thrombectomy in acute stroke. We then follow the layout provided by standard guidelines to review how the various design elements of diagnostic reliability studies can be adapted to assess the repeatability of management decisions and measure clinical uncertainty.
Results: The example shows how this methodology can be used to show disagreement in decisions for thrombectomy, and justify that sufficient clinical uncertainty exists to warrant the conduct of additional randomized trials. The general method we propose is that a sufficient number of diverse individual cases sharing a similar clinical problem and covering a wide spectrum of clinical presentations be assembled into a portfolio that is submitted to a variety of clinicians who routinely manage patients with the clinical problem. Clinicians are asked to independently choose one of the predefined management options, which are selected from those that would be compared within a randomized trial that would address the clinical dilemma. Intra-rater agreement can be assessed at a later time with a second evaluation. Various professional judgments concerning individual patients can then be compared and analyzed using kappa statistics or similar methods. Interpretation of results can be facilitated by providing examples or by translating the results into clinically meaningful summary sentences.
Conclusions: Measuring the uncertainty regarding management options for clinical problems may reveal substantial disagreements, provide an empirical foundation for the notions of clinical uncertainty and equipoise, and inform or facilitate the design/conduct of clinical trials to address the clinical dilemma.
Keywords
equipoise, uncertainty, randomized trials, methodology, clinical decision-making, agreement, reliability, kappa
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CURRENT STATUS: Published
View the published article at BMC Medical Research Methodology.
No community comments so far
Submission checks complete
On 04 Aug, 2020
Editorial decision: Accept
On 03 Aug, 2020
No comments provided
Editorial decision: Minor revision
On 30 Jul, 2020
Editor assigned
On 23 Jul, 2020
Submission checks complete
On 22 Jul, 2020
Editor invited
On 22 Jul, 2020
Version 2
Posted 01 Jun, 2020
No comments provided
Editorial decision: Minor revision
On 10 Jul, 2020
Review #2 received
Received 08 Jul, 2020
Reviewer #2 agreed
On 05 Jun, 2020
Review #1 received
Received 26 May, 2020
Reviewers invited
Invitations sent on 21 May, 2020
Reviewer #1 agreed
On 21 May, 2020
Editor assigned
On 20 May, 2020
Submission checks complete
On 19 May, 2020
Editor invited
On 19 May, 2020
No comments provided
Editorial decision: Major revision
On 17 Apr, 2020
Review #2 received
Received 16 Apr, 2020
Reviewer #2 agreed
On 25 Mar, 2020
Review #1 received
Received 23 Mar, 2020
Reviewers invited
Invitations sent on 17 Feb, 2020
Reviewer #1 agreed
On 17 Feb, 2020
Submission checks complete
On 31 Jan, 2020
Editor invited
On 31 Jan, 2020
Editor assigned
On 23 Jan, 2020
First submitted
On 22 Jan, 2020
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Subject Areas
Health Economics & Outcomes Research
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See the published version of this preprint at BMC Medical Research Methodology.
This is a preprint, 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
Jean Raymond
Centre Hospitalier de L'Universite de Montreal
Corresponding Author
ORCiD: https://orcid.org/0000-0003-1978-4274
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: Published
View the published article at BMC Medical Research Methodology.
No community comments so far
Submission checks complete
On 04 Aug, 2020
Editorial decision: Accept
On 03 Aug, 2020
No comments provided
Editorial decision: Minor revision
On 30 Jul, 2020
Editor assigned
On 23 Jul, 2020
Submission checks complete
On 22 Jul, 2020
Editor invited
On 22 Jul, 2020
Version 2
Posted 01 Jun, 2020
No comments provided
Editorial decision: Minor revision
On 10 Jul, 2020
Review #2 received
Received 08 Jul, 2020
Reviewer #2 agreed
On 05 Jun, 2020
Review #1 received
Received 26 May, 2020
Reviewers invited
Invitations sent on 21 May, 2020
Reviewer #1 agreed
On 21 May, 2020
Editor assigned
On 20 May, 2020
Submission checks complete
On 19 May, 2020
Editor invited
On 19 May, 2020
No comments provided
Editorial decision: Major revision
On 17 Apr, 2020
Review #2 received
Received 16 Apr, 2020
Reviewer #2 agreed
On 25 Mar, 2020
Review #1 received
Received 23 Mar, 2020
Reviewers invited
Invitations sent on 17 Feb, 2020
Reviewer #1 agreed
On 17 Feb, 2020
Submission checks complete
On 31 Jan, 2020
Editor invited
On 31 Jan, 2020
Editor assigned
On 23 Jan, 2020
First submitted
On 22 Jan, 2020
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
View the published article at BMC Medical Research Methodology.
Background: Clinical uncertainty and equipoise are vague notions that play important roles in contemporary problems of medical care and research, including the design and conduct of pragmatic clinical trials. Our goal was to show how the reliability study methods normally used to assess diagnostic tests can be applied to particular management decisions to measure the degree of clinical uncertainty and equipoise regarding the use of rival management options prior to the conduct of randomized trials.
Methods: We first illustrate how we have used the reliability study methodology to measure uncertainty in clinical decision-making regarding mechanical thrombectomy in acute stroke. We then follow the layout provided by standard guidelines to review how the various design elements of diagnostic reliability studies can be adapted to assess the repeatability of management decisions and measure clinical uncertainty.
Results: The example shows how this methodology can be used to show disagreement in decisions for thrombectomy, and justify that sufficient clinical uncertainty exists to warrant the conduct of additional randomized trials. The general method we propose is that a sufficient number of diverse individual cases sharing a similar clinical problem and covering a wide spectrum of clinical presentations be assembled into a portfolio that is submitted to a variety of clinicians who routinely manage patients with the clinical problem. Clinicians are asked to independently choose one of the predefined management options, which are selected from those that would be compared within a randomized trial that would address the clinical dilemma. Intra-rater agreement can be assessed at a later time with a second evaluation. Various professional judgments concerning individual patients can then be compared and analyzed using kappa statistics or similar methods. Interpretation of results can be facilitated by providing examples or by translating the results into clinically meaningful summary sentences.
Conclusions: Measuring the uncertainty regarding management options for clinical problems may reveal substantial disagreements, provide an empirical foundation for the notions of clinical uncertainty and equipoise, and inform or facilitate the design/conduct of clinical trials to address the clinical dilemma.
Figure 1
Figure 2
Figure 3
This is a list of supplementary files associated with this preprint. Click to download.
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