Cargando…
Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification
INTRODUCTION: Adjudication of the primary outcome in randomised trials is thought to control misclassification. We investigated the amount of misclassification needed before adjudication changed the primary trial results. Patients (or materials) and methods: We included data from five randomised str...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313361/ https://www.ncbi.nlm.nih.gov/pubmed/32637651 http://dx.doi.org/10.1177/2396987320910047 |
_version_ | 1783549929110634496 |
---|---|
author | Godolphin, Peter J Bath, Philip M Partlett, Christopher Berge, Eivind Brown, Martin M Eliasziw, Misha Sandset, Per Morten Serena, Joaquín Montgomery, Alan A |
author_facet | Godolphin, Peter J Bath, Philip M Partlett, Christopher Berge, Eivind Brown, Martin M Eliasziw, Misha Sandset, Per Morten Serena, Joaquín Montgomery, Alan A |
author_sort | Godolphin, Peter J |
collection | PubMed |
description | INTRODUCTION: Adjudication of the primary outcome in randomised trials is thought to control misclassification. We investigated the amount of misclassification needed before adjudication changed the primary trial results. Patients (or materials) and methods: We included data from five randomised stroke trials. Differential misclassification was introduced for each primary outcome until the estimated treatment effect was altered. This was simulated 1000 times. We calculated the between-simulation mean proportion of participants that needed to be differentially misclassified to alter the treatment effect. In addition, we simulated hypothetical trials with a binary outcome and varying sample size (1000–10,000), overall event rate (10%–50%) and treatment effect (0.67–0.90). We introduced non-differential misclassification until the treatment effect was non-significant at 5% level. RESULTS: For the five trials, the range of unweighted kappa values were reduced from 0.89–0.97 to 0.65–0.85 before the treatment effect was altered. This corresponded to 2.1%–6% of participants misclassified differentially for trials with a binary outcome. For the hypothetical trials, those with a larger sample size, stronger treatment effect and overall event rate closer to 50% needed a higher proportion of events non-differentially misclassified before the treatment effect became non-significant. DISCUSSION: We found that only a small amount of differential misclassification was required before adjudication altered the primary trial results, whereas a considerable proportion of participants needed to be misclassified non-differentially before adjudication changed trial conclusions. Given that differential misclassification should not occur in trials with sufficient blinding, these results suggest that central adjudication is of most use in studies with unblinded outcome assessment. CONCLUSION: For trials without adequate blinding, central adjudication is vital to control for differential misclassification. However, for large blinded trials, adjudication is of less importance and may not be necessary. |
format | Online Article Text |
id | pubmed-7313361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-73133612020-07-06 Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification Godolphin, Peter J Bath, Philip M Partlett, Christopher Berge, Eivind Brown, Martin M Eliasziw, Misha Sandset, Per Morten Serena, Joaquín Montgomery, Alan A Eur Stroke J Original Research Articles INTRODUCTION: Adjudication of the primary outcome in randomised trials is thought to control misclassification. We investigated the amount of misclassification needed before adjudication changed the primary trial results. Patients (or materials) and methods: We included data from five randomised stroke trials. Differential misclassification was introduced for each primary outcome until the estimated treatment effect was altered. This was simulated 1000 times. We calculated the between-simulation mean proportion of participants that needed to be differentially misclassified to alter the treatment effect. In addition, we simulated hypothetical trials with a binary outcome and varying sample size (1000–10,000), overall event rate (10%–50%) and treatment effect (0.67–0.90). We introduced non-differential misclassification until the treatment effect was non-significant at 5% level. RESULTS: For the five trials, the range of unweighted kappa values were reduced from 0.89–0.97 to 0.65–0.85 before the treatment effect was altered. This corresponded to 2.1%–6% of participants misclassified differentially for trials with a binary outcome. For the hypothetical trials, those with a larger sample size, stronger treatment effect and overall event rate closer to 50% needed a higher proportion of events non-differentially misclassified before the treatment effect became non-significant. DISCUSSION: We found that only a small amount of differential misclassification was required before adjudication altered the primary trial results, whereas a considerable proportion of participants needed to be misclassified non-differentially before adjudication changed trial conclusions. Given that differential misclassification should not occur in trials with sufficient blinding, these results suggest that central adjudication is of most use in studies with unblinded outcome assessment. CONCLUSION: For trials without adequate blinding, central adjudication is vital to control for differential misclassification. However, for large blinded trials, adjudication is of less importance and may not be necessary. SAGE Publications 2020-02-26 2020-06 /pmc/articles/PMC7313361/ /pubmed/32637651 http://dx.doi.org/10.1177/2396987320910047 Text en © European Stroke Organisation 2020 |
spellingShingle | Original Research Articles Godolphin, Peter J Bath, Philip M Partlett, Christopher Berge, Eivind Brown, Martin M Eliasziw, Misha Sandset, Per Morten Serena, Joaquín Montgomery, Alan A Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification |
title | Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification |
title_full | Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification |
title_fullStr | Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification |
title_full_unstemmed | Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification |
title_short | Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification |
title_sort | outcome assessment by central adjudicators in randomised stroke trials: simulation of differential and non-differential misclassification |
topic | Original Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313361/ https://www.ncbi.nlm.nih.gov/pubmed/32637651 http://dx.doi.org/10.1177/2396987320910047 |
work_keys_str_mv | AT godolphinpeterj outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT bathphilipm outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT partlettchristopher outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT bergeeivind outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT brownmartinm outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT eliasziwmisha outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT sandsetpermorten outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT serenajoaquin outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification AT montgomeryalana outcomeassessmentbycentraladjudicatorsinrandomisedstroketrialssimulationofdifferentialandnondifferentialmisclassification |