Evidence map›Paper›PMID 27895297›Full record

ArticleStroke2016

Power of an Adaptive Trial Design for Endovascular Stroke Studies: Simulations Using IMS (Interventional Management of Stroke) III Data.

Maarten G Lansberg, Ninad S Bhat, Sharon D Yeatts, Yuko Y Palesch, Joseph P Broderick, Gregory W Albers, Tze L Lai, Philip W Lavori

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Stroke, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Maarten G LansbergFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.). lansberg@stanford.edu.
Ninad S BhatFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.).
Sharon D YeattsFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.).
Yuko Y PaleschFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.).
Joseph P BroderickFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.).
Gregory W AlbersFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.).
Tze L LaiFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.).
Philip W LavoriFrom the Stanford Stroke Center, School of Medicine (M.G.L., N.S.B., G.W.A.), Department of Statistics (T.L.L., P.W.L.), Department of Biomedical Data Science, School of Medicine (T.L.L., P.W.L.), Stanford University, CA; Department of Public Health Sciences, Medical University of South Carolina, Charleston (S.D.Y., Y.Y.P.); and Department of Neurology, University of Cincinnati Medical Center, OH (J.P.B.).

Funding

Spectrum Stanford Center for clinical and Translational Research and EducationUL1TR001085 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$37.1M
NSTN National Clinical Coordinating CenterU01NS086872 · NINDS · UNIVERSITY OF CINCINNATI · PI Joseph Paul Broderick, Pooja Khatri · 2013 to 2026
$32.3M
Workshop to Identify Collaborative Project(s) for the NIH StrokeNet and the Japan NEtwork for Clinical Stroke Trials (NECST)U01NS087748 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Catherine R. Dillon, Jordan J. Elm · 2014 to 2026
$14.1M
CTP to predict Response to recanalization in Ischemic Stroke Project (CRISP)R01NS075209 · NINDS · STANFORD UNIVERSITY · PI LANSBERG, MAARTEN G · 2011 to 2023
$6.0M
Stanford University Regional Coordinating Stroke Center for the NINDS Stroke TriaU10NS086487 · NINDS · STANFORD UNIVERSITY · PI ALBERS, GREGORY W · 2013 to 2017
$1.9M
NCATS NIH HHS UL1 TR001085NINDS NIH HHS R01 NS075209NINDS NIH HHS U01 NS086872NINDS NIH HHS U01 NS087748NINDS NIH HHS U10 NS086487
6 · The paper itself

Abstract

background and purposeAdaptive trial designs that allow enrichment of the study population through subgroup selection can increase the chance of a positive trial when there is a differential treatment effect among patient subgroups. The goal of this study is to illustrate the potential benefit of adaptive subgroup selection in endovascular stroke studies.

methodsWe simulated the performance of a trial design with adaptive subgroup selection and compared it with that of a traditional design. Outcome data were based on 90-day modified Rankin Scale scores, observed in IMS III (Interventional Management of Stroke III), among patients with a vessel occlusion on baseline computed tomographic angiography (n=382). Patients were categorized based on 2 methods: (1) according to location of the arterial occlusive lesion and onset-to-randomization time and (2) according to onset-to-randomization time alone. The power to demonstrate a treatment benefit was based on 10 000 trial simulations for each design.

resultsThe treatment effect was relatively homogeneous across categories when patients were categorized based on arterial occlusive lesion and time. Consequently, the adaptive design had similar power (47%) compared with the fixed trial design (45%). There was a differential treatment effect when patients were categorized based on time alone, resulting in greater power with the adaptive design (82%) than with the fixed design (57%).

conclusionsThese simulations, based on real-world patient data, indicate that adaptive subgroup selection has merit in endovascular stroke trials as it substantially increases power when the treatment effect differs among subgroups in a predicted pattern.

Indexed as

Clinical Trials as TopicComputer SimulationEndovascular ProceduresHumansOutcome Assessment, Health CareResearch DesignStrokeadaptive trial designendovascular techniquesstroke

Identifiers

PMID27895297
PMCPMC5134921

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.