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Record W2018724911 · doi:10.1007/s00415-011-6200-0

Challenges of clinical trial design when there is lack of clinical equipoise: use of a response-conditional crossover design

2011· article· en· W2018724911 on OpenAlexaff
C. Q. Deng, Kim Hanna, Vera Bril, Marinos C. Dalakas, Peter D. Donofrio, Pieter A. van Doorn, Hans‐Peter Hartung, Ingemar S. J. Merkies

Bibliographic record

VenueJournal of Neurology · 2011
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersGrifolsCSL BehringTeva Pharmaceutical Industries
KeywordsClinical trialCrossover studyClinical equipoiseMedicineClinical study designPlaceboRandomized controlled trialResearch designIntensive care medicineAlternative medicineInternal medicineStatisticsPathology

Abstract

fetched live from OpenAlex

Clinical equipoise is widely accepted as the basis of ethics in clinical research and requires investigators to be uncertain of the relative therapeutic merits of trial comparators. When clinical equipoise is in question, innovative trial designs are needed to reduce ethical tension while satisfying regulators' requirements. We report a novel response-conditional crossover study design used in a Phase 3, randomized, double-blind, placebo-controlled clinical trial of intravenous 10% caprylate-chromatography purified immunoglobulin for chronic inflammatory demyelinating polyradiculoneuropathy. During the initial 24-week period, patients crossed over to the alternative treatment at the first sign of deterioration or if they failed to improve or were unable to maintain improvement at any time after 6 weeks. This trial design addressed concerns about lack of equipoise raised by physicians interested in trial participation and proved acceptable to regulatory authorities. The trial design may be applicable to other studies where clinical equipoise is in question.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.173
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.173
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.687
GPT teacher head0.515
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2011
Admission routes1
Has abstractyes

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