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Record W1510808013 · doi:10.1159/000360670

Current Issues in the Design of Clinical Trials in IBD

2014· article· en· W1510808013 on OpenAlexaff
Brian G. Feagan

Bibliographic record

VenueNestlé Nutrition Institute Workshop series · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsWestern University
Fundersnot available
KeywordsClinical trialMedicineIntensive care medicineDiseaseInflammatory bowel diseaseClinical study designRandomized controlled trialAlternative medicineClinical PracticeResearch designPhysical therapyMedical physicsRisk analysis (engineering)Pathology

Abstract

fetched live from OpenAlex

Although the randomized controlled trial has become the standard for regulatory approval of new drugs and devices in inflammatory bowel disease (IBD), the components of effective trial design and implementation are still evolving. While induction and maintenance of remission are the ultimate goals in the treatment of IBD, the conduct of trials intended to measure these outcomes has varied substantially over time, as have the definitions of disease remission. Significant progress has been made in recent years towards understanding patient- and disease-related factors that are essential considerations in clinical trial design. However, questions remain regarding the best methods for assessing disease activity, and importantly for establishing trial end points that are clinically relevant and likely to affect meaningful long-term improvements in disease outcomes. This chapter will discuss the current 'best methods' in IBD trial design and introduce potential future concepts for improving the efficiency of clinical trials as well as their utility to inform clinical practice management.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.099
GPT teacher head0.404
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2014
Admission routes1
Has abstractyes

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