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Record W4391162439 · doi:10.1093/ecco-jcc/jjad212.1143

P1013 Placebo rates in Crohn's disease: An individual patient data meta-analysis from multiple randomised controlled trials

2024· article· en· W4391162439 on OpenAlexaff
Virginia Solitano, Malcolm Hogan, Siddharth Singh, Silvio Danese, Laurent Peyrin‐Biroulet, Alexa Zayadi, Guangyong Zou, Bruce E. Sands, Brian G. Feagan, Neeraj Narula, Christopher Ma, Vipul Jairath

Bibliographic record

VenueJournal of Crohn s and Colitis · 2024
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of CalgaryMcMaster UniversityPopulation Health Research InstituteWestern University
Fundersnot available
KeywordsCrohn's diseaseMeta-analysisPlaceboMedicineRandomized controlled trialPatient dataInternal medicineDiseaseAlternative medicineComputer sciencePathology

Abstract

fetched live from OpenAlex

Abstract Background Estimating placebo rates and their determinants is essential for designing efficient randomised clinical trials (RCTs) in inflammatory bowel disease. We conducted an individual patient data (IPD) meta-analysis of placebo data from RCTs in Crohn’s disease (CD). Methods MEDLINE, Embase, and CENTRAL were searched from 01/2010 to 01/2020 for contemporary phase 2 and 3 placebo-controlled RCTs of biologics in moderate-to-severe CD. De-identified IPD from eligible trials that were available through the Vivli and Yale University Open Data Access data-sharing platforms were obtained. Primary outcomes were placebo clinical response and remission. Pooled placebo rates and 95% CIs were estimated using a 2-stage meta-analytical approach. Significant patient-level factors (P<0.05) associated with placebo rates were identified using regression analyses. Results Placebo IPD were available from 8 induction (n=1147) and 4 maintenance trials (n=524). Pooled placebo clinical response and remission rates varied based on outcome definition and prior biologic exposure (Figure). In induction trials, overall placebo response and remission rates were 27% (95% CI 23-32%) and 10% (95% CI 8-14%), respectively. Among bio-exposed patients, placebo response and remission rates were 27% (95% CI 16-40%) and 9% (95% CI 6-15%), respectively, compared with 29% (95% CI 24-34%) and 11% (95% CI 8-15%) for bio-naïve patients. Overall placebo response and remission rates in maintenance trials were 32% (95% CI 23%-42%) and 22% (95% CI 14-33%), respectively. Corresponding placebo response and remission rates for bio-exposed patients were 21% (95% CI 8-46%) and 17% (95% CI 11-25%), and 36% (95% CI 28-44%) and 24% (95% CI 15-36%) for bio-naïve patients. Placebo rates were lowest when response was defined as a ≥100-point decrease from baseline in the Crohn's Disease Activity Index (CDAI) score, and when remission was defined using stool frequency (≤1.5) and abdominal pain (≤1) subscores. Higher baseline C-reactive protein concentrations were associated with lower odds of placebo response and remission, while higher baseline albumin levels increased the odds of these outcomes (Table). Increased baseline CDAI and 2-item patient-reported outcome (PRO2) scores predicted higher odds of placebo response in induction trials, yet this reduced the odds of remission in induction trials and of both outcomes in maintenance trials. Prior failure to tumour necrosis factor (TNF) antagonist therapy was more predictive than prior TNF antagonist/biologic exposure for reducing the odds of placebo response and remission. Conclusion Placebo rates and the patient-level factors influencing them vary according to study design, clinical outcome measure and outcome definitions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.141
metaresearch head score (Gemma)0.196
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.745

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1410.196
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0240.086
Bibliometrics0.0090.008
Science and technology studies0.0010.002
Scholarly communication0.0070.004
Open science0.0040.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.260
GPT teacher head0.452
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
DomainMethods
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

Citations0
Published2024
Admission routes1
Has abstractyes

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