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Record W2009841271 · doi:10.1586/17474124.2015.1024657

Comparative efficacy of golimumab, infliximab, and adalimumab for moderately to severely active ulcerative colitis: a network meta-analysis accounting for differences in trial designs

2015· article· en· W2009841271 on OpenAlexaff
Kristian Thorlund, Eric Druyts, Kabirraaj Toor, Edward J. Mills

Bibliographic record

VenueExpert Review of Gastroenterology & Hepatology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of British ColumbiaMcMaster University
Fundersnot available
KeywordsMedicineGolimumabAdalimumabInfliximabBiostatisticsUlcerative colitisEpidemiologyFamily medicinePopulationInternal medicineEnvironmental healthDisease

Abstract

fetched live from OpenAlex

Kristian Thorlund*ab, Eric Druytsac, Kabirraaj Toorad & Edward J Millsaa 1Redwood Outcomes, Vancouver, British Columbia, Canadab 2Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canadac 3Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canadad 4School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada*Author for correspondence: thorluk@mcmaster.caAim: To conduct a network meta-analysis (NMA) to establish the comparative efficacy of infliximab, adalimumab and golimumab for the treatment of moderately to severely active ulcerative colitis (UC). Design: A systematic literature search identified five randomized controlled trials for inclusion in the NMA. One trial assessed golimumab, two assessed infliximab and two assessed adalimumab. Outcomes included clinical response, clinical remission, mucosal healing, sustained clinical response and sustained clinical remission. Innovative methods were used to allow inclusion of the golimumab trial data given the alternative design of this trial (i.e., two-stage re-randomization). Results: After induction, no statistically significant differences were found between golimumab and adalimumab or between golimumab and infliximab. Infliximab was statistically superior to adalimumab after induction for all outcomes and treatment ranking suggested infliximab as the superior treatment for induction. Golimumab and infliximab were associated with similar efficacy for achieving maintained clinical remission and sustained clinical remission, whereas adalimumab was not significantly better than placebo for sustained clinical remission. Golimumab and infliximab were also associated with similar efficacy for achieving maintained clinical response, sustained clinical response and mucosal healing. Finally, golimumab 50 and 100 mg was statistically superior to adalimumab for clinical response and sustained clinical response, and golimumab 100 mg was also statistically superior to adalimumab for mucosal healing. Conclusion: The results of our NMA suggest that infliximab was statistically superior to adalimumab after induction, and that golimumab was statistically superior to adalimumab for sustained outcomes. Golimumab and infliximab appeared comparable in efficacy.

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)0.049
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.073
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0160.058
Bibliometrics0.0080.006
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.367
Teacher spread0.250 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations59
Published2015
Admission routes1
Has abstractyes

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