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076 Assessment of pain improvement in rheumatoid arthritis patients treated with baricitinib, who were inadequate responders to methotrexate and tumor necrosis factor inhibitors

2019· article· en· W2936880304 on OpenAlexaff
Peter C. Taylor, Roy Fleischmann, Tsutomu Takeuchi, Janet Pope, Mark C. Genovese, Baojin Zhu, C. Gaich, Xiang Zhang, Christina Dickson, Amanda Quebe, Francesco De Leonardis, Anabela Cardoso, Ilias Kouris, Patrick Durez

Bibliographic record

VenueLara D. Veeken · 2019
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsSt Joseph's Health Care
Fundersnot available
KeywordsMedicineRheumatoid arthritisMethotrexateTumor necrosis factor αTumor necrosis factor alphaInternal medicineArthritisOncologySurgeryPhysical therapy

Abstract

fetched live from OpenAlex

Background: During the development programme, baricitinib (BARI) demonstrated greater and faster pain relief relative to placebo (PBO) and active comparator in different RA populations. Here, we summarise the findings from two recent post hoc analyses focused on the effect of BARI on pain in two clinically relevant patient populations: methotrexate-inadequate responders (MTX-IR; RA-BEAM) and tumor necrosis factor inhibitor-inadequate responders (TNFi-IR; RA-BEACON). Methods: In both clinical trials (RA-BEAM and RA-BEACON), pain was assessed with a visual analog scale (VAS, 0-100 mm) at each study visit. In RA-BEAM, 1,305 patients on stable background MTX were randomized 3:3:2 to PBO, BARI 4-mg, or adalimumab (ADA) 40-mg. The likelihood of achieving ⩾30%, ⩾50%, and ⩾70% pain VAS improvement through Week 24 and the median time when 50% of patients achieved these pain improvement thresholds was assessed with Cox proportional hazard models and the cumulative incidence estimate. Analyses were not adjusted for multiplicity. In RA-BEACON, 527 patients were randomised to placebo (n = 176), BARI 2-mg (n = 174), or 4-mg (n = 177) once daily for 24 weeks. Approximately 40% of patients had received >1 TNF inhibitor and a quarter of patients had received ⩾3 bDMARDs, representing patients with highly refractory disease. The proportion of patients achieving ⩾30%, ⩾50%, and ⩾70% pain relief at Week-12 was compared between BARI 2-mg or 4-mg and PBO using logistic models. Missing pain values were imputed using modified last observation-carried-forward. Results: In the MTX-IR population, BARI-treated patients were more likely to achieve at least 30%, 50%, and 70% pain improvement than PBO and ADA with HR of 1.7, 1.9 and 2.5, respectively (p < 0.001) compared to PBO, and 1.1 (p = 0.145), 1.2 (p = 0.032) and 1.3 (p = 0.003) compared to ADA. The median time for 50% of patients to achieve at least 30%, 50%, and 70% pain improvement, respectively, was 1.9, 4.0 and 12.4 weeks for BARI, 2.0, 7.9 and 20.0 weeks for ADA, and 4.6, 14.0 and >24 weeks for PBO. In the TNFi-IR population, at Week-12, significantly more patients achieved ⩾30%, ⩾50%, and ⩾70% pain relief with BARI 2-mg or 4-mg vs PBO (p < 0.05, for all comparisons). Consistent improvements were observed regardless of baseline pain. Regardless of treatment history, patients receiving BARI 2-mg or 4-mg were more likely to reach all pain relief thresholds than placebo. Conclusion: In both MTX-IR and TNFi-IR populations, BARI demonstrated greater pain improvement than comparators at Weeks 24 and 12, respectively. Disclosures: P.C. Taylor: Grants/research support; Celgene, Eli lilly and company, Galapagos, UBC. Consultant for: AbbVie, Eli Lilly and Company, Galapagos, GlaxoSmithKline, Pfizer, UCB, Biogen, Sandoz, Novartis, Gilead and Janssen. R. Fleischmann: Consultancies; AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Celltrion, GSK, Janssen, Eli Lilly and company, Novartis, Pfizer, Samsung, Sanofi-Aventis, tahio. Grants/research support; AbbVie, Amgen, AstraZeneca, Bristol-Myers squibb, Celgene, Centrexion, Genetech, GlaxosmithKline, Janssen, Eli Lilly and company, Merck, Pfizer, Regeneron, Roche, Sanofi, Aventis, UCB. T. Takeuchi: Grants/research support; AbbVie, Asahi Kasei Medical, Astellas Pharma, AstraZeneca, BMS, Chugai Pharma, Daiichi Sankyo, Eisai, Lilly, Janssen, Mitsubishi Tanabe Pharma, Nipponkayaku, Novartis, Pfizer Japan, Takeda, Taiho, Tai. J. Pope: Consultancies; AbbVie, Amgen, Bayer, BMS, Celtrion, Lilly, Merck, Novartis, Pfizer, Roche, UCB. Grants/research support; Amgen, Bayer, BMS, GSK, Merck, Novartis, Pfizer, Roche, UCB, M.C. Genovese: Grants/research support; Eli Lilly and Company, Abbvie. B. Zhu: Other; Employee of Eli Lilly and Company. C. Gaich: Shareholder/stock ownership; Eli Lilly and Company. Other; Employee of Eli Lilly and Company. X. Zhang: Other; Employee of Eli Lilly and Company. C. Dickson: Other; Employee at Eli Lilly and Company. A. Quebe: Shareholder/stock ownership; Eli Lilly and Company. Other; Employee of Eli Lilly and Company. F. De Leonardis: Shareholder/stock ownership; Eli Lilly and Company. Other; Employee of Eli Lilly and Company. A. Cardoso: Shareholder/stock ownership; Eli Lilly and Company. Other; Employee of Eli Lilly and Company. I. Kouris: Other; Employee of Eli Lilly and Company. P. Durez: Consultancies; Lilly, BMS, Merck, Pfizer, Sanofi, Janssen. Honoraria; Lilly, BMS, Merck, Pfizer, Sanofi, Janssen.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0020.000

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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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 designObservational
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".

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Citations0
Published2019
Admission routes1
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