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Record W4387890091 · doi:10.1016/s2665-9913(23)00241-2

Stratification of biological therapies by pathobiology in biologic-naive patients with rheumatoid arthritis (STRAP and STRAP-EU): two parallel, open-label, biopsy-driven, randomised trials

2023· article· en· W4387890091 on OpenAlexfundno aff
Felice Rivellese, Alessandra Nerviani, Giovanni Giorli, Louise Warren, Edyta Jaworska, Myles Lewis, Frances Humby, Arthur G. Pratt, Andrew Filer, Nagui Gendi, Alberto Cauli, Ernest Choy, Iain B. McInnes, Patrick Durez, Christopher J Edwards, Maya H Buch, Elisa Gremese, Peter C. Taylor, Nora Ng, Juan D. Cañete, Sabrina Raizada, Neil D McKay, Deepak R. Jadon, Pier Paolo Sainaghi, Richard Stratton, Michael R. Ehrenstein, Pauline Ho, Joaquim Polido‐Pereira, Bhaskar Dasgupta, Claire Gorman, James Galloway, Hector Chinoy, Désirée van der Heijde, Peter Sasieni, Anne Barton, Costantino Pitzalis, Ahmed S Zayat, Ana Rita Marinho Machado, Andrea Cuervo, Arti Mahto, Cankut Çubuk, Charlotte Rawlings, Chijioke H Mosanya, Christopher D. Buckley, Chris Holroyd, Debbie Maskall, Francesco Carlucci, Georgina Thorborn, Gina Tan, Gloria Lliso-Ribera, Hasan Rizvi, Joanna Peel, João Eurico Fonseca, John D. Isaacs, Julio Ramírez, Laurent Méric de Bellefon, Liliane Fossati-Jimak, Mary Ng’endo Githinji, Mattia Congia, Neal L. Millar, Nirupam Purkayastha, Raquel Celis, Rakhi Seth, Rebecca Hands-Greenwood, Robert Landewé, Simone Perniola, Stefano Alivernini, Stefano Marcia, Stefano Marini, Stephen Kelly, Vasco C. Romão

Bibliographic record

VenueThe Lancet Rheumatology · 2023
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersUCB PharmaUniversity College London Hospitals Biomedical Research CentreGenentechNordic Pharma GroupOno PharmaceuticalNational Institute for Health and Care ResearchArthritis SocietyBritish Society for RheumatologyArgenxMedical Research CouncilVersus ArthritisCelgeneBiogenGilead SciencesSanofiRocheAmgenPfizerAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsMedicineRheumatoid arthritisEtanerceptRituximabTocilizumabInternal medicineRheumatismRheumatologyPopulationClinical trialSurgeryLymphoma

Abstract

fetched live from OpenAlex

BACKGROUND: Despite highly effective targeted therapies for rheumatoid arthritis, about 40% of patients respond poorly, and predictive biomarkers for treatment choices are lacking. We did a biopsy-driven trial to compare the response to rituximab, etanercept, and tocilizumab in biologic-naive patients with rheumatoid arthritis stratified for synovial B cell status. METHODS: STRAP and STRAP-EU were two parallel, open-label, biopsy-driven, stratified, randomised, phase 3 trials done across 26 university centres in the UK and Europe. Biologic-naive patients aged 18 years or older with rheumatoid arthritis based on American College of Rheumatology (ACR)-European League Against Rheumatism classification criteria and an inadequate response to conventional synthetic disease-modifying antirheumatic drugs (DMARDs) were included. Following ultrasound-guided synovial biopsy, patients were classified as B cell poor or B cell rich according to synovial B cell signatures and randomly assigned (1:1:1) to intravenous rituximab (1000 mg at week 0 and week 2), subcutaneous tocilizumab (162 mg per week), or subcutaneous etanercept (50 mg per week). The primary outcome was the 16-week ACR20 response in the B cell-poor, intention-to-treat population (defined as all randomly assigned patients), with data pooled from the two trials, comparing etanercept and tocilizumab (grouped) versus rituximab. Safety was assessed in all patients who received at least one dose of study drug. These trials are registered with the EU Clinical Trials Register, 2014-003529-16 (STRAP) and 2017-004079-30 (STRAP-EU). FINDINGS: Between June 8, 2015, and July 4, 2019, 226 patients were randomly assigned to etanercept (n=73), tocilizumab (n=74), and rituximab (n=79). Three patients (one in each group) were excluded after randomisation because they received parenteral steroids in the 4 weeks before recruitment. 168 (75%) of 223 patients in the intention-to-treat population were women and 170 (76%) were White. In the B cell-poor population, ACR20 response at 16 weeks (primary endpoint) showed no significant differences between etanercept and tocilizumab grouped together and rituximab (46 [60%] of 77 patients vs 26 [59%] of 44; odds ratio 1·02 [95% CI 0·47-2·17], p=0·97). No differences were observed for adverse events, including serious adverse events, which occurred in six (6%) of 102 patients in the rituximab group, nine (6%) of 108 patients in the etanercept group, and three (4%) of 73 patients in the tocilizumab group (p=0·53). INTERPRETATION: In this biologic-naive population of patients with rheumatoid arthrtitis, the dichotomic classification into synovial B cell poor versus rich did not predict treatment response to B cell depletion with rituximab compared with alternative treatment strategies. However, the lack of response to rituximab in patients with a pauci-immune pathotype and the higher risk of structural damage progression in B cell-rich patients treated with rituximab warrant further investigations into the ability of synovial tissue analyses to inform disease pathogenesis and treatment response. FUNDING: UK Medical Research Council and Versus Arthritis.

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)0.012
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.080
GPT teacher head0.347
Teacher spread0.268 · 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 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".

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Citations68
Published2023
Admission routes1
Has abstractyes

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