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Record W2808497289 · doi:10.3310/hta22340

Alternative tumour necrosis factor inhibitors (TNFi) or abatacept or rituximab following failure of initial TNFi in rheumatoid arthritis: the SWITCH RCT

2018· article· en· W2808497289 on OpenAlexaff
Sarah Brown, Colin Everett, Kamran Naraghi, Claire Davies, Bryony Dawkins, Claire Hulme, Christopher McCabe, Sue Pavitt, Paul Emery, Linda Sharples, Maya H Buch

Bibliographic record

VenueHealth Technology Assessment · 2018
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity of Alberta
FundersHealth Technology Assessment ProgrammeNational Institute for Health and Care Research
KeywordsMedicineAbataceptRituximabRheumatoid arthritisInternal medicinePopulationTNF inhibitorRheumatologyRandomized controlled trialPhysical therapyAdalimumab

Abstract

fetched live from OpenAlex

BACKGROUND: Rheumatoid arthritis (RA), the most common autoimmune disease in the UK, is a chronic systemic inflammatory arthritis that affects 0.8% of the UK population. OBJECTIVES: To determine whether or not an alternative class of biologic disease-modifying antirheumatic drugs (bDMARDs) are comparable to rituximab in terms of efficacy and safety outcomes in patients with RA in whom initial tumour necrosis factor inhibitor (TNFi) bDMARD and methotrexate (MTX) therapy failed because of inefficacy. DESIGN: Multicentre, Phase III, open-label, parallel-group, three-arm, non-inferiority randomised controlled trial comparing the clinical and cost-effectiveness of alternative TNFi and abatacept with that of rituximab (and background MTX therapy). Eligible consenting patients were randomised in a 1 : 1 : 1 ratio using minimisation incorporating a random element. Minimisation factors were centre, disease duration, non-response category and seropositive/seronegative status. SETTING: UK outpatient rheumatology departments. PARTICIPANTS: Patients aged ≥ 18 years who were diagnosed with RA and were receiving MTX, but had not responded to two or more conventional synthetic disease-modifying antirheumatic drug therapies and had shown an inadequate treatment response to a first TNFi. INTERVENTIONS: Alternative TNFi, abatacept or rituximab (and continued background MTX). MAIN OUTCOME MEASURES: The primary outcome was absolute reduction in the Disease Activity Score of 28 joints (DAS28) at 24 weeks post randomisation. Secondary outcome measures over 48 weeks were additional measures of disease activity, quality of life, cost-effectiveness, radiographic measures, safety and toxicity. LIMITATIONS: Owing to third-party contractual issues, commissioning challenges delaying centre set-up and thus slower than expected recruitment, the funders terminated the trial early. RESULTS: = 40). The numbers, as specified, were analysed in each group [in line with the intention-to-treat (ITT) principle]. Comparing alternative TNFi with rituximab, the difference in mean reduction in DAS28 at 24 weeks post randomisation was 0.3 [95% confidence interval (CI) -0.45 to 1.05] in the ITT patient population and -0.58 (95% CI -1.72 to 0.55) in the per protocol (PP) population. Corresponding results for the abatacept and rituximab comparison were 0.04 (95% CI -0.72 to 0.79) in the ITT population and -0.15 (95% CI -1.27 to 0.98) in the PP population. General improvement in the Health Assessment Questionnaire Disability Index, Rheumatoid Arthritis Quality of Life and the patients' general health was apparent over time, with no notable differences between treatment groups. There was a marked initial improvement in the patients' global assessment of pain and arthritis at 12 weeks across all three treatment groups. Switching to alternative TNFi may be cost-effective compared with rituximab [incremental cost-effectiveness ratio (ICER) £5332.02 per quality-adjusted life-year gained]; however, switching to abatacept compared with switching to alternative TNFi is unlikely to be cost-effective (ICER £253,967.96), but there was substantial uncertainty in the decisions. The value of information analysis indicated that further research would be highly valuable to the NHS. Ten serious adverse events in nine patients were reported; none were suspected unexpected serious adverse reactions. Two patients died and 10 experienced toxicity. FUTURE WORK: The results will add to the randomised evidence base and could be included in future meta-analyses. CONCLUSIONS: How to manage first-line TNFi treatment failures remains unresolved. Had the trial recruited to target, more credible evidence on whether or not either of the interventions were non-inferior to rituximab may have been provided, although this remains speculative. TRIAL REGISTRATION: Current Controlled Trials ISRCTN89222125 and ClinicalTrials.gov NCT01295151. FUNDING: ; Vol. 22, No. 34. See the NIHR Journals Library website for further project information.

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)0.008
metaresearch head score (Gemma)0.009
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 score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.008
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.029
GPT teacher head0.389
Teacher spread0.360 · 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".

Quick stats

Citations34
Published2018
Admission routes1
Has abstractyes

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