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Abatacept in the treatment of rheumatoid arthritis

2007· review· en· W1577414370 on OpenAlexaboutno aff
Derrick J. Todd, Karen H. Costenbader, Michael E. Weinblatt

Bibliographic record

VenueInternational Journal of Clinical Practice · 2007
Typereview
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsAbataceptMedicineRheumatoid arthritisEtanerceptContext (archaeology)ImmunologyImmunotherapyInfliximabClinical trialTumor necrosis factor alphaInternal medicineOncologyImmune systemRituximabLymphoma

Abstract

fetched live from OpenAlex

Over the past decade, biological immunotherapy has revolutionised the treatment of rheumatoid arthritis (RA). The most widely used of these therapies targets tumour necrosis factor-alpha (TNF-alpha). Approximately 20% of patients fail to respond to TNF-alpha antagonism, however, and a significant number of additional patients become refractory to anti-TNF-alpha therapy over time. Thus investigators have sought to target other pathogenic elements of RA using novel biological therapies. Abatacept is the first immunotherapy directed against the process of T-cell costimulation. Abatacept has shown clinical effectiveness in RA by improving disease activity, quality of life measures and radiographic progression of disease. In this article, we review the immunology of T-cell activation and costimulation, define the role of abatacept in this process, and discuss the clinical trials that led to the approval of abatacept as the latest biological therapy in RA in the USA and Canada. We also address the role of abatacept in the greater context of biological therapy for RA.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.219
GPT teacher head0.570
Teacher spread0.351 · 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 teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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

Citations24
Published2007
Admission routes1
Has abstractyes

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