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Record W1827097600 · doi:10.1517/14712598.2015.1065248

Subcutaneous abatacept in rheumatoid arthritis: current update

2015· review· en· W1827097600 on OpenAlexaff
Edward Keystone, Mosaab Makkawy

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2015
Typereview
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsAbataceptMedicineRheumatoid arthritisClinical trialImmunogenicityBiologic AgentsAdverse effectSafety profileIntensive care medicineInternal medicineOncologyImmunologyAntigenAntibody

Abstract

fetched live from OpenAlex

INTRODUCTION: A number of biologic agents have been approved for the treatment of rheumatoid arthritis (RA). They have changed the landscape of therapy and demonstrate substantial efficacy with a good safety record. One of these agents is intravenous (i.v.) abatacept (ABA), which has a novel mechanism of action by selectively inhibiting the interaction between T- and antigen-presenting cells. Recently, ABA administered by subcutaneous (s.c.) injection has also been approved for use in RA. In this review, will focus in recent data published in this agent. AREAS COVERED: This paper reviews Phase III clinical trials (ACQUIRE, ACCOMPANY, ALLOW, ATTUNE, AMPLE and AVERT) in terms of clinical efficacy including long-term efficacy, radiographic progression, safety and immunogenicity. EXPERT OPINION: Given the current trend in biologic therapy to s.c. administration, the availability of both i.v. and s.c. ABA provides considerable advantage both to patients and physicians in this competitive environment. The clinical trials have shown comparable efficacy and safety of s.c. ABA to i.v. ABA and others biologics.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.157
GPT teacher head0.421
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

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

Citations9
Published2015
Admission routes1
Has abstractyes

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