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Record W1969604218 · doi:10.3899/jrheum.120258

Pharmacoeconomic Issues in Psoriatic Arthritis

2012· review· en· W1969604218 on OpenAlexvenueno aff
Ignazio Olivieri, Salvatore D’Angelo, Carlo Palazzi, Angela Padula, Ennio Lubrano, LG Mantovani

Bibliographic record

VenueJournal of Rheumatology Supplement · 2012
Typereview
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsoriatic arthritisAntirheumatic drugsDiseaseNonsteroidalPsoriasisTumor necrosis factor alphaQuality of life (healthcare)ArthritisIntensive care medicineJoint diseaseInternal medicineAntirheumatic AgentsDermatologyAlternative medicinePathologyOsteoarthritis

Abstract

fetched live from OpenAlex

Therapies for psoriatic arthritis were inadequate until a short time ago. Nonsteroidal antiinflammatory drugs are helpful in relieving symptoms but do not prevent joint damage. Traditional disease-modifying antirheumatic drugs are used to control symptoms, but there is no evidence that they prevent or significantly slow the progression of structural damage in peripheral joints. The introduction of tumor necrosis factor-α (TNF-α) blocking agents has opened new horizons. These drugs lessen signs and symptoms of inflammation, enhance functional capacity and quality of life, and inhibit structural joint damage. On the other hand, TNF-α blockers are very costly and not easily available to all patients, whether they rely on a national health system or on private insurance. Pharmacoeconomic studies on these drugs so far have shown that they are cost-effective on both the musculoskeletal and skin manifestations of psoriatic disease, offering good value for money.

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)0.000
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.374
Teacher spread0.332 · 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 designNot applicable
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

Citations12
Published2012
Admission routes1
Has abstractyes

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