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Record W2169804509 · doi:10.1586/14737167.2014.933671

The economic burden of psoriasis: a systematic literature review

2014· review· en· W2169804509 on OpenAlexaboutno aff
Steven R. Feldman, Chakkarin Burudpakdee, Smeet Gala, Merena Nanavaty, Usha G. Mallya

Bibliographic record

VenueExpert Review of Pharmacoeconomics & Outcomes Research · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsnot available
Fundersnot available
KeywordsPsoriasisIndirect costsMedicineSystematic reviewEconomic costMEDLINEBusinessEconomicsPolitical scienceDermatologyAccounting

Abstract

fetched live from OpenAlex

Costs associated with psoriasis present a considerable economic burden. A previously published review was lacking comprehensive data on biologics. Therefore, a systematic literature review was performed to gain a comprehensive understanding of the economic burden of psoriasis throughout the world. Studies published in the English language between January 2001 and May 2013 reporting the direct and indirect economic burden of psoriasis were identified from PubMed and conference proceedings. Thirty-five studies from 11 countries met the inclusion criteria. In 2004, the annual total cost (direct and indirect) in the USA alone was approximately US$1.40 billion. Among the European countries, the most recent studies reported an annual total cost per patient of €11,928 in Sweden, €8372 in Italy, €2866-6707 in Germany and CDN$7999 in Canada, based on treatment type. Costs associated with psoriasis are high in many countries, indicating a continued need for treatments that offer 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 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)0.005
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0140.013
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.044
GPT teacher head0.472
Teacher spread0.428 · 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 designSystematic review
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

Citations81
Published2014
Admission routes1
Has abstractyes

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