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Record W4400552116 · doi:10.1016/j.jdrv.2024.06.007

The efficacy and safety of switching between interleukin inhibitors in psoriasis therapy: A systematic review

2024· review· en· W4400552116 on OpenAlexaff
Ahmed Bagit, Siddhartha Sood, Sauliha Alli, Khalad Maliyar, Jorge R. Georgakopoulos, Muskaan Sachdeva, Asfandyar Mufti, Jensen Yeung

Bibliographic record

VenueJAAD reviews. · 2024
Typereview
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsProbity Medical ResearchHealth Sciences CentreSunnybrook Health Science CentreWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsPsoriasisMedicineInterleukinIntensive care medicineDermatologyImmunologyCytokine

Abstract

fetched live from OpenAlex

Switching between biologics has become increasingly common in dermatology clinics, particularly in treating moderate-to-severe plaque psoriasis. Documented evidence in literature extensively examines the outcomes of switching between older generation and newer generation biologic therapies.1,2 However, the understanding of the safety and efficacy outcomes of switching between biologics within the same class, particularly among interleukin (IL) inhibitors, remains inadequate. As such, we conducted a systematic review investigating the safety and efficacy of intraclass switching within IL inhibitors in plaque psoriasis treatment.

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)0.004
metaresearch head score (Gemma)0.017
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.324
Teacher spread0.278 · 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

Citations0
Published2024
Admission routes1
Has abstractno

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