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Record W4213002005 · doi:10.2340/actadv.v102.1984

Time to Loss of Response following Withdrawal of Ixekizumab in Patients with Moderate-to-Severe Psoriasis

2022· article· en· W4213002005 on OpenAlexaff
Kim Papp, C. Paul, C. Elise Kleyn, Yu‐Huei Huang, Tsen‐Fang Tsai, Christopher Schuster, Céline El Baou, A. Tóth, Elisabeth Riedl, Ulrich Mrowietz

Bibliographic record

VenueActa Dermato Venereologica · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsProbity Medical Research
FundersEli Lilly and Company
KeywordsIxekizumabMedicineConfidence intervalPsoriasisPlaceboPost-hoc analysisRandomized controlled trialClinical trialInternal medicinePsoriasis Area and Severity IndexDermatologyAlternative medicine

Abstract

fetched live from OpenAlex

In clinical practice, interruption of treatment may not result in immediate cessation of disease control, and some patients even experience sustained treatment response following treatment interruption. This post hoc analysis of UNCOVER-1 and -2 Phase 3 clinical trials characterized the time to loss of treatment response in patients with psoriasis who responded to ixekizumab through a 12-week treatment period, and who were then re-randomized to placebo for the following 48 weeks. For those with static Physician Global Assessment [sPGA]0/1 and Psoriasis Area and Severity Index [PASI]90 at Week 12, the median time to loss of PASI90 was 16.1 weeks (95% confidence interval 12.7-16.4). For those with PASI100 at Week 12, the median time to loss of PASI100 was 12.1 weeks (95% confidence interval 9.0-13.0). A small subset of patients maintained high levels of disease control through Week 60. This study adds to the growing body of evidence on sustained treatment response following treatment interruption.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueActa Dermato VenereologicaSame topicPsoriasis: Treatment and PathogenesisFrench-language works237,207