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Record W4328052704 · doi:10.1093/bjd/ljad081

Safety of guselkumab in patients with psoriasis with a history of malignancy: 5-year results from the VOYAGE 1 and VOYAGE 2 trials

2023· article· en· W4328052704 on OpenAlexaff
Andrew Blauvelt, Diamant Thaçi, Kim Papp, Vincent Ho, Kamran Ghoreschi, Byung‐Soo Kim, Megan Miller, Yaung‐Kaung Shen, Yin You, Daphne Chan, Jenny Yu, Ya‐Wen Yang, Mark Lebwohl, Alice B. Gottlieb, Jeffrey Crowley, Peter Foley

Bibliographic record

VenueBritish Journal of Dermatology · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsUniversity of British ColumbiaProbity Medical Research
FundersJanssen Research and DevelopmentSt Vincent's Hospital MelbournePusan National University HospitalHumboldt-Universität zu BerlinJanssen Scientific AffairsFreie Universität BerlinPusan National UniversityBerlin Institute of HealthUniversity of Melbourne
KeywordsMedicineMalignancyPsoriasisDermatologySkin cancerBreast cancerCancerPopulationFamily historyInternal medicine

Abstract

fetched live from OpenAlex

The VOYAGE 1 and 2 studies of guselkumab in moderate-to-severe psoriasis are among the first studies of biologics to include patients with a history of malignancy. In these studies, 18 guselkumab-treated patients had a history of malignancy (excluding nonmelanoma skin cancer) > 5 years prior to enrolment. These 18 patients were exposed to guselkumab for up to 5 years; during this time, one patient had a recurrence of bronchial carcinoma, and three patients developed new malignancies (breast cancer, melanoma and sebaceous carcinoma). All patients with new or recurrent malignancies had underlying risk factors for malignancy. Overall, the results of this analysis in a small population of patients with a history of malignancy support the favourable long-term safety profile of guselkumab.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.002
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 head0.016
GPT teacher head0.211
Teacher spread0.195 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of DermatologySame topicPsoriasis: Treatment and PathogenesisFrench-language works237,207