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Record W3186349681 · doi:10.1177/20552173211024298

Treatment-emergent adverse events occurring early in the treatment course of cladribine tablets in two phase 3 trials in multiple sclerosis

2021· article· en· W3186349681 on OpenAlexaff
Jiwon Oh, Bryan Walker, Gavin Giovannoni, Dominic Jack, Fernando Dangond, Axel Nolting, Julie Aldridge, Lori Lebson, Thomas Leist

Bibliographic record

VenueMultiple Sclerosis Journal - Experimental Translational and Clinical · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsCladribineMultiple sclerosisAdverse effectMedicinePhase (matter)PharmacologyInternal medicinePsychiatryChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Treatment-emergent adverse events (TEAEs) that occur close to treatment initiation may negatively affect overall tolerability and adherence. It is important to develop a clear understanding of potential early TEAEs after initiating treatment with cladribine tablets. OBJECTIVE: To identify TEAEs that begin early in the course of treatment in patients enrolled in CLARITY and ORACLE-MS studies. METHODS: analysis of CLARITY and ORACLE-MS safety populations assessed the incidence of TEAEs, serious TEAEs, drug-related TEAEs, and TEAEs leading to discontinuation in patients receiving cladribine tablets or placebo within 2, 6, and 12 weeks after treatment initiation. RESULTS: By Week 12, 61.3% of patients treated with cladribine tablets 3.5 mg/kg and 55.2% treated with placebo experienced a TEAE. More patients receiving cladribine tablets versus placebo experienced a drug-related TEAE by Week 12 (34.7% vs. 23.2%). The most common TEAEs reported with cladribine tablets were: headache (7.2%), lymphopenia (6.8%), and nausea (6.0%). Patients receiving cladribine tablets and placebo reported similar proportions of serious TEAEs (2.2% vs. 1.7%) and TEAEs leading to treatment discontinuation (1.6% vs. 1.4%). CONCLUSION: Cladribine tablets were well tolerated during the first 12 weeks as evidenced by a low incidence of TEAEs leading to treatment discontinuation.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.386
GPT teacher head0.477
Teacher spread0.091 · 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 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

Citations10
Published2021
Admission routes1
Has abstractyes

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