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Subcutaneous Interferon Beta-1a Decreases the Evolution of Gadolinium-Enhancing Lesions Into Chronic Black Holes in Relapsing Multiple Sclerosis (P7.240)

2014· article· en· W1661382002 on OpenAlexaff
Anthony Traboulsee, David Li, Yinshan Zhao, Roger Tam, Guojun Zhao, Yan Cheng, Andrew Riddehough, Fernando Dangond, Juanzhi Fang, Ludwig Kappos

Bibliographic record

VenueNeurology · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMultiple sclerosisGadoliniumMedicineBETA (programming language)Interferon beta-1aInterferon betaPathologyImmunologyChemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: Assess the effect of subcutaneous (sc) interferon (IFN) beta-1a on evolution of gadolinium-enhancing (Gd+) lesions into chronic black holes (CBHs) in relapsing-remitting multiple sclerosis (MS). BACKGROUND: CBHs indicate irreversible axonal loss in MS. METHODS: Retrospective analysis of magnetic resonance imaging scans of patients who had monthly scans during the first 9 months of the PRISMS study and 蠅1 new T1 Gd+ lesion at Months -1 to 2/3. Images were reanalyzed to assess evolution of new Gd+ lesions at Months -1 to 2/3 into CBHs by Month 8/9. CBHs were defined as new T1 hypointense lesions (initially Gd+) persisting for 蠅6 months. Outcomes were analyzed for all patients receiving sc IFN beta-1a (44mcg and 22mcg groups combined) and placebo, and by Expanded Disability Status Scale (EDSS) categories (≤2.5, >2.5; ≤3.5, >3.5). RESULTS: 122 patients were included; mean (standard deviation [SD]) age 34.7 (7.6) years; 87 (71.3%) were female. For sc IFN beta-1a and placebo, respectively, mean (SD) number of new Gd+ lesions from Month -1 to 2/3 was 7.5 (16.5) and 8.7 (12.7); median (Q1, Q3) was 4.0 (1.0, 7.0) and 4.0 (2.0, 11.0). At Month 8/9, for sc IFN beta-1a and placebo, respectively, mean (SD) proportion of Gd+ lesions that evolved into CBHs was 12.6% (24.7%) and 19.8% (28.9%); median (Q1, Q3) was 0.0 (0.0, 12.5) and 6.3 (0.0, 28.6); p=0.033. Fewer patients had 蠅1 evolved CBH with sc IFN beta-1a (34.2%) versus placebo (55.1%; odds ratio 0.42; 95% confidence interval 0.20, 0.89; p=0.024). The treatment effect on the proportion of lesions evolving was most evident in the EDSS ≤3.5 subgroup (p=0.010). Mean (SD) volume of newly evolved CBHs was: sc IFN beta-1a, 66.0 (172.6); placebo, 118.3 (329.5) mm^3 (p=0.073). CONCLUSIONS: sc IFN beta-1a was associated with a decreased proportion of new Gd+ lesions evolving into CBHs, particularly in patients with lower disability scores. Study Support: Merck Serono SA Geneva, Switzerland, a subsidiary of Merck KGaA, Darmstadt, Germany

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.289
Teacher spread0.245 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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