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Effect of Delayed-Release Dimethyl Fumarate on Total Disability Burden in the CONFIRM Study of Relapsing-Remitting Multiple Sclerosis: Area Under the Curve Analysis of Changes from Baseline in Expanded Disability Status Scale Scores (P7.233)

2015· article· en· W1561633407 on OpenAlexaff
Nuwan Kurukulasuriya, Robert J. Fox, Ralf Gold, James Xiao, Annie Zhang, Amit Bar‐Or

Bibliographic record

VenueNeurology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFungal Plant Pathogen Control
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsDimethyl fumarateRelapsing remittingMultiple sclerosisMedicineBaseline (sea)Physical medicine and rehabilitationPhysical therapyImmunologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Quantify the effect of delayed-release dimethyl fumarate (DMF; also known as gastro-resistant DMF) on total disability burden in the Phase 3 CONFIRM study of relapsing-remitting multiple sclerosis (RRMS) using area under the Expanded Disability Status Scale (EDSS)-time curve (AUC) to integrate all measured EDSS progression and improvement over the 2-year study period. BACKGROUND: Quantifying on-treatment disability changes in RRMS patients over time may inform treatment decisions. Compared with traditional disability progression analysis, AUC analysis contains more information about the cumulative extent of disability over time because it considers all EDSS scores over the study period. DESIGN/METHODS: RRMS patients were randomized to placebo, DMF 240 mg BID or TID, or glatiramer acetate (GA) for up to 2 years. EDSS scores were assessed at 12-week intervals. For AUC analysis, EDSS change scores were computed relative to baseline (week 0). AUC of EDSS change scores was calculated for all patients, with imputation applied for missing scores; treatment groups were compared in mean EDSS AUC change, adjusted for covariates, using ANCOVA ranked data. Positive AUC change indicates net worsening in EDSS from baseline; negative AUC change indicates net improvement in EDSS from baseline. RESULTS: A total of 363, 359, and 350 patients received placebo, DMF BID, and GA, respectively, in CONFIRM. Two-year mean (standard error of the mean [SE]) AUC change in EDSS was 0.075 (0.062) for placebo. Compared with placebo, the mean differences in AUC change in EDSS (SE) were 0.110 (0.084) and 0.034 (0.090) for DMF BID (P=0.0375) and GA (P=0.5523), respectively. Results for the Phase 3 DEFINE study will also be reported. CONCLUSIONS: AUC analysis suggests a positive benefit of DMF on a measure of total disability burden. Patients receiving DMF had a better overall experience with respect to disability compared with placebo. Study Supported by: Biogen Idec

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)0.004
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 score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.040
GPT teacher head0.254
Teacher spread0.213 · 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
Published2015
Admission routes1
Has abstractyes

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