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RRMS Patients Switching from SC IFNB-1a to Alemtuzumab in the CARE-MS I and II Extension Study Have a Reduced Rate of Brain Volume Loss (P6.183)

2016· article· en· W2595384992 on OpenAlexaff
Frederik Barkhof, Jeffrey A. Cohen, Alasdair Coles, Edward Fox, Hans‐Peter Hartung, Eva Havrdová, Krzysztof Selmaj, David Margolin, Karthinathan Thangavelu, Douglas L. Arnold

Bibliographic record

VenueNeurology · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsMcGill UniversityNeuroRx Research (Canada)Montreal Neurological Institute and Hospital
Fundersnot available
KeywordsAlemtuzumabExtension (predicate logic)MedicinePsychologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

Objective: To examine brain volume loss (BVL) before and after switching from SC IFNB-1a to alemtuzumab in the CARE-MS extension study (NCT00930553). Background: Active relapsing-remitting MS (RRMS) patients who were treatment-naive (CARE-MS I; NCT00530348) or who had an inadequate response (≥1 relapse) to prior therapy at baseline (CARE-MS II; NCT00548405) demonstrated 42[percnt] and 24[percnt] reduction, respectively, in brain atrophy rate with alemtuzumab versus SC IFNB-1a over 2 years. Durable slowing of BVL in patients who received core study alemtuzumab was observed through 5 years in the absence of additional treatment for most patients for 4 years. Design/Methods: Patients treated with SC IFNB-1a in the CARE-MS core studies for 2 years discontinued treatment and received 2 alemtuzumab courses at extension Months 0 and 12, then as-needed alemtuzumab retreatment for relapse or radiological activity. MRI scans were assessed at baseline and annually thereafter. BVL was derived by relative brain parenchymal fraction change. Results: The extension study enrolled 144 (83[percnt]) and 146 (83[percnt]) SC IFNB-1a-treated patients from CARE-MS I and II; 81[percnt] and 84[percnt] received no alemtuzumab retreatment since Month 12 after switching. Median yearly BVL in Year 2 on SC IFNB-1a in CARE-MS I (-0.50[percnt]) and CARE-MS II (-0.33[percnt]) was reduced in Years 1, 2, and 3 after switching to alemtuzumab (CARE-MS I: -0.07[percnt], -0.13[percnt], -0.09[percnt]; CARE-MS II: 0.02[percnt], -0.05[percnt], -0.14[percnt]). Despite this improvement, these patients still had 22[percnt] greater BVL at the end of Year 5 of the extension than those who received alemtuzumab in the core studies (CARE-MS I: -1.646[percnt] vs -1.352[percnt], and CARE-MS II: -1.044[percnt] vs -0.855[percnt]). Conclusions: Switching from SC IFNB-1a to alemtuzumab markedly slowed BVL over 3 years. Despite these beneficial effects, earlier use of alemtuzumab led to lower rates of BVL through 5 years. Study Supported By: Genzyme, a Sanofi company, and Bayer Healthcare Pharmaceuticals.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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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Citations2
Published2016
Admission routes1
Has abstractyes

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