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Phase II trial of methotrexate in myasthenia gravis

2012· article· en· W1765269564 on OpenAlexaboutno aff
Mamatha Pasnoor, Jianghua He, Laura Herbelin, Mazen M. Dimachkie, Richard J. Barohn

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2012
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesU.S. Food and Drug Administration
KeywordsPrednisoneMethotrexateMedicineMyasthenia gravisInternal medicinePlaceboCorticosteroidRandomized controlled trialCyclophosphamideGastroenterologyPharmacologyChemotherapyPathology

Abstract

fetched live from OpenAlex

Prednisone is a frequently used treatment for myasthenia gravis (MG) but it has numerous side effects. Methotrexate is a selective inhibitor of dihydrofolate reductase and lymphocyte proliferation and is an effective immuosuppressive medication for autoimmune diseases. Given the negative results of the mycophenolate mofetil study, search for an effective immunosuppressant drug therapy is ongoing. The objective is to determine if oral methotrexate is safe and effective for MG patients who take prednisone. We have initiated a randomized, double-blind, placebo-controlled multicenter trial of methotrexate versus placebo in patients taking at least 10 mg/day of prednisone at enrollment. The methotrexate dose is increased to 20 mg and the prednisone dose is adjusted per protocol during the study. Clinical and laboratory evaluations are performed monthly for 12 months, with the primary efficacy measure being the nine-month prednisone area under the curve (AUC) from months 3 to 12. Secondary outcome measures include MG outcomes, quality of life measures, and a polyglutamation biomarker assay. A total of 18 U.S. sites and 2 Canadian sites are participating, with 48 screened cases, 42 enrolled, with 19 still active in the study.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.158
GPT teacher head0.417
Teacher spread0.258 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations21
Published2012
Admission routes1
Has abstractyes

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