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Record W3035067402 · doi:10.1177/1352458520930620

The introduction of new medications in pediatric multiple sclerosis: Open issues and challenges

2020· article· en· W3035067402 on OpenAlexaff
Angelo Ghezzi, Maria Pia Amato, Gilles Edan, Hans‐Peter Hartung, Eva Havrdová, Ludwig Kappos, Xavier Montalbán, Carlo Pozzilli, Per Soelber Sorensen, María Trojano, P. Vermersch, Giancarlo Comi

Bibliographic record

VenueMultiple Sclerosis Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsFingolimodMultiple sclerosisMedicineObservational studyRandomized controlled trialClinical trialClinical endpointIntensive care medicineEndpoint DeterminationInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Disease-modifying drugs (DMDs) for multiple sclerosis (MS) have been evaluated in pediatric patients in observational studies demonstrating a similar, even better clinical effect compared to adults, with a similar safety. Only fingolimod has been tested in a randomized controlled trial (RCT) and is approved for pediatric multiple sclerosis (ped-MS). Numerous methodological, practical, and ethical issues underline that RCTs are difficult to conduct in ped-MS. This also creates a lack of safety information. To facilitate the availability of new agents in ped-MS, we encourage to develop a different approach based on pharmacokinetic/pharmacodynamic studies to yield information on optimal doses and implementation of obligatory registries to obtain information on safety as primary endpoint.

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)0.162
metaresearch head score (Gemma)0.248
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.162
Threshold uncertainty score0.856

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1620.248
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0070.016
Open science0.0040.004
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0070.002

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 head0.252
GPT teacher head0.340
Teacher spread0.088 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2020
Admission routes1
Has abstractyes

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