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Record W4415671084 · doi:10.1177/20552173251390649

Safety reporting quality in multiple sclerosis clinical trials: A review of phase III clinical trials included in FDA approval of disease-modifying treatments

2025· review· en· W4415671084 on OpenAlexaff
William Z. Lin, Jaimie J. Lee, Aníbal Chertcoff, Helen Tremlett, John L. K. Kramer

Bibliographic record

VenueMultiple Sclerosis Journal - Experimental Translational and Clinical · 2025
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of ManitobaInternational Collaboration On Repair DiscoveriesUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsClinical trialMultiple sclerosisQuality (philosophy)Phase (matter)Phases of clinical researchMEDLINEFingolimod

Abstract

fetched live from OpenAlex

Background: Evaluating safety of emerging interventions is important in clinical trials. To support reporting of safety outcomes, a harms extension of the Consolidated Standards of Reporting Trial (CONSORT) guidelines was published in 2004. Objective: To examine safety reporting in pivotal trials of disease-modifying therapies (DMTs) in patients with multiple sclerosis (MS). Methods: Published phase III clinical trials from 1995 to 2022 included in FDA approval material for MS DMTs were compiled and reviewed by two independent examiners. Criteria derived from the CONSORT harms extension were used to evaluate safety reporting. Linear regression was applied to examine associations between quality of safety reporting and study level factors. Results: = 0.005) were associated with higher quality reporting. Items related to laboratory-defined toxicity and defining adverse events were among reporting items notably lacking (present in 53% and 40% of publications, respectively). Conclusion: While the reporting of phase III clinical trials for DMTs for the treatment of MS has improved with time, there remain gaps and opportunities for further improvement.

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)0.156
metaresearch head score (Gemma)0.202
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1560.202
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0240.011
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
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 head0.808
GPT teacher head0.639
Teacher spread0.169 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations0
Published2025
Admission routes1
Has abstractyes

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