MétaCan
Menu
Back to cohort
Record W2972393403 · doi:10.1177/1352458519876701

Clinical outcome measures in SPMS trials: An analysis of the IMPACT and ASCEND original trial data sets

2019· article· en· W2972393403 on OpenAlexaff
Marcus Koch, Jop Mostert, Bernard M.J. Uitdehaag, Gary Cutter

Bibliographic record

VenueMultiple Sclerosis Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsExpanded Disability Status ScaleMultiple sclerosisClinical trialInternal medicineLogistic regressionPlaceboOncologyMedicinePsychologyPhysical therapyImmunologyAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Still too little is known about the natural history of clinical outcome measures beyond the Expanded Disability Status Scale (EDSS), such as the timed 25-foot walk (T25FW) and nine-hole peg test (9HPT) in secondary progressive multiple sclerosis (SPMS). OBJECTIVE: To describe progression on the EDSS, T25FW, 9HPT, and their combinations. To investigate the association of the baseline characteristics age, sex, EDSS, T25FW, gadolinium-enhancing lesions, and relapse activity with EDSS and T25FW progression. METHODS: Using original trial data from the placebo arms of the IMPACT and ASCEND randomized controlled trials, we describe disability progression (with and without 3- or 6-month confirmation). We investigated the association of selected baseline characteristics with EDSS and T25FW progression over 2 years using binary logistic regression. RESULTS: T25FW was the single outcome measure with the largest proportion of patients progressing, followed by EDSS and 9HPT. EDSS and T25FW at baseline were associated with EDSS and T25FW progression in both data sets. Age and relapse activity were only mild and inconsistent predictors, while sex and gadolinium enhancement at baseline did not predict disability progression in either data set. CONCLUSION: Our analyses inform the selection of primary outcome measures as well as inclusion criteria for clinical trials in SPMS.

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)0.025
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.583
GPT teacher head0.524
Teacher spread0.060 · 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.

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".

Quick stats

Citations26
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueMultiple Sclerosis JournalSame topicMultiple Sclerosis Research StudiesFrench-language works237,207