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Record W7116985745 · doi:10.1136/bmjno-2025-001313

Study protocol for a multicentre, randomised, double-blinded, placebo-controlled, multi-arm, multi-stage, trial of SpironolacTone and famciclOovir in the treatment of Progressive Multiple Sclerosis to prevent disability progression: the STOP-MS trial

2025· article· en· W7116985745 on OpenAlexaff
Kayla Ward, Vivien Li, Sudarshini Ramanathan, Katherine Buzzard, Kaylene M. Young, Fiona Mckay, Vanessa Vigar, Sabrina Oishi, Lidia Madrid San Martin, Belinda J. Kaskow, Grant P. Parnell, Corey Smith, Vilija Jokubaitis, Tomas Kalincik, David C. Tscharke, Andrew Potter, Erin Brady, Jeannette Lechner-Scott, Lawrence Steinman, Mahesh Parmar, Chataway Jeremy, Todd Hardy, William M. Carroll, M. Barnett, Bruce Taylor, Simon Broadley

Bibliographic record

VenueBMJ Neurology Open · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsInstitute of Infection and Immunity
FundersNational Health and Medical Research CouncilTeva Pharmaceutical IndustriesMitsubishi Tanabe Pharma CorporationGlaxoSmithKlineBiogenSanofi
KeywordsClinical trialMultiple sclerosisSpironolactoneProtocol (science)Administration (probate law)

Abstract

fetched live from OpenAlex

Introduction: Targeting progressive multiple sclerosis (MS) addresses the current single biggest unmet need in the MS therapeutic landscape and anti-Epstein-Barr virus (EBV) therapy potentially strikes at the root cause. The SpironolacTone and famciclOvir in the treatment of Progressive MS to prevent disability progression (STOP-MS) trial has been developed to assess anti-EBV therapies in the treatment of progressive MS. Methods and analysis: STOP-MS is a multi-arm, multi-stage, randomised, double-blind, placebo-controlled trial testing spironolactone and famciclovir to prevent disability progression in MS. Australians with progressive forms of MS, aged 25 to 70 years with established disability, are eligible. Recruitment commenced in March 2025 and the first participant was enrolled on 15 April 2025. The sample size for STOP-MS is 150 in stage 1 and 300 in stage 2. In stage 1, the composite primary outcome measures will be reduction of EBV DNA in saliva and serum EBV nuclear antigen-1 antibody titres. Minimum criteria for consideration of progression to stage 2 will be a 10% reduction in the composite outcome measure. In stage 2, the primary outcome measure will be 6-month confirmed disability progression analysed using Cox-proportional hazards. Trial registration number: The STOP-MS trial has been acknowledged by the Therapeutics Goods Administration under the Clinical Trial Notification scheme (CT-2023-CTN-03 505-1) and is registered with the Australian and New Zealand Clinical Trial Registry (ACTRN12623000849695).

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.282
GPT teacher head0.506
Teacher spread0.224 · 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 designRandomized trial
Domainnot available
GenreProtocol

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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