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
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.030 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.266 | 0.059 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".