Hydroxychloroquine for Primary Progressive Multiple Sclerosis
Bibliographic record
Abstract
OBJECTIVE: Primary progressive multiple sclerosis (PPMS) does not respond well to immunomodulatory or immunosuppressive treatment. Chronic activation of microglia has been implicated in the pathophysiology of PPMS. The antimalarial drug hydroxychloroquine (HCQ) reduces the activity of human microglia and has neuroprotective effects in vitro. METHODS: We conducted a single-arm, phase II futility trial of 200 mg oral HCQ twice daily for 18 months. In an effort to investigate disability worsening in the absence of overt focal inflammation, we excluded participants with contrast enhancing lesions on a screening magnetic resonance imaging (MRI). The primary end point was ≥20% worsening on the timed 25-foot walk measured between 6 and 18 months of follow-up. RESULTS: Based on original trial data, 40% of the cohort were expected to worsen. We used a Simon 2-stage design to compare a null hypothesis of 40% of the cohort worsening against the one-sided alternative of 20%. Using a 5% type 1 error rate and 80% power, HCQ treatment would be deemed successful if fewer than 10 of 35 participants experienced clinically significant worsening. The study met its primary end point, as only 8 of 35 participants worsened between 6 and 18 months. HCQ was overall well-tolerated, with adverse events in 82% and serious adverse events in 12% of participants. All serious adverse events were unlikely related to HCQ use. INTERPRETATION: HCQ treatment was associated with reduced disability worsening in people with PPMS. HCQ is a promising treatment candidate in PPMS and should be investigated further in randomized controlled clinical trials. ANN NEUROL 2021;90:940-948.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".