Mogamulizumab for Treatment of Human T-lymphotropic Virus Type 1-Associated Myelopathy/Tropical Spastic Paraparesis: A Single-Center US-based Series
Bibliographic record
Abstract
BACKGROUND: Human T-lymphotropic virus type 1 (HTLV-1)-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a chronic neurological condition characterized by progressive myelopathic symptoms including spasticity, pain, weakness, and urinary symptoms, without proven treatments. Mogamulizumab (MOG) is a monoclonal antibody that binds CCR4 and leads to the clearance of HTLV-1-infected CCR4+ cells. A phase 1-2a study in Japan evaluated MOG for the treatment of HAM/TSP and reported decreases in HTLV-1 proviral load and neuroinflammatory markers, with clinical improvement in some participants. METHODS: We administered MOG 0.1 mg/kg every 8 weeks to individuals with HAM/TSP as a compassionate and palliative treatment. Patients who received MOG had (1) a positive peripheral HTLV-1 antibody, (2) progressive myelopathic symptoms, and (3) a diagnosis of HAM/TSP. RESULTS: Four female patients, ages 45-68, received MOG (range, 2-6 infusions) between 1 November 2019 and 30 November 2022. Two patients with <3 years of symptoms had milder disease, with Osame scores <4. The other 2, with >7 years of symptoms, had Osame scores >5. One patient, with 6 total treatments, received dose-reduced MOG after she developed a rash at the initial dose. The 2 patients with milder baseline disease reported symptomatic improvement and saw reductions in Osame and/or modified Ashworth scale scores during follow-up. The other 2 patients showed no improvement. All 4 developed rashes after receiving MOG-a treatment-limiting event in some cases. CONCLUSIONS: Clinical trials are needed including diverse patient populations to assess the potential role of MOG for HAM/TSP. Our findings may help inform the development of these trials.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".