Therapeutic modalities of deferiprone in Parkinson's disease: SKY and EMBARK studies
Bibliographic record
Abstract
BackgroundReducing nigrostriatal iron overload reduces neuronal loss in Parkinson's disease (PD) models.ObjectiveExamine the safety and efficacy of deferiprone in reducing motor disability progression in dopaminergic-treated and treatment-naïve patients with early-stage PD.MethodsTwo phase II, multicenter studies, SKY and EMBARK, enrolled patients diagnosed with early PD (<3 years from screening). In SKY, patients on stable dopaminergic therapy were randomized 1:1 to one of four dosage (or placebo-matching) cohorts (300, 600, 900, 1200 mg twice daily [BID]) for 9 months. EMBARK enrolled patients on stable dopaminergic therapy or treatment-naïve patients and received 15 mg/kg BID. For both studies, the primary outcome was the change from baseline to month 9 in motor examination score (Movement Disorder Society-Unified Parkinson's Disease Rating Scale [MDS-UPDRS] Part III). ClinicalTrials.gov: NCT02728843; ANZCTR: ACTRN12617001578392.ResultsOverall, 140 patients were randomized in SKY (28 per cohort). Thirty-six patients enrolled in EMBARK (27 dopaminergic-treated; 9 treatment-naïve). In the SKY study, all doses showed the same worsening as the placebo group, with the exception of the 600 mg dose, which was associated with non-significant reductions in MDS-UPDRS Part III least-squares mean (LSM) between baseline and 9 months (-2-8 points versus placebo). In EMBARK, LSM (SE) changes from baseline in MDS-UPDRS Part III were nonsignificant (-1.6 [1.7]) and significant (8.3 [3.9]) for dopaminergic-treated and treatment-naïve patients, respectively, the latter indicating disease worsening. Adverse events possibly related to deferiprone were reported in 35.7%-88.9% across all deferiprone groups vs. 42.9% for placebo.ConclusionsSKY and EMBARK studies indicate that deferiprone combined with L-dopa does not provide significant motor function benefit, while the absence of L-dopa treatment worsens symptoms.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".