Randomized phase 2 study of GMI-1070 in SCD: reduction in time to resolution of vaso-occlusive events and decreased opioid use
Bibliographic record
Abstract
Treatment of vaso-occlusive crises (VOC) or events in sickle cell disease (SCD) remains limited to symptom relief with opioids. Animal models support the effectiveness of the pan-selectin inhibitor GMI-1070 in reducing selectin-mediated cell adhesion and abrogating VOC. We studied GMI-1070 in a prospective multicenter, randomized, placebo-controlled, double-blind, phase 2 study of 76 SCD patients with VOC. Study drug (GMI-1070 or placebo) was given every 12 hours for up to 15 doses. Other treatment was per institutional standard of care. All subjects reached the composite primary end point of resolution of VOC. Although time to reach the composite primary end point was not statistically different between the groups, clinically meaningful reductions in mean and median times to VOC resolution of 41 and 63 hours (28% and 48%, P = .19 for both) were observed in the active treatment group vs the placebo group. As a secondary end point, GMI-1070 appeared safe in acute vaso-occlusion, and adverse events were not different in the two arms. Also in secondary analyses, mean cumulative IV opioid analgesic use was reduced by 83% with GMI-1070 vs placebo (P = .010). These results support a phase 3 study of GMI-1070 (now rivipansel) for SCD VOC. This trial was registered at www.clinicaltrials.gov as #NCT01119833.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".