Effectiveness of olutasidenib versus ivosidenib in patients with mutated isocitrate dehydrogenase 1 acute myeloid leukemia who are relapsed or refractory to venetoclax: the 2102-HEM-101 trial versus a US electronic health record-based external control arm
Bibliographic record
Abstract
First-line venetoclax (VEN) treatment for acute myeloid leukemia (AML) has high relapse rates, with limited evidence guiding subsequent therapy sequencing. This study evaluated the effectiveness of olutasidenib (OLU) versus ivosidenib (IVO) for patients withIDH1 relapsed/refractory (R/R) AML previously treated with VEN based therapy. Outcomes were compared between a subcohort of OLU-treated patients from the 2102-HEM-101 trial and an external control arm of IVO-treated patients from the Loopback Analytics electronic health record database. Entropy balancing was applied to align key prognostic variables. Risk differences (RD) for response/TI were estimated via logistic regression, and hazard ratios (HR) for OS via Cox regression. Following weighting, treatment with OLU versus IVO was associated with significantly higher rates of complete response (RD: 0.25; 95%CI: 0.01, 0.49), transfusion independence (RD: 0.27; 95%CI: 0.01, 0.53), and OS (HR: 0.33; 95%CI: 0.11, 0.94). Results suggest favorable effectiveness of OLU versus IVO in this population.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".