Who truly benefits from gilteritinib combinations in FLT3-mutated relapsed-refractory(R/R) AML: a Canadian single center analysis
Bibliographic record
Abstract
Treatment of relapsed-refractory (R/R) FLT3 mut AML is an unmet need. Use of gilteritinib monotherapy in the ADMIRAL trial resulted in a modest prolongation of overall survival (OS) from 5.6 months to 9.3 months [ 1 ]. Following the results from in-vitro studies showing synergism between gilteritinib and venetoclax [ 2 , 3 ], this combination was studied in a phase Ib/II study, resulting in a median OS of 10.0 months [ 4 ]. The combination of gilteritinib with azacytidine-venetoclax in another phase I/II study resulted in a median OS of 5.8 months in the R/R cohort [ 5 ]. Thus, even though combination therapy shows improved response rates, cross trial comparisons show the survival with combination therapy to be similar to that of monotherapy at the cost of increased toxicities [ 1 , 4 , 5 ]. Thus, clinical equipoise persists regarding the optimal regimen for R/R FLT3 mutated AML. To address this knowledge gap, we conducted a single center retrospective study to evaluate our experience with use of gilteritinib-based therapy in the R/R FLT3 mut AML population. Specifically, we compared the outcomes of patients who received gilteritinib monotherapy with gilteritinib combination therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".