The potential of triplet combination therapies for patients with FLT3-ITD -mutated acute myeloid leukemia
Bibliographic record
Abstract
INTRODUCTION: Acute myeloid leukemia (AML) encompasses a heterogeneous group of aggressive myeloid malignancies, where FMS-like tyrosine kinase 3 (FLT3) mutations are prevalent, accounting for approximately 25-30% of adult patients. The presence of this mutation is related to a dismal prognosis and high relapse rates. In the lasts years many FLT3 inhibitors have been developed. AREAS COVERED: AML, summarizing the state of art of current treatment and available data about combination strategies including an FLT3 inhibitor. EXPERT OPINION: In addition, the review discusses the emergence of drug resistance and the need for a nuanced approaches in treating patients who are ineligible for or resistant to intensive chemotherapy. Specifically, it explores the historical context of FLT3 inhibitors (FLT3Is) and their impact on treatment outcomes, emphasizing the pivotal role of midostaurin, as well as gilteritinib and quizartinib, and providing detailed insights into ongoing trials exploring the safety and efficacy of novel triplet combinations involving FLT3Is in different AML settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".