Response Kinetics and Clinical Benefits of Nonintensive AML Therapies in the Absence of Morphologic Response
Bibliographic record
Abstract
The ultimate goal of treatment for acute myeloid leukemia (AML) is to improve survival, and the best means of doing so is through the induction of morphologic remission, which is historically most reliably achieved with intensive chemotherapy regimens. Older patients with AML are less likely to be candidates for or to benefit from intensive chemotherapy. Patients deemed ineligible for intensive therapy may nevertheless benefit from lower-intensity therapies and from newly available targeted AML treatments. Recently approved lower-intensity treatments for AML include enasidenib, ivosidenib, glasdegib, venetoclax, midostaurin, and gilteritinib, and additional promising agents are in later stages of clinical development. Noncytotoxic agents may result in slower kinetics of therapeutic activity compared to intensive regimens, and although they are generally better tolerated than intensive chemotherapy, bone marrow responses are less frequent and may take longer to achieve. Notably, newer therapies might have been considered ineffective had they been judged solely by 2003 International Working Group response criteria for AML, which were based on experience with intensive regimens in predominantly younger patients. Lower-intensity therapies may require several treatment cycles to induce responses, and failure to achieve rapid morphologic remission may not signal the need for treatment cessation or transition to alternative therapies. Additionally, even in the absence of a conventional complete remission, lower-intensity therapies may provide meaningful clinical benefit, including improved survival and quality of life, by inducing hematologic improvement and transfusion independence. Reviewed here are the mechanisms of activity and response kinetics of lower-intensity AML therapies, as well as the clinical benefits resulting from nontraditional AML responses.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".