Relation of Clinical Response and Minimal Residual Disease and Their Prognostic Impact on Outcome in Acute Myeloid Leukemia
Bibliographic record
Abstract
PURPOSE: Both presence of minimal residual disease (MRD) and achievement of complete remission (CR) with incomplete platelet recovery (CRp) rather than CR after induction therapy predict relapse in acute myeloid leukemia (AML). These results suggest a correlation between response (peripheral count recovery) and MRD at the time of morphologic remission. Here we examine this hypothesis and whether MRD and response provide independent prognostic information after accounting for other relevant covariates. PATIENTS AND METHODS: We retrospectively analyzed data from 245 adults with AML who achieved CR, CRp, or CR with incomplete blood count recovery (CRi) after induction therapy. Bone marrow samples were collected on or closest to the first date of blood count recovery, and MRD was determined by 10-color multiparameter flow cytometry. RESULTS: The 71.0% of patients who achieved CR had MRD less frequently and had lower levels of MRD than the 19.6% of patients achieving CRp and 9.4% achieving CRi. Although pretreatment covariates such as cytogenetics, monosomal karyotype, relapsed or refractory rather than newly diagnosed AML, and FLT3 internal tandem duplication were associated with relapse, their prognostic effect was much lower once MRD and response were taken into account, the univariable statistical effect of which was not materially affected by inclusion of pretreatment covariates. CONCLUSION: Our data indicate that post-therapy parameters including MRD status and response are important independent prognostic factors for outcome in patients with AML achieving remission. MRD status and type of response (CR v CRp or CRi) should play important, and perhaps dominant, roles in planning postinduction 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".