Clonal hematopoiesis and myeloid malignancies: clonal dynamics and clinical implications
Bibliographic record
Abstract
PURPOSE OF REVIEW: Clinical and experimental studies have uncovered relevant clinical implications of clonal hematopoiesis. However, the true magnitude of this process, clonal dynamics over time and mechanisms of progression into overt malignancy remain to be largely elucidated. In this article, the consequences of clonal hematopoiesis, its significance in the context of cytopenia, and its implications in the clinical management of patients with myeloid malignancies are reviewed and discussed. RECENT FINDINGS: Clonal hematopoiesis has been associated with higher risk of hematologic cancers, as well as of death from cardiovascular causes. Clonal hematopoiesis has been proven clinically relevant in the context of disorders characterized by peripheral blood cytopenia, including aplastic anemia, cytopenia of undetermined significance, as well as unexplained anemia of the elderly. SUMMARY: The available evidence has been proving the utility of somatic mutational analysis in patients with unexplained cytopenia, as well as in those receiving a diagnosis of myeloid neoplasm, enabling more accurate diagnosis, risk assessment, effective therapeutic strategies and residual disease monitoring. The access to a minimally invasive assessment is paving the way for screening programs of clonal hematopoiesis in individuals with absent or mild hematologic phenotype, as well as for therapeutic targeting of preleukemia cells.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".