Emerging patterns in clonal haematopoiesis
Bibliographic record
Abstract
Clonal haematopoiesis (CH) is defined by the presence of acquired mutations and/or cytogenetic abnormalities in haematopoietic cells. By definition, these premalignant clones do not meet criteria for haematopoietic neoplasms listed in the Revised Fourth Edition of the WHO classification. CH is fairly common in elderly individuals and is associated with higher risks for haematological cancers, in particular myelodysplastic syndrome and acute myeloid leukaemia (AML), as well as cardiovascular events. Similar small clones have also been detected during follow-up in patients with AML in morphological remission, in individuals with aplastic anaemia, and in pre-chemotherapy blood samples from patients with other types of cancers. In each of these contexts, the presence of mutations carries different clinical implications, and sometimes demonstrates unique genetic profiles. Emerging research suggests that the number and identity of mutations, the size of the mutant clones and various other factors, including age, immune status and history of exogenous drugs/toxins, are important for disease biology and progression. This review focuses specifically on the subset of CH with gene mutations detected by sequencing, and includes discussions of nomenclature and molecular technologies that detect and quantify gene mutations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| 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) | 0.002 | 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".