Risk of Incident Cytopenia in Clonal Hematopoiesis
Bibliographic record
Abstract
Abstract Clonal hematopoiesis of indeterminate potential (CHIP) is an asymptomatic condition associated with elevated risk for myeloid neoplasms (MN). Patients with CHIP and cytopenia are at greater risk of MN. Quantifying the incidence of cytopenia and identifying risk factors among CHIP patients is critical for improving clinical management. We analyzed sequencing data from 805,249 participants in the NIH All of Us Research Program (AoU), Vanderbilt’s BioVU repository, and UK Biobank (UKB). Genetic mutations, laboratory values, and MN diagnoses were included in survival analyses to determine predictors of cytopenia in individuals with CHIP and matched controls. The cohort contained 9,374 CHIP cases and 24,749 controls. Cytopenia occurred in 13.5% of cases and 11.6% of controls (HR = 1.17, 95% confidence interval: 1.10 – 1.25, P=2.5 × 10 −6 ). Cytopenia risk factors included smoking, male sex, variant allele frequency ≥ 0.20, age ≥ 65, mean corpuscular volume ≥ 100 femtoliters, red cell distribution width ≥ 15%, mutations in high-risk CHIP genes, and ≥ 2 CHIP mutations. In BioVU, 45% of participants with ≥ 4 risk factors progressed to cytopenia within two years. Individuals with CHIP and cytopenia progressed to MN at a rate of ~2% per year, compared to <0.1% per year for those without cytopenia. Longitudinal analysis across three cohorts demonstrated an increased risk of cytopenia in CHIP patients and identified those at highest risk. These findings suggest that cytopenia is a critical step in progression from CHIP to MN, underscoring its utility as an endpoint in cancer prevention trials for CHIP patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".