Colchicine and Longitudinal Dynamics of Clonal Hematopoiesis
Bibliographic record
Abstract
BACKGROUND: Clonal hematopoiesis (CH) is an aging-related hematologic condition associated with increased risk for cardiovascular events. Larger CH clones associate more strongly with cardiovascular risk. Preclinical data indicate that inflammatory signaling drives expansion of CH clones and CH-associated cardiovascular disease. However, the effect of anti-inflammatory therapies on CH clonal dynamics in humans is unclear. OBJECTIVES: The goal of this study was to test the association of randomization to colchicine vs placebo with CH growth in participants with chronic coronary artery disease. It also assessed the association of colchicine use with change in inflammatory biomarkers over time according to CH status. METHODS: In this exploratory substudy of the LoDoCo2 (Low-Dose Colchicine 2) trial, high-coverage targeted sequencing was used to detect CH driver mutations and to quantify variant allele frequency at 4 timepoints: baseline, after a 30-day open-label colchicine run-in phase (0.5 mg daily), 1 year postrandomization to colchicine or placebo, and at end of study (median follow-up of 25.0 months). Clonal dynamics were assessed by using a generalized linear mixed model. High-sensitivity C-reactive protein and interleukin-6 were additionally measured at baseline, randomization, and 1 year postrandomization. RESULTS: = 0.01). CONCLUSIONS: In this exploratory analysis, treatment with low-dose colchicine was associated with attenuated clonal expansion in TET2 CH. These findings suggest the potential for colchicine to curb the proliferative advantage of key CH driver mutations and to mitigate their associated risk of cardiovascular disease. Further validation in prospective studies is warranted.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".