Healthy Lifestyle and Clonal Hematopoiesis of Indeterminate Potential: Results From the Women's Health Initiative
Bibliographic record
Abstract
Background Presence of clonal hematopoiesis of indeterminate potential (CHIP) is associated with a higher risk of atherosclerotic cardiovascular disease, cancer, and mortality. The relationship between a healthy lifestyle and CHIP is unknown. Methods and Results This analysis included 8709 postmenopausal women (mean age, 66.5 years) enrolled in the WHI (Women's Health Initiative), free of cancer or cardiovascular disease, with deep‐coverage whole genome sequencing data available. Information on lifestyle factors (body mass index, smoking, physical activity, and diet quality) was obtained, and a healthy lifestyle score was created on the basis of healthy criteria met (0 point [least healthy] to 4 points [most healthy]). CHIP was derived on the basis of a prespecified list of leukemogenic driver mutations. The prevalence of CHIP was 8.6%. A higher healthy lifestyle score was not associated with CHIP (multivariable‐adjusted odds ratio [OR] [95% CI], 0.99 [0.80–1.23] and 1.13 [0.93–1.37]) for the upper (3 or 4 points) and middle category (2 points), respectively, versus referent (0 or 1 point). Across score components, a normal and overweight body mass index compared with obese was significantly associated with a lower odds for CHIP (OR, 0.71 [95% CI, 0.57–0.88] and 0.83 [95% CI, 0.68–1.01], respectively; P ‐trend 0.0015). Having never smoked compared with being a current smoker tended to be associated with lower odds for CHIP. Conclusions A healthy lifestyle, based on a composite score, was not related to CHIP among postmenopausal women. However, across individual lifestyle factors, having a normal body mass index was strongly associated with a lower prevalence of CHIP. These findings support the idea that certain healthy lifestyle factors are associated with a lower frequency of CHIP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".