Dose-response association between cardiovascular health and mortality in cancer survivors
Bibliographic record
Abstract
BACKGROUND: There is little knowledge on the dose-response association between cardiovascular health (CVH) and risk of all-cause, cardiovascular disease (CVD) and cancer deaths among cancer survivors. AIMS: We aimed to examine the dose-response association of CVH with all-cause, CVD, and cancer mortality. METHODS: A total of 1701 US adult cancer survivors were followed-up during a median of 7.3 (IQR 4.0-10.2) years from 2007 to 2018 through the National Health and Nutrition Examination Survey (NHANES). We used the American Heart Association´s (AHA) Life´s Essential 8 (LE8) as a proxy for CVH. RESULTS: Restricted cubic spline models indicated a close to inverse linear shape for the dose-response association between LE8 score and all-cause mortality with significant risk reductions within the range between 61.25 (Hazard ratio [HR]: 0.76, 95% CI, 0.59-0.98) and 100 points (HR: 0.28, 95%CI, 0.12-0.62), and a curvilinear shape for the dose-response association between LE8 score and CVD deaths with significant risk reductions within the range between 50.25 (HR: 0.72, 95% CI, 0.52-0.99) and 90.25 points (HR: 0.15, 95%CI, 0.02-0.98). No significant dose-response association was observed between LE8 and cancer deaths. CONCLUSIONS: Our study showed a close to inverse relationship between higher LE8 and risk of death from all cause, an inverse curvilinear relationship between higher LE8 and the risk for CVD death, and a non-significant association between higher LE8 and the risk of cancer death among US adult cancer survivors, which may translate to a substantial number of annual averted deaths and thus important public health implications.
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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 | 0.005 | 0.015 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".