Modifiable risk factors for late mortality among five-year survivors of childhood cancer: A report from the Childhood Cancer Survivor Study.
Bibliographic record
Abstract
10014 Background: The impact ofmodifiable lifestyle and cardiovascular risk factors (CVRFs) on risk for late mortality in adult survivors of childhood cancer is not well established. Methods: All-cause and health-related late (>5 years from cancer diagnosis) mortality (HRM; excludes death from primary cancer and external causes) were evaluated in five-year survivors diagnosed <21 years of age using the National Death Index through 2017. Modifiable lifestyle (smoking status, alcohol use, physical activity, body mass index [BMI]; combined to create a score [0-4] and categorized as unhealthy [0-2], moderate [2.5 or 3], healthy [3.5 or 4]) and CVRFs (hypertension [HTN], diabetes [DM], dyslipidemia) were assessed as time-varying covariates. Standardized mortality ratios (SMRs) and absolute excess risk of death per 1000 person-years (AER) with 95% confidence intervals (CIs) were estimated. Multivariable models estimated the relative risk (RR) of death adjusted for demographic and socioeconomic variables. Results: Among 20,051 adult survivors (median age 40.0 years, range 18.7 – 67.7), 19% reported ≥1 CVRF (13% HTN, 9% dyslipidemia, 5% DM) and few reported a healthy lifestyle (29% healthy, 40% moderate, 31% unhealthy). There were 1476 deaths due to health-related causes. While all survivors experienced an increased risk of HRM compared to the US population, risk was lower among those with a healthy vs. unhealthy lifestyle (SMR 3.5, 95% CI 3.1-3.9 vs. 6.2, 5.7-6.7) and very high among underweight survivors (11.1, 9.3-13.3) and those with both HTN and DM (13.0, 9.2-18.0). Stratified by lifestyle score, the excess risk of HRM was lowest in those with a healthy lifestyle across survival time (Table). Similar trends were seen when stratified by 0, 1 and 2 CVRFs. In multivariable models, compared to survivors with no CVRFs and healthy lifestyle, no CVRFs and unhealthy lifestyle was associated with a 50% increased risk of HRM (RR 1.5, 95% CI 1.2-1.8) and unhealthy lifestyle plus HTN a 2-fold increased risk of HRM (2.2, 1.6-2.8). Regardless of lifestyle group, ≥2 CVRF increased risk for HRM at least 2-fold (p-values <0.001). Conclusions: A reduction in excess deaths is observed among adult survivors of childhood cancer with a healthy lifestyle and no CVRFs as they age. Interventions that target improved lifestyle choices and prevention or aggressive treatment of modifiable CVRFs may reduce risk for late mortality. [Table: see text]
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".