Lifestyle Behaviors in Elderly Cancer Survivors: A Comparison With Middle-Age Cancer Survivors
Bibliographic record
Abstract
PURPOSE: Improved cancer screening and treatment have led to a greater focus on cancer survivorship care. Older cancer survivors may be a unique population. We evaluated whether older cancer survivors (age ≥ 65 years) had lifestyle behaviors, attitudes, and knowledge distinct from younger survivors. PATIENTS AND METHODS: Adult cancer survivors with diverse cancer subtypes were recruited from Princess Margaret Cancer Centre (Toronto, Ontario, Canada). Multivariable models evaluated the effect of age on smoking, alcohol, and physical activity habits, attitudes toward and knowledge of these habits on cancer outcomes, and lifestyle information and recommendations received from health care providers, adjusted for sociodemographic and clinicopathologic covariates. RESULTS: Among the 616 survivors recruited, 23% (n = 139) were older. Median follow-up since diagnosis was 24 months. Older survivors were more likely ex-smokers and less likely current smokers than younger survivors, but they were less likely to know that smoking could affect cancer treatment (adjusted odds ratio [OR], 0.53; P = .007) or prognosis (adjusted OR, 0.53; P = .008). Older survivors were more likely to perceive alcohol as improving overall survival (adjusted OR, 2.39; P = .02). Rates of meeting moderate-to-vigorous physical activity guidelines 1 year before diagnosis (adjusted OR, 0.55; P = .02) and maintaining and improving their exercise levels to meet these guidelines after diagnosis (adjusted OR, 0.48; P = .02) were lower in older survivors. Older and younger cancer survivors reported similar rates of receiving lifestyle behavior information from health care providers (P = .36 to .98). CONCLUSION: Older cancer survivors reported being less aware of the impact of smoking on their overall health, more likely perceived alcohol as beneficial to survival, and were less likely to meet exercise goals compared with younger survivors. Survivorship programs need to consider age when counseling on lifestyle behaviors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".