Lifestyle Challenges in Endometrial Cancer Survivorship
Bibliographic record
Abstract
OBJECTIVE: To examine lifestyle behaviors that may contribute to endometrial cancer survivor morbidity and to identify associations with quality of life. METHODS: Patients with early-stage (I or II) endometrial cancer with a body mass index of at least 25 kg/m2 completed questionnaires on smoking, physical activity, fruit and vegetable intake, and the Functional Assessment of Cancer Therapy (FACT) and Short-Form medical outcomes (SF-36) quality-of-life surveys. Behaviors were compared with American Cancer Society 2006 guidelines for cancer survivors (150 min/wk of moderate-to-vigorous physical activity; five servings fruit and vegetables per day; no smoking). Effect size (d) was calculated for the difference in means between meeting and not meeting guidelines (d=0.5 moderate effect). RESULTS: A total of 120 participants were enrolled. Of those, 43% had hypertension, 35% osteoarthritis, 33% metabolic syndrome, 21% type 2 diabetes mellitus, and 93% abdominal obesity. Only 12% of participants were meeting physical activity guidelines. Fifteen percent reported five or more servings of fruit and vegetables per day; mean intake was 2.6 servings per day. Seventy-four percent of participants were nonsmokers. Only 1% of participants met all three American Cancer Society guidelines; 22% met none of the recommendations. The emotional well-being (mean 17.4 [±4.1] compared with 20.1 [±4.1]; d=0.66) and fatigue scores (mean 34.6 [±9.5] compared with 40.5 [±9.6]; d=0.62) indicate that those who do not meet the guidelines had lower emotional well-being and increased fatigue. CONCLUSION: Endometrial cancer survivors have unhealthy lifestyles that put them at risk for morbidity. This survivor group should be offered multi-behavioral lifestyle interventions after diagnosis. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, www.clinicaltrials.gov, NCT 00420979 and NCT00732173. LEVEL OF EVIDENCE: II.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".