Associations of Health-Related Quality of Life and Sleep Disturbance With Cardiovascular Disease Risk in Postmenopausal Breast Cancer Survivors
Bibliographic record
Abstract
BACKGROUND: Breast cancer (BC) survivors are at an increased risk of long-term cardiovascular disease (CVD), often attributed to cancer treatment. However, cancer treatment may also negatively impact health-related quality of life (HRQoL), a risk factor of CVD in the general population. OBJECTIVE: We examined whether sleep disturbance, and physical or mental HRQoL were associated with CVD risk in BC survivors. METHODS: We conducted a longitudinal analysis in the Women's Health Initiative of postmenopausal women given a diagnosis of invasive BC during follow-up through 2010 with no history of CVD before BC. The primary outcome was incident CVD, defined as physician-adjudicated coronary heart disease or stroke, after BC. Physical and mental HRQoL, measured by the Short-Form 36 Physical and Mental Component Summary scores, and sleep disturbance, measured by the Women's Health Initiative Insomnia Rating Scale, were recorded post BC. Time-dependent Cox proportional hazards models were used starting at BC diagnosis until 2010 or censoring and adjusted for relevant confounders. RESULTS: In 2884 BC survivors, 157 developed CVD during a median follow-up of 9.5 years. After adjustment, higher Physical Component Summary scores were significantly associated with a lower risk of CVD (hazard ratio, 0.90 [95% confidence interval, 0.81-0.99]; per 5-point increment in Physical Component Summary). No associations with CVD were found for Mental Component Summary or Insomnia Rating Scale. CONCLUSION: In BC survivors, poor physical HRQoL is a significant predictor of CVD. IMPLICATIONS FOR PRACTICE: Our findings highlight the importance for nurses to assess and promote physical HRQoL as part of a holistic approach to mitigating the risk of CVD in BC survivors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".