Bedtime misalignment and progression of breast cancer
Bibliographic record
Abstract
Disruption of circadian rhythms, which frequently occurs during night shift work, may be associated with cancer progression. The effect of chronotype (preference for behaviors such as sleep, work, or exercise to occur at particular times of day, with an associated difference in circadian physiology) and alignment of bedtime (preferred vs. habitual), however, have not yet been studied in the context of cancer progression in women with breast cancer. Chronotype and alignment of actual bedtime with preferred chronotype were examined using the Morningness-Eveningness Scale (MEQ) and sleep-wake log among 85 women with metastatic breast cancer. Their association with disease-free interval (DFI) was retrospectively examined using the Cox proportional hazards model. Median DFI was 81.9 months for women with aligned bedtimes ("going to bed at preferred bedtime") (n = 72), and 46.9 months for women with misaligned bedtimes ("going to bed later or earlier than the preferred bedtime") (n = 13) (log rank p = 0.001). In a multivariate Cox proportional hazard model, after controlling for other significant predictors of DFI, including chronotype (morning type/longer DFI; HR = 0.539, 95% CI = 0.320-0.906, p = 0.021), estrogen receptor (ER) status at initial diagnosis (negative/shorter DFI; HR = 2.169, 95% CI = 1.124-4.187, p = 0.028) and level of natural-killer cell count (lower levels/shorter DFI; HR = 1.641, 95% CI = 1.000-2.695, p = 0.050), misaligned bedtimes was associated with shorter DFI, compared to aligned bedtimes (HR = 3.180, 95% CI = 1.327-7.616, p = 0.018). Our data indicate that a misalignment of bedtime on a daily basis, an indication of circadian disruption, is associated with more rapid breast cancer progression as measured by DFI. Considering the limitations of small sample size and study design, a prospective study with a larger sample is necessary to explore their causal relationship and underlying mechanisms.
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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 | 0.000 |
| 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".