Subjective sleep problems and objective circadian disruption: Impact on outcomes in patients with metastatic colorectal cancer (MCC).
Bibliographic record
Abstract
e14584 Background: Both subjective sleep problems (S) and circadian disruption (C) have been shown to be independently associated with shorter overall survival (OS), shorter progression-free survival (PFS) and lower objective response (OR) rate in MCC patients (Lévi F., Chronobiol Int, 2014; Innominato P., Sleep Med, 2015). Although sleep and circadian functions are interconnected, the disruption of both (S + C) on patients’ outcomes has yet to be evaluated. Methods: Sleep problems were assessed using self-report sleep item from the EORTC QLQ-C30 questionnaire. Circadian function was evaluated with wrist actigraphy, using the robust I < O parameter. Previously validated cut off values were used. A multivariate Cox regression hazard model was built to predict OS or PFS, whereas a multivariate binary logistic regression was used for predicting OR. Results: Data were available for 237 MCC patients (median age: 60.2 years; Female: 37.6%; Performance Status = 0: 60%) before starting chemotherapy. Sleep problems and circadian disruption were positively correlated (p = 0.006). Patients with no disruption had significantly better outcomes as compared to the other groups. Specifically, patients with C alone or C+S displayed the worst outcomes, followed by those with S alone. Sleep and/or circadian disruption were associated with shorter OS and PFS and lower OR rate, independent of other prognostic factors. Conclusions: Large proportion of MCC patients experience both sleep and circadian disruption. Circadian disruption is sufficient, regardless of sleep, to worsen prognosis, whereas sleep problems are associated with poor outcomes only in patients without circadian disruption. These preliminary results suggest that personalized pharmacological and/or behavioral interventions specifically impacting sleep and/or circadian functions could improve patients’ outcomes. Median OS (months) HR Median PFS (months) HR OR rate OR None (N=47; 19.8%) 28.3 1 13.3 1 55.3 1 Sleep problems alone (N=60; 25.3%) 16.4 1.47 8.8 1.25 43.3 0.64 Circadian disruption alone (N=35; 14.8%) 11.8 2.42 8.6 1.70 28.6 0.34 Both (N=95; 40.1%) 12.0 2.65 5.7 1.96 29.5 0.32 Multivariate p 0.0001 0.001 0.012
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".