Patient-reported sleep disturbance in advanced cancer: frequency, predictors and screening performance of the Edmonton Symptom Assessment System sleep item
Bibliographic record
Abstract
AIMS: Sleep Disturbance (SD) is a severe debilitating symptom in advanced cancer patients (ACP). However, routine screening of SD is uncommon. The primary aim of this study was to determine the optimal cutoff score for SD screening for Edmonton Symptom Assessment system (ESAS) sleep item using Pittsburgh Sleep Quality Index (PSQI) as a gold standard. We also determined the frequency of SD, obstructive sleep apnea symptoms (OSA) and restless leg syndrome (RLS) and factors associated with SD. METHODS: We prospectively surveyed 180 consecutive ACP. Patients completed validated assessment for symptoms. We determined epidemiological performance, receiver operating characteristics, and correlations of SD. RESULTS: SD according to PSQI was diagnosed in 112/180 (62%), and median (IQR) ESAS sleep was 5 (2-7). ESAS sleep ≥ 4 had a sensitivity of 74% and 80%, and specificity of 71% and 64% in the training and validation samples, respectively for screening of SD. The frequency of OSA was 61%; RLS was 38%. ESAS sleep was associated [r, p-value] with PSQI (0.61, <0.0001), pain (0.4, <0.0001); fatigue (0.35, <0.0001); depression (0.20, 0.006); anxiety (0.385, <0.0001); drowsiness (0.385, <0.0001), shortness of breath (0.24, <0.0014); anorexia (0.32, <0.0001), well-being (0.36, <0.0001). Multivariate analysis found well-being (OR per point 1.34, p=0.0003), pain (OR 1.21, p<0.0037), dyspnea (OR 1.16, p=0.027), and OSA (OR 0.31, P=0.003) as independent predictors of SD. There was no association between SD and survival. CONCLUSIONS: SD is frequent and ESAS SD item ≥ 4 has good sensitivity for SD screening.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".