Abstract PS02-04: Associations of sleep health with quality of life among women with newly diagnosed breast cancer: baseline results from the AMBER cohort study
Notice bibliographique
Résumé
Abstract Background High incidence, ageing, and advancements in early detection and clinical treatment have led to a growing breast cancer survivor population, particularly in developed countries. Sleep problems are common and persist in this population, affecting over 50% of breast cancer survivors. Good sleep health is characterized by sleep duration, sleep timing and sleep quality, and these three dimensions do not necessarily correlate with each other. This analysis aimed to investigate the associations of sleep health, characterized by sleep duration, sleep timing, and a range of metrics for sleep quality (latency, efficient, disturbance, medication, daytime dysfunction) with physical and mental well-being in women with newly diagnosed breast cancer. Methods Newly diagnosed breast cancer patients, with early-stage disease were recruited between 2012-2019 in Edmonton and Calgary, Canada, and completed the Pittsburg Sleep Quality Index (PSQI) to assess the habitual sleep duration and timing, as well as sleep latency, efficiency, disturbance, medication and daytime dysfunction. To measure quality of life, participants completed the SF-36 version-2 to assess their physical and mental well-being. Multivariable linear regressions were used to estimate the association of sleep characteristics with physical and mental well-being, adjusting for socio-demographic, disease, clinical and lifestyle behaviour factors. Results Among 1409 breast cancer survivors, 41% reported short or long sleep duration ( < 6 or ≥9 h/d), 41% reported habitual bedtimes after 11pm, 56% reported sleep efficiency being < 85%, 80% reported fairly good (vs. very good) sleep disturbance, 35% reported taking sleep medication in the past month, and 71% reported fairly good, fairly bad or very bad (vs. very good) daytime function. In the multivariable model, short sleep (≤6/d) was associated with worse mental well-being (-3.6, 95%CI: -4.7,-2.4) but not physical well-being (-1.5, 95%CI: -2.3,-0.7). No clinically meaningful differences in quality of life were found for sleep timing. Metrics characterizing suboptimal sleep quality were associated with poorer physical and mental well-being, with stronger associations observed for mental health well-being. Notably, only 20% and 29% women were classified as “very good” in sleep disturbance and daytime dysfunction measures, respectively. Nevertheless, even “fairly good” sleep disturbance and daytime dysfunction were associated with statistically and clinically meaningful significant poorer physical (-3, 95%CI: -3.8,-2.2) and mental (-8, 95%CI: -9,-7) well-being. Conclusion Sleep timing does not appear to affect the quality of life in a clinically meaningful manner in women newly diagnosed with breast cancer. In contrast, short sleep duration and worse sleep quality were strongly associated with poorer mental well-being in these women. Targeted interventions to improve sleep may lead to improvements in the quality of life among women with newly diagnosed breast cancer. Table 1. Association of Sleep Characteristics with SF-36 Measured Quality of Life, Physical Well-Being. Table 2. Association of Sleep Characteristics with SF-36 Measured Quality of Life, Mental Well-Being. Citation Format: Lin Yang, Qinggang Wang, Jessica McNeil, Charles Matthews, Leanne Dickau, Jeff Vallance, Margaret McNeely, S. Nicole Culos-Reed, Karen Kopciuk, Kerry Courneya, Christine Friedenreich. Associations of sleep health with quality of life among women with newly diagnosed breast cancer: baseline results from the AMBER cohort study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS02-04.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».