ArticleAnnals of medicine2024
Association between sleep duration, depression and breast cancer in the United States: a national health and nutrition examination survey analysis 2009-2018.
Article in Annals of medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Sleep Traits to the Risk of Breast Cancer Disease Incidence, Adverse Progression and Mortality: Evidence From a Global Systematic Review and Meta-Analysis.International journal of public health · 2025Pooled it
- Multi-omics graph attention network reveals neuro-immune-tumor pathways in breast cancer liver depression syndrome.Frontiers in immunology · 2026Trial
- Multimorbidity Clusters and Depressive Symptom Networks in Old Age: Evidence From China.Psychiatry investigation · 2026Article
- The role of artificial intelligence in precision medicine for breast cancer.Discover oncology · 2026Review
- Revolutionizing Sleep Medicine: The Impact of Machine Learning on Diagnosis, Treatment, and Personalized Care.Health science reports · 2026Article
- Prevalence and its associated factors of cancer-related fatigue among liver cancer patients: a cross-sectional study.Scientific reports · 2026Article
- A U-shaped association between sleep duration and depression in adult prescription opioid users.Frontiers in psychiatry · 2026Article
- Construction of risk predictive models for postoperative hyponatremia in colorectal cancer patients.American journal of cancer research · 2026Article
- Article
- Mental distress and inflammation in bladder cancer: The nerve makes things less vague.Brain, behavior, & immunity - health · 2025Article
- A narrative review of sleep and breast cancer: from epidemiology to mechanisms.Cancer causes & control : CCC · 2025Review
- Post-marketing safety of elacestrant in breast cancer: a pharmacovigilance investigation using the FDA adverse event reporting system.BMC pharmacology & toxicology · 2025Article
- Associations between phenol and paraben exposure and the risk of developing breast cancer in adult women: a cross-sectional study.Scientific reports · 2025Article
- Article
- Machine Learning-Based Radiomics for Differentiating Pancreatic Lesions: A Potential Tool to Enhance Clinical Decision-Making and Nursing Management.Journal of nursing management · 2025Article
- The Common Hallmarks and Interconnected Pathways of Aging, Circadian Rhythms, and Cancer: Implications for Therapeutic Strategies.Research (Washington, D.C.) · 2025Review
- Exploring the Link Between Sleep Duration and Visual Impairment and Major Eye Diseases: National Health and Nutrition Examination Survey 2005-2008.BioMed research international · 2025Article
- Association Between Sleep Duration and Anxiety in US Adults: A Nationally Representative Cross-Sectional Study.Psychology research and behavior management · 2025Article
- Predictive and Prognostic Values of Glycoprotein 96, Androgen Receptors, and Extranodal Extension in Sentinel Lymph Node-Positive Breast Cancer: An Immunohistochemical Retrospective Study.Journal of clinical medicine · 2024Article
- Exploring the association between sleep duration and cancer risk in middle-aged and older Chinese adults: observations from a representative cohort study (2011-2020).BMC public health · 2024Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveBreast cancer is the most common cancer in women, threatening both physical and mental health. The epidemiological evidence for association between sleep duration, depression and breast cancer is inconsistent. The aim of this study was to determine the association between them and build machine-learning algorithms to predict breast cancer.
methodsA total of 1,789 participants from the National Health and Nutrition Examination Survey (NHANES) were included in the study, and 263 breast cancer patients were identified. Sleep duration was collected using a standardized questionnaire, and the Nine-item Patient Health Questionnaire (PHQ-9) was used to assess depression. Logistic regression yielded multivariable-adjusted breast cancer odds ratios (OR) and 95% confidence intervals (CI) for sleep duration and depression. Then, six machine learning algorithms, including AdaBoost, random forest, Boost tree, artificial neural network, limit gradient enhancement and support vector machine, were used to predict the development of breast cancer and find out the best algorithm.
resultsBody mass index (BMI), race and smoking were statistically different between breast cancer and non-breast cancer groups. Participants with depression were associated with breast cancer (OR = 1.99, 95%CI: 1.55-3.51). Compared with 7-9h of sleep, the ORs for <7 and >9 h of sleep were 1.25 (95% CI: 0.85-1.37) and 1.05 (95% CI: 0.95-1.15), respectively. The AdaBoost model outperformed other machine learning algorithms and predicted well for breast cancer, with an area under curve (AUC) of 0.84 (95%CI: 0.81-0.87).
conclusionsNo significant association was observed between sleep duration and breast cancer, and participants with depression were associated with an increased risk for breast cancer. This finding provides new clues into the relationship between breast cancer and depression and sleep duration, and provides potential evidence for subsequent studies of pathological mechanisms.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.