Relationship between dyspnoea and related factors in patients with cancer: a cross-sectional study.

OBJECTIVES: Dyspnoea is a common and distressing symptom in patients with cancer. We aimed to analyse the association between dyspnoea and related factors and to estimate their causal relationship. METHODS: A cross-sectional study was conducted. Patients with cancer with dyspnoea and a mean Numerical Rating Scale (NRS) of ≥3 over 24 hours were enrolled at 10 institutions in Japan from December 2019 to February 2021. The outcomes included dyspnoea, cough and pain NRS over 24 hours, Eastern Cooperative Oncology Group Performance Status, Hospital Anxiety and Depression Scale, Somatosensory Amplification Scale, opioids for dyspnoea and respiratory failure. Path analyses were conducted to estimate the direct and indirect paths with reference to dyspnoea and related factors. RESULTS: A total of 209 patients were enrolled and 208 patients were included in the analysis. Cough worsened dyspnoea (ß=0.136), dyspnoea increased emotional distress (ß=1.104), emotional distress increased somatosensory amplification (ß=0.249) and somatosensory amplification worsened cough (ß=0.053) according to path analysis. CONCLUSION: There may be a vicious circle among dyspnoea and related factors: cough worsened dyspnoea, dyspnoea increased emotional distress, emotional distress increased somatosensory amplification and somatosensory amplification worsened cough. When treating dyspnoea in patients with cancer, managing these factors aimed at interrupting this vicious circle may be useful. TRIAL REGISTRATION NUMBER: UMIN Clinical Trials Registry (UMIN000038820).

Influence of social isolation and loneliness on the prognosis of advanced lung cancer patients: a prospective cohort study.

PURPOSE: The purpose of this study was to investigate the impact of social isolation and loneliness on the overall survival and death at home in patients with lung cancer. METHODS: This prospective cohort study was conducted in a Japanese tertiary hospital. The enrollment period was from April 2018 to March 2020. Patients with pathologically diagnosed advanced lung cancer were included in this study. The primary outcome was overall survival, whereas the secondary outcome was death at home. The exposures were social isolation and loneliness. RESULTS: A total of 211 patients were enrolled and divided into two groups and further into quartiles according to their social isolation and loneliness level, respectively. The hazard ratios of social isolation were 1.65 (95% confidence interval; 1.12 to 2.44) and 1.87 (95% confidence interval; 1.15 to 3.03) in the univariate analysis, while 1.40 (95% confidence interval; 0.92 to 2.13) in the multivariate analysis with complete case and multiple imputation. The odds ratio of death at home with social isolation was 3.47 (95% confidence interval; 1.08 to 11.1) in the multivariate analysis with multiple imputation. Loneliness was not associated with overall survival or death at home. CONCLUSIONS: Our study suggests that social isolation may be related to overall survival and death at home among patients with advanced lung cancer. More attention should be given to such patients at the time of diagnosis.

Development and external validation of a deep learning-based computed tomography classification system for COVID-19.

BACKGROUND: We aimed to develop and externally validate a novel machine learning model that can classify CT image findings as positive or negative for SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR). METHODS: We used 2,928 images from a wide variety of case-control type data sources for the development and internal validation of the machine learning model. A total of 633 COVID-19 cases and 2,295 non-COVID-19 cases were included in the study. We randomly divided cases into training and tuning sets at a ratio of 8:2. For external validation, we used 893 images from 740 consecutive patients at 11 acute care hospitals suspected of having COVID-19 at the time of diagnosis. The dataset included 343 COVID-19 patients. The reference standard was RT-PCR. RESULTS: In external validation, the sensitivity and specificity of the model were 0.869 and 0.432, at the low-level cutoff, 0.724 and 0.721, at the high-level cutoff. Area under the receiver operating characteristic was 0.76. CONCLUSIONS: Our machine learning model exhibited a high sensitivity in external validation datasets and may assist physicians to rule out COVID-19 diagnosis in a timely manner at emergency departments. Further studies are warranted to improve model specificity.

Influence of loneliness and social isolation on the diagnosis and treatment of Japanese patients with advanced lung cancer: a prospective cohort study.

BACKGROUND: Social determinants of health (SDHs) are social factors that affect human health; loneliness and social isolation are core SDH factors. There is a possibility that SDHs are related to passive decision-making. However, few studies have evaluated SDHs, especially social isolation and loneliness, among lung cancer patients. This study aims to investigate the effects of social isolation and loneliness on the diagnosis and treatment of Japanese lung cancer patients. METHODS: This is a prospective cohort study that was conducted in a tertiary referral hospital in Japan (University Hospital Medical Information Network registration: UMIN000031810). The enrollment period was between April 2018 and March 2020. Patients with clinical and/or pathological diagnosis of lung cancer were enrolled in this study. Exposures were social isolation and loneliness, and main outcomes were diagnosis methods and whether the initial treatment involved active therapy or best supportive care (BSC). The confounding factors were defined as sex, age, smoking status, respiratory symptoms, weight loss, presentation with any symptoms, Eastern Cooperative Oncology Group (ECOG) performance status, tumor nodes metastasis (TNM) classification, driver gene mutations [i.e., epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK)], and programmed death-ligand 1 (PD-L1) tumor proportion score. RESULTS: The study enrolled 264 patients who were divided into quartiles according to their loneliness scores and into two groups according to the social isolation level. Univariate analysis, complete case analysis, and multivariate analysis with multiple imputation failed to detect significant differences in diagnostic method or initial treatment strategy according to loneliness or social isolation level. CONCLUSIONS: Physicians may not need to consider a patient's loneliness and/or social isolation when diagnosing lung cancer and selecting treatment under universal health insurance coverage. Further studies are needed to understand the influences of loneliness and social isolation on the prognosis of lung cancer patients.

Factors Influencing Social Isolation and Loneliness Among Lung Cancer Patients: A Cross-sectional Study.

BACKGROUND/AIM: Previous reviews of Social determinants of health in lung cancer patients have not examined essential factors such as social isolation and loneliness. This study aimed to explore the factors affecting social isolation and loneliness among lung cancer patients. PATIENTS AND METHODS: A cross-sectional study was conducted. Social isolation, loneliness, and the presence of dementia were measured using Japanese adaptations of the Lubben Social Network Scale, UCLA Loneliness Scale, and Life Function Evaluation for Care Provision, respectively. RESULTS: From March 2019 to March 2020, 264 patients were included. Social isolation was significantly higher for patients receiving welfare (adjusted OR=5.28, 95% CI=2.24-12.4). Loneliness was significantly higher for patients receiving welfare (beta coefficient=0.52, 95% Cl=0.13-0.90) with symptoms of dementia (beta coefficient=0.28, 95% Cl=0.03-0.54). CONCLUSION: Results showed that receiving welfare was associated with experiencing social isolation. Receiving welfare and symptoms of dementia were associated with experiencing loneliness.

Influence of social determinants of health on patients with advanced lung cancer: a prospective cohort study.

INTRODUCTION: Socioeconomic factors with an influence on human health are known as social determinants of health (SDH). There are some SDH studies in patients with lung cancer, but important exposures such as social isolation and loneliness have not been adequately investigated. This study will assess the influence of SDH, particularly social isolation and loneliness, on patients with advanced lung cancer in Japan. METHODS AND ANALYSIS: The inclusion criteria for this prospective cohort study will be as follows: a diagnosis of advanced lung cancer; unsuitability for curative surgery; and willingness to participate. The primary outcome will be the initial choice of treatment and the secondary outcomes will be overall survival, changes in disease staging or performance status, route to diagnosis and place of death. The exposures will be social isolation, loneliness, employment, insurance type, education and dementia. The study enrolment period will be 1 year and the follow-up duration will be 2 years. The log-rank test will be used to compare overall survival between patients when grouped according to the study exposures and multivariate analysis will be performed using Cox proportional hazards regression. The Χ2 test will be used to compare the initial treatment, changes in disease stage and place of death, and logistic regression will be used for multivariate analysis of these factors. A p value <0.05 will be considered statistically significant. ETHICS AND DISSEMINATION: This study has been approved by the Institutional Review Board at Hyogo Prefectural Amagasaki General Medical Center (No 29-164). A manuscript summarising the outcome of this study will be submitted to a peer-reviewed journal and the data will be presented at conferences. TRIAL REGISTRATION NUMBER: UMIN000031810.