Objective To identify the perception of pain among breast cancer patients and their quality of life, and to assess the influence of pain on their quality of life. Methods We did a cross-sectional study. A face-to-face survey was administered to 200 breast cancer patients, using two scales: Chinese Cancer Pain Assessment Tool (CCPAT) and European Organization for Research and Treatment of Cancer Core Quality-of-Life Questionnaire (Version 3) [EORTIC QLQ-C30]. Results Among the 200 breast cancer patients, 84 suffered from pain, while 116 did not. In regard to quality of life, the scores of physical function, role function and social function were higher among women without pain than among those in the pain group (Plt;0.05). There were no significant differences in scores of emotional function, cognitive function and global quality of life between the two groups (Pgt;0.05). There was a significant negative correlation between pain and quality of life in the pain group, the non-pain group and the whole sample (r=–0.731, Plt;0.001). Conclusion Pain has negative effects on physical function, role function and social function of breast cancer patients. The exacerbation of pain is associated with a decreased global quality of life for breast cancer patients.
Objective To identify the correlative symptoms of breast cancer patients and their influence on quality of life. Methods The cross-sectional study was used. A face-to-face survey was administered to 200 breast cancer patients, using two scales: ① Memorial Symptom Assessment Scale(MSA); ② European Organization for Research and Treatment of Cancer Core Quality-of-Life Questionnaire (Version 3) [EORTIC QLQ-C30]. Results The top five most highly prevalent symptoms were: lack of energy, hair loss, nervousness, sweating and worry. The five most frequent symptoms were: lack of energy, difficulty in sleeping, dry mouth, lack of appetite and sweating. The five most severe symptoms were: hair loss, lack of energy, difficulty in sleeping, nervousness and a change in food preference. The top five symptoms causing much distress were: hair loss, a feeling of“I don’t look like myself”, difficulty in sleeping, lack of appetite and lack of energy. The major factors influencing quality of life were: lack of energy, worry, pain, difficulty in sleeping, constipation, irritability, dry mouth, sweating, numbness/tingling in hands/feet, changes in skin, diarrhea, nausea, lack of appetite, and shortness of breath. Adjusted R square was 0.790. Conclusions The most conspicuous symptom in breast cancer patients is lack of energy. The symptom that distresses patients most is hair loss. The other notable symptoms are: “I don’t look like myself”, difficulty in sleeping, and lack of appetite. In addition, the quality of life is influenced by fourteen symptoms, and these symptoms account for 79.0% of the variance in quality of life.
Objective To explore the influencing factors of internet game addiction among middle school students. Methods Students from a certain district in Sichuan between September 2022 and March 2023 were included as participants. Basic information such as gender, age, whether the subjects were only children, place of residence, parental education, and subjective economic status were investigated. The nine-item Internet Gaming Disorder Scale-short form was used to investigate whether participants had internet game addiction, and the Berkman-Syme Social Network Index was used to evaluate the participants’ social level. Multiple linear regression analysis was used to conduct multivariate analysis to explore the influencing factors of internet game addiction. Results A total of 594 questionnaires were distributed, and 592 valid questionnaires were ultimately obtained. The detection rate of internet game addiction was 12.0%. Multiple linear regression analysis showed that gender (t=?8.281, P<0.001), age (t=3.211, P=0.001), subjective economic status in the region (t=2.025, P=0.043), and social level (t=?4.239, P<0.001) were the influencing factors of online game addiction. Due to the P value was close to the set test level (0.05), subjective economic status in the region was not considered an influencing factor of internet game addiction. Conclusion Teenagers with male gender, older age, and lower social skills are more likely to develop addiction to internet games.
Objective To identify potential clinical phenotypes in immunoglobulin G4-related disease (IgG4-RD) and to characterize differences in immune and metabolic profiles across distinct phenotypic subgroups. Methods A total of 125 patients diagnosed with IgG4-RD at West China Hospital, Sichuan University between January 2020 and December 2024 were retrospectively selected, and data regarding 12 organs (including the prostate) were collected. The prostate data were utilized solely for descriptive statistical purposes. Latent class analysis (LCA) was conducted using 11 organ variables, excluding the prostate, to perform a data-driven unsupervised classification of multiple organ involvement patterns. The optimal model was selected by comprehensively considering model fit indices, class size distribution, and clinical interpretability. Serum levels of immunoglobulin (Ig)G4, IgE, and uric acid were compared across different phenotypes. Results Among 125 patients with IgG4-RD, 89 were male (71.2%) and 36 were female (28.8%). Involvement of the pancreas was observed in 25 cases (20.0%), lymph nodes in 23 cases (18.4%), biliary system in 18 cases (14.4%), lungs in 16 cases (12.8%), lacrimal glands in 13 cases (10.4%), salivary glands and retroperitoneal fibrosis in 11 cases each (8.8%), eyes and pituitary glands in 7 cases each (5.6%), kidneys and aorta in 6 cases each (4.8%). LCA supported a three-class solution as optimal. Three distinct clinical phenotypes were identified: Class 1 (pulmonary-involvement type, n=26), characterized by frequent lung and lymph node involvement; Class 2 (mild systemic involvement type, n=89), showing limited multi-organ engagement; and Class 3 (glandular-lymphatic type, n=10), defined by predominant involvement of salivary glands, lacrimal glands, and lymph nodes, features resembling Mikulicz’s disease. Immunological and metabolic analysis revealed that the serum IgG4 level in Group 3 was higher than that in Group 1 and Group 2, but there was no statistically significant difference between the three groups (P>0.05). Spearman’s rank correlation analysis indicated a positive correlation between uric acid and IgG4 levels (r=0.2454, P=0.0067) as well as between IgE and IgG4 levels (r=0.4169, P<0.001). Conclusions Three distinct intrinsic clinical phenotypes of IgG4-RD were identified by LCA. Each phenotype exhibits characteristic patterns of organ involvement, along with specific immune and metabolic profiles. This suggests that interactions between metabolic and immune pathways may contribute to phenotypic differentiation and disease progression.