Workplace violence and depressive symptoms: the mediating role of fear of future workplace violence and burnout among Chinese nurses.

BACKGROUND: The mechanisms underlying the relationship between workplace violence (WPV) and depressive symptoms in nurses have been less studied. This study aims to examine the mediating role of fear of future workplace violence (FFWV) and burnout in the association between WPV and depressive symptoms. METHODS: We conducted a cross-sectional web survey at 12 tertiary hospitals in Shandong province, China, in 2020. The Center for Epidemiologic Studies Depression Scale (CESD-10), the Chinese version of the Maslach Burnout Inventory-General Survey and the Fear of Future Violence at Work Scale were used to collect data. Descriptive statistics, independent sample t-test, one-way analysis of variance, Pearson's correlation coefficient, and ordinary least squares regression with bootstrap resampling were used to analyze the data. RESULTS: The prevalence of depressive symptoms was 45.9% among nurses. The regression model showed that FFWV and burnout mediated the relationship between WPV and depressive symptoms. The total effects of WPV on depressive symptoms (3.109, 95% bootstrap CI:2.324 - 3.713) could be decomposed into direct (2.250, 95% bootstrap CI:1.583 - 2.917) and indirect effects (0.769, 95% bootstrap CI:0.543 - 1.012). Indirect effects mediated by FFWV and burnout were 0.203 (95% bootstrap CI:0.090 - 0.348) and 0.443 (95% bootstrap CI:0.262 - 0.642), respectively. Furthermore, serial multiple mediation analyses indicated that the indirect effect mediated by FFWV and burnout in a sequential manner was 0.123 (95% bootstrap CI:0.070 - 0.189). CONCLUSION: The prevalence of depressive symptoms among Chinese nurses was high. The WPV was an important risk factor for depressive symptoms and its negative effect was mediated by FFWV and burnout. The importance of decreasing WPV exposure and level of FFWV and burnout was emphasized to prevent depressive symptoms among nurses. The findings implied that hospital managers and health policy makers should not only develop targeted interventions to reduce exposure to WPV in daily work among all nurses, but also provide psychological support to nurses with WPV experience to reduce FFWV and burnout.

Acute kidney injury in hospitalized patients with nonmalignant pleural effusions: a retrospective cohort study.

BACKGROUND: Nonmalignant pleural effusion (NMPE) is common and remains a definite health care problem. Pleural effusion was supposed to be a risk factor for acute kidney injury (AKI). Incidence of AKI in NMPE patients and whether there is correlation between the size of effusions and AKI is unknown. OBJECTIVE: To assess the incidence of AKI in NMPE inpatients and its association with effusion size. STUDY DESIGN AND METHOD: We conducted a retrospective cohort study of inpatients admitted to the Chinese PLA General Hospital with pleural effusion from 2018-2021. All patients with pleural effusions confirmed by chest radiography (CT or X-ray) were included, excluding patients with diagnosis of malignancy, chronic dialysis, end-stage renal disease (ESRD), community-acquired AKI, hospital-acquired AKI before chest radiography, and fewer than two serum creatinine tests during hospitalization. Multivariate logistic regression and LASSO logistic regression models were used to identify risk factors associated with AKI. Subgroup analyses and interaction tests for effusion volume were performed adjusted for the variables selected by LASSO. Causal mediation analysis was used to estimate the mediating effect of heart failure, pneumonia, and eGFR < 60 ml/min/1.73m2 on AKI through effusion volume. RESULTS: NMPE was present in 7.8% of internal medicine inpatients. Of the 3047 patients included, 360 (11.8%) developed AKI during hospitalization. After adjustment by covariates selected by LASSO, moderate and large effusions increased the risk of AKI compared with small effusions (moderate: OR 1.47, 95%CI 1.11-1.94 p = 0.006; large: OR 1.86, 95%CI 1.05-3.20 p = 0.028). No significant modification effect was observed among age, gender, diabetes, bilateral effusions, and eGFR. Volume of effusions mediated 6.8% (p = 0.005), 4.0% (p = 0.046) and 4.6% (p < 0.001) of the effect of heart failure, pneumonia and low eGFR on the development of AKI respectively. CONCLUSION: The incidence of AKI is high among NMPE patients. Moderate and large effusion volume is independently associated with AKI compared to small size. The effusion size acts as a mediator in heart failure, pneumonia, and eGFR.

Establishment of patient-derived organoids for guiding personalized therapies in breast cancer patients.

Breast cancer has become the most commonly diagnosed cancer. The intra- and interpatient heterogeneity induced a considerable variation in treatment efficacy. There is an urgent requirement for preclinical models to anticipate the effectiveness of individualized drug responses. Patient-derived organoids (PDOs) can accurately recapitulate the architecture and biological characteristics of the origin tumor, making them a promising model that can overtake many limitations of cell lines and PDXs. However, it is still unclear whether PDOs-based drug testing can benefit breast cancer patients, particularly those with tumor recurrence or treatment resistance. Fresh tumor samples were surgically resected for organoid culture. Primary tumor samples and PDOs were subsequently subjected to H&E staining, immunohistochemical (IHC) analysis, and whole-exome sequencing (WES) to make comparisons. Drug sensitivity tests were performed to evaluate the feasibility of this model for predicting patient drug response in clinical practice. We established 75 patient-derived breast cancer organoid models. The results of H&E staining, IHC, and WES revealed that PDOs inherited the histologic and genetic characteristics of their parental tumor tissues. The PDOs successfully predicted the patient's drug response, and most cases exhibited consistency between PDOs' drug susceptibility test results and the clinical response of the matched patient. We conclude that the breast cancer organoids platform can be a potential preclinical tool used for the selection of effective drugs and guided personalized therapies for patients with advanced breast cancer.

Machine learning predicts the risk of osteoporosis in patients with breast cancer and healthy women.

OBJECTIVE: In this study, we investigated the effects of endocrine therapy and related drugs on the body composition and bone metabolism of patients with breast cancer. Additionally, using body composition-related indicators in machine learning algorithms, the risks of osteoporosis in patients with breast cancer and healthy women were predicted. METHODS: We enrolled postmenopausal patients with breast cancer who were hospitalized in a tertiary hospital and postmenopausal women undergoing health checkups in our hospital between 2019 and 2021. The basic information, body composition, bone density-related indicators, and bone metabolism-related indicators of all the study subjects were recorded. Machine learning models were constructed using cross-validation. RESULTS: Compared with a healthy population, the body composition of patients with breast cancer was low in bone mass, protein, body fat percentage, muscle, and basal metabolism, whereas total water, intracellular fluid, extracellular fluid, and waist-to-hip ratio were high. In patients with breast cancer, the bone mineral density (BMD), Z value, and T value were low and the proportion of bone loss and osteoporosis was high. BMD in patients with breast cancer was negatively correlated with age, endocrine therapy status, duration of medication, and duration of menopause, and it was positively correlated with body mass index (BMI) and basal metabolism. The parameters including body composition, age, hormone receptor status, and medication type were used for developing the machine learning model to predict osteoporosis risk in patients with breast cancer and healthy populations. The model showed a high accuracy in predicting osteoporosis, reflecting the predictive value of the model. CONCLUSIONS: Patients with breast cancer may have changed body composition and BMD. Compared with the healthy population, the main indicators of osteoporosis in patients with breast cancer were reduced nonadipose tissue, increased risk of edema, altered fat distribution, and reduced BMD. In addition to age, duration of treatment, and duration of menopause, body composition-related indicators such as BMI and basal metabolism may be considerably associated with BMD of patients with breast cancer, suggesting that BMD status can be monitored in clinical practice by focusing on changes in the aforementioned indexes, which may provide a way to prevent preclinical osteoporosis.

Persistent B Cell-Derived MHC Class II Signaling Is Required for the Optimal Maintenance of Tissue-Resident Helper T Cells.

Emerging studies have identified the critical roles of tissue-resident memory CD8+ T (TRM) and B (BRM) cells in the protection against mucosal viral infections, but the underlying mechanisms regulating robust development of TRM and BRM cells remain incompletely understood. We have recently shown that tissue-resident helper CD4+ T (TRH) cells, developed following influenza virus infection, function to sustain the optimal maintenance of TRM and BRM cells at the mucosal surface. In this study, we have explored the cellular and molecular cues modulating lung TRH persistence after influenza infection in C57BL/6 mice. We found that TRH cells were colocalized in tertiary lymphoid structures (TLSs) with local B cells. Abolishing TLSs or the depletion of B cells impaired lung TRH cell numbers. Of note, we found that persistent TCR signaling is needed for the maintenance of TRH cells after the clearance of infectious influenza virus. Furthermore, selective ablation of B cell-derived MHC class II resulted in partial reduction of lung TRH cell number after influenza infection. Our findings suggest that the interaction between lung-resident TRH cells and B cells, along with persistent Ag stimulation, is required to maintain TRH cells after respiratory viral infection.

Rotational gland dissection for refractory granulomatous mastitis: A single-center retrospective study.

BACKGROUND: Refractory granulomatous mastitis (RGM) is a chronic benign breast disease that commonly occurred in women of childbearing age and is usually treated with surgery, with numerous cases suffering from unsatisfied postoperative recovery of breast shape, high rates of surgical complications, and even high recurrence. This study tries to evaluate the efficacy of an innovative surgical procedure, the rotational gland dissection for the treatment of RGM. METHODS: 129 patients with RGM who underwent surgical treatment at the Second Affiliated Hospital of Xi'an Jiaotong University between Apr. 2017 and May. 2021 were retrospectively included in this study. The article analyzed the age, local symptoms, lesion location, and size, days in hospital, recurrence rate, and satisfaction rate of the patients. RESULTS: Patients ranged in age from 19 to 58 years, with a median age of onset of 32 years. In 63 patients (48.84%), their lesions coverage exceeded two quadrants, and 52.71% of patients had lesions larger than 10 cm2. The average days in hospital of patients was 7.5 days, and 85.27% of them were satisfied with their post-surgery breast appearance. Within the median follow-up of 56 months, only 3.10% of patients experienced a recurrence of mastitis on the operation side. CONCLUSION: This novel surgical procedure we created is an effective treatment for RGM with a high success rate, high patient satisfaction, and low recurrence rate, and is significantly superior to other studies for it has the largest sample size and longest follow-up in this field.

High dose Vitamin C inhibits PD-L1 by ROS-pSTAT3 signal pathway and enhances T cell function in TNBC.

Vitamin C (VitC) presents excellent anti-tumor effect for long time. Recently, high dose VitC achieved by intravenous administration manifests superior anti-tumor effect. However, the functions and detailed mechanisms of high dose VitC's role in cancer immunity are not fully understood. This study investigates the effect of high dose VitC on PD-L1 expression in triple negative breast cancer (TNBC) and the potential mechanism. Results showed VitC inhibited PD-L1 expression in breast cancer cell lines and enhanced anti-tumor effects of T cells. Furthermore, we found VitC inhibited PD-L1 transcription through ROS-pSTAT3 signal pathways. Consistent with in vitro results, in vivo study showed VitC suppressed tumor growth in immunocompetent mice and enhanced CD8+ T cells infiltration and function in tumor microenvironment. Our findings identify the effects of high dose VitC on PD-L1 expression and provide a rationale for the use of high dose VitC as immunomodulator for cancer therapy.

Proximal immune-epithelial progenitor interactions drive chronic tissue sequelae post COVID-19.

The long-term physiological consequences of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are rapidly evolving into a major public health concern. The underlying cellular and molecular etiology remain poorly defined but growing evidence links PASC to abnormal immune responses and/or poor organ recovery post-infection. Yet, the precise mechanisms driving non-resolving inflammation and impaired tissue repair in the context of PASC remain unclear. With insights from three independent clinical cohorts of PASC patients with abnormal lung function and/or viral infection-mediated pulmonary fibrosis, we established a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. By employing a combination of spatial transcriptomics and imaging, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to the fibroproliferation in respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell-macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, thus impairing alveolar regeneration and driving fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-γ and TNF stimulated lung macrophages to chronically release IL-1ß, resulting in the abnormal accumulation of dysplastic epithelial progenitors and fibrosis. Notably, therapeutic neutralization of IFN-γ and TNF, or IL-1ß after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC. Moreover, in contrast to other approaches requiring early intervention, we highlight therapeutic strategies to rescue fibrotic disease in the aftermath of respiratory viral infections, addressing the current unmet need in the clinical management of PASC and post-viral disease.

Tensile Strain-Dependent Ultrafast Electron Transfer and Relaxation Dynamics in Flexible WSe2/MoS2 Heterostructures.

Understanding and controlling carrier dynamics in two-dimensional (2D) van der Waals heterostructures through strain are crucial for their flexible applications. Here, femtosecond transient absorption spectroscopy is employed to elucidate the interlayer electron transfer and relaxation dynamics under external tensile strains in a WSe2/MoS2 heterostructure. The results show that a modest ∼1% tensile strain can significantly alter the lifetimes of electron transfer and nonradiative electron-hole recombination by >30%. Ab initio non-adiabatic molecular dynamics simulations suggest that tensile strain weakens the electron-phonon coupling, thereby suppressing the transfer and recombination dynamics. Theoretical predictions indicate that strain-induced energy difference increases along the electron transfer path could contribute to the prolongation of the transfer lifetime. A subpicosecond decay process, related to hot-electron cooling, remains almost unaffected by strain. This study demonstrates the potential of tuning interlayer carrier dynamics through external strains, offering insights into flexible optoelectronic device design with 2D materials.

A novel web-based prognostic nomogram and the features influencing the curative effect of chemotherapy and radiotherapy for Paget's disease with invasive ductal carcinoma.

Paget's disease (PD) of the breast is a rare underlying malignant tumor. Approximately 50% to 60% of patients with mammary PD are concurrently diagnosed with invasive ductal carcinoma (PD-IDC), a condition associated with a worse prognosis than IDC without PD. Thus far, there has been a lack of an accurate and efficient prognostic model for PD-IDC, and the factors influencing the effectiveness of chemotherapy and radiotherapy for these patients remain unknown. In this study, we developed a web-based nomogram based on the data from the Surveillance Epidemiology and End Results (SEER) database. We subjected the model to a series of validation methods, including area under the curve (AUC) values, receiver operating characteristic curve (ROC) analysis, calibration curves, and decision curve analysis (DCA). Our results demonstrated that our model exhibited high discrimination, accuracy, and clinical applicability in predicting the overall survival (OS) of patients with PD-IDC (testing set: three- and five-year AUCs, 0.831 and 0.841, respectively). To further validate our nomogram, we used external data from both our institution and sister hospitals (external data: three- and five-year AUCs, 0.892 and 0.914, respectively). Multivariable Cox regression analysis identified several independent unfavorable prognostic factors for the OS of patients with PD-IDC, including increasing age, high grade, widowed status, higher T stages, and the presence of bone metastases. Furthermore, propensity score matching (PSM)-adjusted analysis was conducted, revealing that chemotherapy did not significantly improve the survival of patients with PD-IDC across molecular subtypes, except for those in the grade III/IV group, where it improved both OS and breast cancer-specific survival (BCSS). Additionally, our findings indicated that only patients with PD-IDC with T4 and N3 stages benefited from radiotherapy, leading to improvements in both OS and BCSS. In conclusion, we have comprehensively analyzed the clinical characteristics and prognosis of patients with PD-IDC, culminating in the development of a user-friendly web-based nomogram for predicting their survival. Our predictive model is not only highly accurate but also offers simplicity, making it accessible for healthcare providers and patients. Furthermore, our stratified analysis highlights that the pathological grade, rather than the molecular subtype, plays a pivotal role in determining the efficacy of chemotherapy in improving the prognosis for patients with PD-IDC, while radiotherapy confers survival benefits to patients with PD-IDC in T4 and N3 stages.

Health-related quality of life and its changes of the Tibetan population in China: based on the 2013 and 2018 National Health Services Surveys.

OBJECTIVE: Health-related quality of life (HRQoL) was an important health outcome measure for evaluating an individual's overall health status. However, there was limited in the literature on HRQoL and its long-term changes of the Tibetan population. This study aimed to assess HRQoL of Tibetan and its changes over time, and explore the differences in HRQoL for residents at different altitudes. DESIGN: Data for the cross-sectional study were extracted from the fifth and sixth waves of the National Health Services Surveys which were conducted in 2013 and 2018. A multistage stratified cluster random sampling strategy was used to select representative participants. SETTING: Tibet Autonomous Region in China. PARTICIPANTS: This study recruited 14 752 participants in 2013 and 13 106 participants in 2018, and after excluding observations with missing values for key variables, 10 247 in 2013 and 6436 in 2018 were included in the study analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: The EQ-5D-3L was used to measure participants' HRQoL. RESULTS: The mean health state utility scores of the participants were 0.969±0.078 and 0.966±0.077 in 2013 and 2018, respectively. Pain/discomfort was the most frequently prevalent issue reported in 18.1% and 17.9% of the participants in 2013 and 2018, respectively. Tibetans living 3500-4000 m altitude had the best HRQoL. Age, sex, employment status, educational attainment, chronic disease and weekly physical exercise were influencing factors associated with HRQoL. CONCLUSIONS: The HRQoL of the Tibetan population was lower than the general Chinese population, and decreased over time between 5 years. There were differences in HRQoL among Tibetan at different altitudes, with residents living at 3500-4000 m having the best quality of life. More attention should be paid to those Tibetans who are older, female, unemployed and without formal education.

Proximal immune-epithelial progenitor interactions drive chronic tissue sequelae post COVID-19.

The long-term physiological consequences of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are rapidly evolving into a major public health concern. The underlying cellular and molecular etiology remain poorly defined but growing evidence links PASC to abnormal immune responses and/or poor organ recovery post-infection. Yet, the precise mechanisms driving non-resolving inflammation and impaired tissue repair in the context of PASC remain unclear. With insights from three independent clinical cohorts of PASC patients with abnormal lung function and/or viral infection-mediated pulmonary fibrosis, we established a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. By employing a combination of spatial transcriptomics and imaging, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to the fibroproliferation in respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell-macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, thus impairing alveolar regeneration and driving fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-γ and TNF stimulated lung macrophages to chronically release IL-1ß, resulting in the abnormal accumulation of dysplastic epithelial progenitors and fibrosis. Notably, therapeutic neutralization of IFN-γ and TNF, or IL-1ß after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC. Moreover, in contrast to other approaches requiring early intervention, we highlight therapeutic strategies to rescue fibrotic disease in the aftermath of respiratory viral infections, addressing the current unmet need in the clinical management of PASC and post-viral disease.

Causal associations of Sjögren's syndrome with cancers: a two-sample Mendelian randomization study.

BACKGROUND: Several observational studies have explored the associations between Sjögren's syndrome (SS) and certain cancers. Nevertheless, the causal relationships remain unclear. Mendelian randomization (MR) method was used to investigate the causality between SS and different types of cancers. METHODS: We conducted the two-sample Mendelian randomization with the public genome-wide association studies (GWASs) summary statistics in European population to evaluate the causality between SS and nine types of cancers. The sample size varies from 1080 to 372,373. The inverse variance weighted (IVW) method was used to estimate the causal effects. A Bonferroni-corrected threshold of P < 0.0031 was considered significant, and P value between 0.0031 and 0.05 was considered to be suggestive of an association. Sensitivity analysis was performed to validate the causality. Moreover, additional analysis was used to assess the associations between SS and well-accepted risk factors of cancers. RESULTS: After correcting the heterogeneity and horizontal pleiotropy, the results indicated that patients with SS were significantly associated with an increased risk of lymphomas (odds ratio [OR] = 1.0010, 95% confidence interval [CI]: 1.0005-1.0015, P = 0.0002) and reduced risks of prostate cancer (OR = 0.9972, 95% CI: 0.9960-0.9985, P = 2.45 × 10-5) and endometrial cancer (OR = 0.9414, 95% CI: 0.9158-0.9676, P = 1.65 × 10-5). Suggestive associations were found in liver and bile duct cancer (OR = 0.9999, 95% CI: 0.9997-1.0000, P = 0.0291) and cancer of urinary tract (OR = 0.9996, 95% CI: 0.9992-1.0000, P = 0.0281). No causal effect of SS on other cancer types was detected. Additional MR analysis indicated that causal effects between SS and cancers were not mediated by the well-accepted risk factors of cancers. No evidence of the causal relationship was observed for cancers on SS. CONCLUSIONS: SS had significant causal relationships with lymphomas, prostate cancer, and endometrial cancer, and suggestive evidence of association was found in liver and bile duct cancer and cancer of urinary tract, indicating that SS may play a vital role in the incidence of these malignancies.

Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

Risk, molecular subtype and prognosis of second primary breast cancer: an analysis based on first primary cancers.

Second primary breast cancer (SPBC) was potentially related to other cancers, which may impact its incidence, prognosis and therapeutic approaches. Nevertheless, few studies have characterized this relationship and analyzed the subtypes of SPBC. Our study intended to investigate the occurrence and prognosis of SPBC. We analyzed the patterns, clinical characteristics, standardized incidence ratio (SIR) and standardized mortality ratio (SMR) of patients with SPBC. The propensity score matching (PSM) approach was further used to balance the differences in clinical features between patients with primary breast cancer (PBC) and SPBC, then Kaplan-Meier (KM) survival analysis was used to compare their overall survival and breast cancer-specific survival. Finally, a predictive model was constructed to estimate the 3- and 5-year survival rates of SPBC patients. We found that the SIR of individuals with SPBC was significantly higher in cancer survivors than in the general population (SIR=1.16, 95% CI=1.15-1.17, P<0.05). SPBC patients with first primary lung/bronchus cancer had a much higher SMR (SMR=1.71, 95% CI=1.58-1.85, P<0.05) compared with survivors of other malignancies. Individuals with SPBC had a larger proportion of the HR-/HER2- subtype than those with PBC. Particularly among survivors of estrogen-dependent ovarian and breast cancer, the proportion of the HR-/HER2- subtype of SPBC considerably rose. After propensity score matching, we discovered that SPBC patients' overall survival remained poorer than that of PBC patients (HR=1.43, 95% CI=1.39-1.47, P<0.001). However, the prognosis of SPBC in first primary thyroid cancer survivors was better than PBC patients (HR=0.64, 95% CI=0.55-0.75, P<0.001). Also, an extreme gradient boosting (XGBoost) model was developed to evaluate the 3-year (AUC=0.817) and 5-year survival (AUC=0.825) of SPBC patients. Our data demonstrated the distinct biological performance of SPBC with various first primary cancers. Furthermore, our findings revealed an indispensable role of first primary cancer (FPC) in the development of SPBC and provided an additional theoretical basis for the clinical follow-up and identification of SPBC.

Mapping the Seattle Angina Questionnaire to EQ-5D-5L in patients with coronary heart disease.

BACKGROUND: Health economic evaluation is critical in supporting novel cardiovascular disease therapies. However, most clinical studies do not include preference-based questionnaires to calculate utilities for health economic evaluations. Thus, this study aimed to develop mapping algorithms that convert the Seattle Angina Questionnaire (SAQ) to EQ-5D-5L health utility scores for patients with coronary health disease (CHD) in China. METHODS: Data were obtained from a longitudinal study of patients with CHD conducted at the Tianjin Medical University General Hospital in China. Convenience sampling was used to recruit patients with CHD. The inclusion criteria were having been diagnosed with CHD through a medical examination and being aged 18 years or older. The exclusion criteria were a lack of comprehension ability, serious comorbidities, mental illness, and hearing or vision impairment. All eligible patients were invited to participate, and 305 and 75 patients participated at baseline and in the follow-up, respectively. Seven regression models were developed using a direct approach. Furthermore, we predicted the five EQ-5D items using ordered logit model and derived the utility score from predicted responses using an indirect approach. Model performances were evaluated using mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (ρ), and Lin's concordance correlation coefficient (CCC). A five-fold cross-validation method was used to evaluate internal validation. RESULTS: The average age was 63.04 years, and 53.72% of the included patients were male. Most (70.05%) patients had unstable angina pectoris, and the mean illness duration was 2.50 years. The EQ-5D scores were highly correlated with five subscales of the SAQ, with Spearman's rank correlation coefficients ranging from 0.6184 to 0.7093. The mixture beta model outperformed the other regression models in the direct approach, with the lowest MAE and RMSE and highest ρ and CCC. The ordered logit model in the indirect approach performed the same as the mixture beta regression with equal MAE, lower RMSE, and higher ρ and CCC. CONCLUSION: Mapping algorithms developed using mixture beta and ordered logit models accurately converted SAQ scores to EQ-5D-5L health utility values, which could support health economic evaluations related to coronary heart disease.

Visualized machine learning models combined with propensity score matching analysis in single PR-positive breast cancer prognosis: a multicenter population-based study.

The characteristics of single PR-positive (ER-PR+, sPR+) breast cancer (BC) and its prognosis are not well elucidated due to its rarity and conflicting evidence. There is a lack of an accurate and efficient model for predicting survival, thereby rendering treatment challenging for clinicians. Whether endocrine therapy should be intensified in sPR+ BC patients was another controversial clinical topic. We constructed and cross-validated XGBoost models that showed high precision and accuracy in predicting the survival of patients with sPR+ BC cases (1-year: AUC=0.904; 3-year: AUC=0.847; 5-year: AUC=0.824). The F1 score for the 1-, 3-, and 5-year models were 0.91, 0.88, and 0.85, respectively. The models exhibited superior performance in an external, independent dataset (1-year: AUC=0.889; 3-year: AUC=0.846; 5-year: AUC=0.821). Further, intensified endocrine therapy did not provide a significant overall survival benefit compared to initial or no endocrine therapy (P=0.600, HR: 1.46; 95% CI: 0.35-6.17). Propensity-score matching (PSM)-adjusted data showed that there was no statistically significant difference in the prognosis between ER-PR+HER2+ and ER-PR-HER2+ BC. Patients having the ER-PR+HER2- subtype had a slightly worse prognosis than those with the ER-PR-HER2- subtype. In conclusion, XGBoost models can be highly reproducible and effective in predicting survival in patients with sPR+ BC. Our findings revealed that patients with sPR-positive BC may not benefit from endocrine therapy. Patients with sPR+ BC may benefit from intensive adjuvant chemotherapy compared to endocrine therapy.