To summarize the distribution characteristics of human papillomavirus(HPV) infection types in patients with cervical squamous intraepithelial lesion(SIL) and cervical cancer(CC), and to explore the impact of HPV vaccination, HPV infection types, and general clinical data on different grades of cervical lesions.

To evaluate patient satisfaction levels in a gynecological teaching clinic and to explore its associated influencing factors, so as to provide evidence for optimizing the operational model of teaching clinics.

Objective:To explore the application of machine learning (ML) models based on radiomics and dosiomics to the assessment of hematologic toxicity (HT) in patients with locally advanced cervical cancer, and to preliminarily explore the comprehensive application of multi-omics features.Methods:A retrospective study was conducted on the clinical data, planning computed tomography (CT) images, and dose files of 205 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy at the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, from January 2022 to June 2023. Patients were categorized according to the severity of HT. Radiomics and dosiomics features were extracted from the same regions of interest (ROIs), followed by feature selection utilizing a random forest algorithm. Then, radiomics, dosiomics, and hybrid models were established based on extreme gradient boosting (XGBoost). The classification performance of these models was assessed by calculating their sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Results:The radiomics model yielded sensitivity, specificity, and AUC of 0.42, 0.86, and 0.78, respectively. The dosiomics model exhibited sensitivity, specificity, and AUC of 0.50, 0.90, and 0.74, respectively. In contrast, the hybrid model achieved sensitivity, specificity, and AUC of 0.50, 0.83, and 0.83, respectively. These findings suggest that the hybrid model possessed an enhanced classification capability compared to the individual radiomics and dosiomics models.Conclusions:It is feasible to use ML models based on radiomics and dosiomics to conduct the classification and prediction of HT in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Furthermore, integrating both radiomics features and dosiomics features can improve the classification performance of relevant prediction models, thus holding application potentials to optimize treatment strategies for patients with locally advanced cervical cancer.

Objective:To compare four postmastectomy radiotherapy plans with different arc angles for left-sided breast cancer prepared using deep inspiration breath hold (DIBH) technique, in order to explore the feasibility of selecting optimal arc angles based on the parameters of patients′ anatomical structures.Methods:A total of 51 patients who underwent postmastectomy radiotherapy for left-sided breast cancer using DIBH at the Second Affiliated Hospital of Guangxi Medical University and the First Affiliated Hospital of Guangzhou Medical University were selected. Among these, 40 patients selected using simple random sampling were treated with four radiotherapy plans with different arc angles, labeled as SV120, SV100, SV80, and SV60, while the remaining 11 patients were treated with only the SV60 plans. The dose parameters of the target volumes (TVs) and organs at risk (the heart, lungs, and contralateral breast), as well as the beam-on times of individual arcs, in these plans were compared. The parameters of the anatomical structures (i.e., the heart, lung, and breast) of the 51 patients, including PHeart, PLungl, and PBreast, were extracted. Taking these parameters as independent variables and the quality of the SV60 plans as the dependent variable, fitting was conducted using P(SV60)—a multivariate logistic regression model—based on a training set (45 patients) and a testing set (six patients). The classification threshold of the plans was set at 0.5. Results:As the arc angle increased, the plans exhibited improved modulation capabilities for TVs and the left lung. However, the V5 of the right lung and the average beam-on time of a single arc also increased. The SV120 plans demonstrated significantly better V107% of planning target volume (PTV; 6.84%), homogeneity index (HI; 0.13), conformity index (CI; 0.81), and mean dose to the left lung (1 330.97 cGy) compared to the other three types of plans, with statistically significant differences ( W = 0-99, P < 0.001). The SV60 plans displayed lower mean doses to the contralateral breast (198.97 cGy) and the heart (440.35 cGy) and lower V5 of the right lung (0.27%) than the other three types of plans, with significant differences in V5 of the right lung and the mean dose to the contralateral breast ( W = 0-157, P < 0.001). In contrast, no significant difference was observed in these parameters (except for V5 of the right lung) among the other three types of plans. The four types of plans exhibited average beam-on times of individual arcs of 22.0, 19.1, 16.1, and 14.4 s, respectively, with statistically significant differences ( χ2= 93.0, P < 0.001). A multivariate logistic regression model revealed that PLungl, PHeart, and PBreast were negatively correlated with the quality of the SV60 plans ( t = -64.84, -28.20, -24.45, P<0.001). This model yielded an accuracy of 93.33% and a precision of 92.86% in the training set, while its accuracy and precision reached 100% in the testing set. Conclusions:For patients treated with postmastectomy radiotherapy for left-sided breast cancer using DIBH, it is feasible to select appropriate arc angles based on patients’ anatomical structures.

Objective:To explore the associations of temperature, relative humidity, and their interaction effect with fall risk.Methods:Data on fall cases were collected using the national injury surveillance system from May to September, in 2006-2022 in Hubei Province. Combined with the meteorological and air pollution data, we conducted a time-stratified case-crossover design and used conditional logistic regression models and distributed lag nonlinear models to examine the exposure-response relationships between temperature, humidity, and fall risk. We further divided the low and the high temperature groups and the low and the high relative humidity groups and analyzed the excess risk ( ER) of falls attributed to dry-hot or wet-hot events. Finally, we calculated the additive interactions of temperature and humidity on fall risk. Results:A total of 55 401 fall cases were included. With the increase in temperature and relative humidity decrease, the exposure-response curves of fall showed nonlinear upward trends among all populations. Gender and age differences were found in temperature-fall and relative humidity-fall risk relationships. Compared with wet-non-hot (normal temperature and high relative humidity) events, the ER of fall in dry-hot (high temperature and low relative humidity) events was 14.80% (95% CI: 9.69%- 20.15%), and the ER of wet-hot (high temperature and high relative humidity) events was 9.59% (95% CI: 2.52%-17.13%). However, there was no statistically significant difference between dry-hot and wet-hot events in the fall, and no statistically significant difference between different genders, ages, occupations, and fall occurred place (all P>0.05). No significant synergistic additive interaction was found between temperature and relative humidity on fall risk (relative excess risk due to interaction=-0.08, 95% CI: -0.19-0.02). Conclusions:Higher temperatures and lower relative humidity were associated with increased fall risk. Both dry-hot and wet-hot events had a higher risk of fall, while high temperature and low humidity have no synergistic effect on fall risk.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.
Humans ; Female ; Pelvic Organ Prolapse/epidemiology* ; Middle Aged ; Risk Assessment/methods* ; China/epidemiology* ; Multifactorial Inheritance ; Aged ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Case-Control Studies ; Adult ; Polymorphism, Single Nucleotide ; Genetic Risk Score ; East Asian People

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index