Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

Objective To analyze the medication rules of traditional Chinese medicine in treating breast cancer based on real-world data mining.Methods Inpatients with breast cancer who received traditional Chinese medicine treatment at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from January 2017 to December 2021 were selected.Python 3.10 software was used to mine traditional Chinese medicine prescription data;SPSS 23.0 software was applied for descriptive analysis,and systematic cluster analysis was performed on high-frequency drugs.Results A total of 3026 consultation records of inpatients with breast cancer were collected.The main traditional Chinese medicine syndrome diagnosis of"predominantly liver depression and Qi stagnation"accounted for 60.94％of the total consultations.A total of 240 kinds of traditional Chinese medicine were used,with a cumulative frequency of 35 462 times.Among them,29 kinds of traditional Chinese medicine such as Danggui,Fuling,Baizhu,Chaihu had a cumulative usage frequency exceeding 300 times.Regarding the four natures of drugs,cold-natured(43.55％),warm-natured(30.05％),and neutral-natured(23.34％)drugs were predominant;In terms of five flavors,sweet(46.12％),bitter(30.91％),and pungent(20.02％)were the main ones.The most frequently used drugs were tonifying herbs(32.77％),followed by heat-clearing herbs(15.96％)and phlegm-resolving herbs(14.71％).Systematic cluster analysis yielded 7 groups of drug combinations.Conclusion In real-world clinical practice,traditional Chinese medicine for breast cancer mainly uses tonifying herbs,reflecting the traditional Chinese medicine principle of"strengthening healthy Qi and cultivating the root"in treating tumors.The four natures and five flavors of drugs follow syndrome differentiation and the combination of cold and heat.The clustered drug combinations have extensive therapeutic effects,covering various syndromes of breast cancer at different stages,which can provide a reference for clinical medication.

Objective Our study aimed to provide a comprehensive overview of the current status and dynamic trends of the human immunodeficiency virus (HIV) prevalence in Sichuan,the second most heavily affected province in China,and to explore future interventions. Methods The epidemiological,behavioral,and population census data from multiple sources were analyzed to extract inputs for an acquired immunodeficiency syndrome (AIDS) epidemic model (AEM). Baseline curves,derived from historical trends in HIV prevalence,were used,and the AEM was employed to examine future intervention scenarios. Results In 2015,the modeled data suggested an adult HIV prevalence of 0.191％ in Sichuan,with an estimated 128,766 people living with HIV/AIDS and 16,983 individuals with newly diagnosed infections. Considering current high-risk behaviors,the model predicts an increase in the adult prevalence to 0.306％ by 2025,projecting an estimated 212,168 people living with HIV/AIDS and 16,555 individuals with newly diagnosed infections. Conclusion Heterosexual transmission will likely emerge as the primary mode of AIDS transmission in Sichuan. Furthermore,we anticipate a stabilization in the incidence of AIDS with a concurrent increase in prevalence. Implementing comprehensive intervention measures aimed at high-risk groups could effectively alleviate the spread of AIDS in Sichuan.

Objective:To understand the impact of intimate social networks and sexual networks on HIV-infection in men aged ≥50 years in Pengzhou, Sichuan Province, and provide reference for the formulation of HIV/AIDS prevention and control strategies in middle-aged and elderly people.Methods:A case-control study was conducted by an interview-style questionnaire survey in a case group consisted of 114 men aged ≥50 years and a control group consisted of 423 healthy men matched by age frequency in Pengzhou, Sichuan Province, from April 2019 to October 2020, and the influencing factors of HIV infection were identified by unconditional stepwise logistic regression analysis.Results:Among the 114 cases, 63.16% (72/114) and 96.49% (110/114) of men had intimate social network size and sexual network size ≥4 people, which were higher than the control group of 23.40% (99/423) and 11.58% (49/423) (all P<0.05).The overlap of intimate social network and sexual network was 49.12% (56/114) in the case group, which was lower than that in the control group (82.27%, 348/423)( P<0.05). Logistic regression analysis showed that the size of the intimate social network ≥4 people ( OR=8.66, 95 %CI: 2.01-37.30), the size of the sexual network ≥4 people ( OR=1 121.11, 95% CI: 28.38-4 429.61), the material support from the first intimate network member ( OR=6.39, 95% CI: 1.03-39.75), and multiple sexual partners ( OR=55.50, 95% CI: 6.22-494.96) were the risk factors of HIV-infection in men aged ≥50 years. Receiving health education about AIDS ( OR=0.07, 95% CI: 0.01-0.37), high sexual satisfaction with the first sexual partner and good personal relationship ( OR=0.02, 95% CI: 0.01-0.59; OR=0.01, 95% CI: 0.01-0.26), and the overlap between intimate social network and sexual network ( OR=0.02, 95% CI: 0.01-0.38) were the protective factors of HIV-infection in men aged ≥50 years. Conclusions:The overlap of intimate social network and sexual network can reduce the risk of HIV-infection in men aged ≥50 years. It is important to help middle-aged and elderly men to build good and stable intimate social and sexual networks to meet their social communication and sex demands and prevent HIV infection by reducing high riak sexual behaviors.