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1.
Front Pharmacol ; 15: 1406862, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-39156102

RESUMO

Background: Breast cancer lung metastasis occurs at a high rate and at an early stage, and is the leading cause of death in breast cancer patients. The aim of this study was to investigate the effect of Ru'ai Shuhou Recipe (RSR) intervention on the occurrence of recurrent metastases, especially lung metastases, in postoperative patients with breast cancer. Materials and Methods: A retrospective cohort study was implemented at Shuguang Hospital of Shanghai University of Traditional Chinese Medicine in China between January 2014 to January 2019. Female patients were included according to the propensity score matching (PSM) method and balanced on the basis of general and clinical information such as age, body mass index, neo-adjuvant therapy, and surgical approach. Patients with pathological diagnosis of breast cancer were included in this study. Breast cancer patients were divided into exposed and non-exposed groups according to whether they took RSR-based botanical drugs after surgery. Kaplan-Meier survival analysis and Cox survival analysis to explore the relationship between RSR and 5-year disease-free survival and incidence of lung metastases in breast cancer patients after surgery. Results: 360 female patients were assessed and 190 patients were included in the study after PSM (95 in each of the exposed and non-exposed groups). Of the 190 patients after PSM, 55.79% were over 50 years of age. The mean follow-up time was 60.55 ± 14.82 months in the exposed group and 57.12 ± 16.37 months in the non-exposed group. There was no significant baseline characteristics difference between two groups. Kaplan-Meier analysis showed that the 5-year incidence of lung metastases was significantly lower in the exposed group, and the disease-free survival of patients was significantly longer. Cox univariate and multivariate analysis showed that neoadjuvant chemotherapy and lymph node metastasis were independent risk factors for the development of breast cancer lung metastasis, with risk ratios of 17.188 and 5.812, while RSR treatment was an independent protective factor against the development of breast cancer lung metastasis, with a risk ratio of 0.290. Conclusion: Standard biomedical treatment combined with RSR intervention can better prevent breast cancer recurrence and metastasis, reduce the incidence of lung metastasis in patients, and improve long-term prognosis.

2.
J Inflamm Res ; 17: 553-564, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38323114

RESUMO

Background: Granulomatous lobular mastitis (GLM) is a chronic inflammatory breast disease, and abscess formation is a common complication of GLM. The process of abscess formation is accompanied by changes in multiple inflammatory markers. The present study aimed to construct a diagnosis model for the early of GLM abscess formation based on multiple inflammatory parameters. Methods: Based on the presence or absence of abscess formation on breast magnetic resonance imaging (MRI), 126 patients with GLM were categorised into an abscess group (85 patients) and a non-abscess group (41 patients). Demographic characteristics and the related laboratory results for the 9 inflammatory markers were collected. Logistics univariate analysis and collinearity test were used for selecting independent variables. A regression model to predict abscess formation was constructed using Logistics multivariate analysis. Results: The univariate and multivariate analysis showed that the N, ESR, IL-4, IL-10 and INF-α were independent diagnostic factors of abscess formation in GLM (P<0. 05). The nomogram was drawn on the basis of the logistics regression model. The area under the curve (AUC) of the model was 0.890, which was significantly better than that of a single indicator and the sensitivity and specificity of the model were high (81.2% and 85.40%, respectively). These results predicted by the model were highly consistent with the actual diagnostic results. The results of this calibration curve indicated that the model had a good value and stability in predicting abscess formation in GLM. The decision curve analysis (DCA) demonstrated a satisfactory positive net benefit of the model. Conclusion: A predictive model for abscess formation in GLM based on inflammatory markers was constructed in our study, which may provide a new strategy for early diagnosis and treatment of the abscess stage of GLM.

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