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Objective: This study aims to systematically evaluate the effectiveness and safety of acupuncture in treating mammary hyperplasia. Methods: A comprehensive search was conducted in various databases, including PubMed, Web of Science, Cochrane Library, Embase, SinoMed, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP Database, from their inception until July 2023. Only randomized controlled trials (RCTs) researching the use of acupuncture for mammary hyperplasia were included. Quality assessment and data analysis were performed using RevMan 5.3 software. Results: Eight RCTs, comprising 573 patients, were included in this analysis. The meta-analysis revealed that in the acupuncture group, the experimental group was better than the control group in improving breast pain, breast lump extent, and the texture of breast lump (P=0.0007, I2=61%; P=0.02, I2=0%; P=0.0002, I2=0%). We found that both could be improved, but after statistical analysis, there was no significant advantage in the acupuncture group compared with the patent Chinese medicine group (p>0.05). Conclusion: Acupuncture appears to be an effective and safe treatment for mammary hyperplasia, providing pain relief and reducing mass volume, texture, and extent. However, the insufficient quality of the available evidence indicates the need for further methodologically rigorous and convincingly designed studies to determine the efficacy and safety of acupuncture in the treatment of breast hyperplasia.
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Background: This study aimed to explore the risk factors and clinical characteristics of granulomatous mastitis (GM) using a case-control study and establish and validate a clinical prediction model (nomogram). Methods: This retrospective case-control study was conducted in three hospitals in China from June 2017 to December 2021. A total of 1634 GM patients and 186 healthy women during the same period were included and randomly divided into the modeling and validation groups in a 7:3 ratio. To identify the independent risk factors of GM, univariate and multivariate logistic analyses were conducted and used to develop a nomogram. The prediction model was internally and externally validated using the Bootstrap technique and validation cohort. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and calibration of the prediction model. Decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the clinical significance of the model. Results: The average age of GM patients was 33.14 years (mainly 20-40). The incidence was high within five years from delivery and mainly occurred in the unilateral breast. The majority of the patients exhibited local skin alterations, while some also presented with systemic symptoms. On multivariate logistic analysis, age, high prolactin level, sex hormone intake, breast trauma, nipple discharge or invagination, and depression were independent risk factors for GM. The mean area under the curve (AUC) in the modeling and validation groups were 0.899 and 0.889. The internal and external validation demonstrated the model's predictive ability and clinical value. Conclusion: Lactation-related factors are the main risk factors of GM, leading to milk stasis or increased ductal secretion. Meanwhile, hormone disorders could affect the secretion and expansion of mammary ducts. All these factors can obstruct or injure the duct, inducing inflammatory reactions and immune responses. Additionally, blunt trauma, depressed mood, and diet preference can accelerate the process. The nomogram can effectively predict the risk of GM.
ABSTRACT
Introduction: Granulomatous mastitis (GM) is a chronic inflammatory breast disease. In recent years, the role of Corynebacterium in GM onset has received more and more attention. This study aims to detect the dominant bacterium in GM patients and analyze the association between clinical characteristics and infectious factors. Methods: In this study, 88 samples from 44 GM patients, six acute lactation mastitis (ALM) patients, and 25 non-inflammatory breast disease (NIB) patients were divided into a GM pus group, a GM tissue group, an ALM pus group, and a NIB tissue group; then, 16S ribosomal DNA sequencing was used to explore their microbiota. The clinical data of all 44 GM patients were also retrospectively collected and analyzed to determine their relationship with infection. Results: The median age of the 44 GM patients was 33 years, and 88.6% of patients had primary-onset cases, while 11.4% were recurrences; additionally, 89.5% of patients were postpartum and 10.5% were nulliparous. The serum prolactin level was abnormal in nine patients (24.3%). Samples from 15 GM patients (34.1%) had a Corynebacterium abundance of >1% (1.08-80.08%), with eight (53.3%) displaying an abundance of >10%. Corynebacterium was the only genus with significant differences between the GM pus group and the other three groups (p < 0.05). Corynebacterium kroppenstedtii was the predominant Corynebacterium species. Among clinical characteristics, a statistical difference in breast abscess formation was observed according to Corynebacterium abundance in Corynebacterium-positive and- negative patients (p < 0.05). Discussion: This study explored the relationship between Corynebacterium infection and GM, compared the clinical characteristics between Corynebacterium-positive and- negative patients, and provided support for the role of Corynebacterium species-in particular, C. kroppenstedtii-in the pathogenesis of GM. The detection of Corynebacterium can predict GM onset, especially in patients with high prolactin levels or a history of recent lactation.
