ArticleRisk management and healthcare policy2023
Risk Factors for Granulomatous Mastitis and Establishment and Validation of a Clinical Prediction Model (Nomogram).
Article in Risk management and healthcare policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 13 citations in OpenAlex.
- Small-incision, point-by-point debridement combined with double-cannula negative-pressure irrigation and drainage for granulomatous mastitis: A single-center retrospective cohort study.The Journal of international medical research · 2026Article
- Oxidative Stress-Related DNA Damage in Patients with Idiopathic Granulomatous Mastitis: A Prospective Case-Control Study.Journal of clinical medicine · 2026Article
- Therapeutic effects of Tuolitounong decoction on pyroptosis in granulomatous lobular mastitis: evidence from in vitro and in vivo models.Journal of molecular histology · 2026Article
- Demographic characteristics and clinical analysis of patients with plasma cell mastitis: a single-center, retrospective, cross-sectional study.Gland surgery · 2026Article
- Granulomatous mastitis: from localized inflammation to systemic immune-mediated disorder.Frontiers in medicine · 2026Review
- Cystic Neutrophilic Granulomatous Mastitis in Accessory Breast Tissue: A Case Report.International journal of women's health · 2026Article
- From hypothesis to robust evidence in a nationwide multicenter case-control study on 1490 women: milk stasis and idiopathic granulomatous mastitis.Scientific reports · 2025Article
- Analysis of risk factors associated with recurrence of granulomatous lobular mastitis and establishment of a prediction model.Discover oncology · 2025Article
- Letter to the editor: Reflections on idiopathic granulomatous mastitis.Clinical rheumatology · 2025Article
- Bilateral granulomatous mastitis associated with ductoscopy.Gland surgery · 2025Article
- Recurrent Nipple Duct Obstruction in Two Breastfeeding Patients: A Case Report and Discussion of the Underlying Pathophysiology.Journal of mammary gland biology and neoplasia · 2025Article
- Treatment of idiopathic granulomatous mastitis: a retrospective case series.Rheumatology international · 2025Article
- Single-cell RNA sequencing analysis reveals cell landscape and gene signatures associated with granulomatous lobular mastitis.Frontiers in immunology · 2025Article
- Exploring the interplay of prolactin and bromocriptine on serum markers in granulomatous lobular mastitis.Frontiers in immunology · 2025Article
- Development and Validation of a Nomogram Model for Accurately Predicting Depression in Maintenance Hemodialysis Patients: A Multicenter Cross-Sectional Study in China.Risk management and healthcare policy · 2024Article
- Clinical review and drug sensitivity test ofFrontiers in microbiology · 2024Article
- Immune Markers and Inflammatory Cytokines in Granulomatous Lobular Mastitis: A Case-Control Study.Journal of inflammation research · 2024Article
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Authors and funding
11 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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