Akademik Veri Yönetim Sistemi
BREAST CARE, sa.5, 2024 (SCI-Expanded)
Objective: The aim of the idiopathic granulomatous mastitis (IGM) consensus study was to evaluate the etiology, diagnostic steps, and differential diagnosis and propose a widely accepted clinical classification of this mysterious breast disease. Method: The organization of a national IGM consensus was decided by the joint evaluation of the Turkish Federation of Breast Diseases Societies, SENATURK, and the Society of Breast Surgery. First, a working group of 11 members was formed, and a survey and workshop were organized to reach a common consensus. The modified Delphi method was used in the consensus methodology. Voting rates of 80% and above were considered as acceptance. Results: The consensus was 45/50 (92%) that core needle biopsies are necessary for the diagnosis of IGM and 39/40 (97%) that a new clinical classification is needed. The proposed Turkish clinical classification of IGM was accepted by 94% in three rounds of voting. Conclusion: This disease should be considered etiologically idiopathic. Tissue diagnosis and pathological evaluation are recommended for treatment. The proposed IGM Turkey classification was strongly accepted. Idiopathic granulomatous mastitis is a highly heterogeneous group of diseases. There is ongoing controversy regarding the etiology, clinical classification, and treatment algorithm of the disease. There is no common terminological language for the clinical signs and symptoms of the disease. Treatment algorithms are diverse, and there is no standardization. Scientific comparisons cannot be made precisely due to the inclusion of heterogeneous groups in studies. Since there is no consensus on the severity of the disease, the types of treatment do not allow for comparisons between groups with the same clinical severity. These scientific limitations create difficulties in establishing national/international treatment algorithms or the acceptance of proposed algorithms. This consensus, prepared by our working group, defines a diagnostic algorithm for disease diagnosis and a terminological classification. The classification system, prepared according to disease severity, will be a pioneer in comparing patient groups and developing treatment algorithms.