Granulomatous mastitis: high surgical burden and limited microbiological yield in a 20-year multicenter retrospective cohort
Kian Chin, Thorhildur Halldorsdottir, Sarah Palm, Désirée Bourghardt Wiklund, Elisabeth Werner Rönnerman, Sanaa Abood, Catarina Ohrn, Eva Vikhe Patil, Slavica JanevaAbstract
Introduction
Granulomatous mastitis (GM) is a rare, benign inflammatory breast disease with a chronic and often relapsing course. Its heterogeneous presentation and lack of standardized treatment pose clinical challenges. This study aimed to evaluate the long-term clinical course of GM and inform evidence-based management.
Methods
This is a multicenter retrospective cohort study at two university hospitals in Sweden and one in Iceland. Histopathology databases were searched for inflammatory breast lesions between 2003–2023. Inclusion criteria were histopathological diagnosis of GM, recurrent disease, and absence of secondary causes. Disease severity was categorized as mild, moderate, or severe. Relevant clinical data were collected. Comparisons were performed using non-parametric statistics (P < 0.05).
Results
Of 315 patients identified, 39 (12%) met inclusion criteria. Infectious causes were excluded in 24 (61%), classified as idiopathic GM. Median age was 40 years (IQR 35–50), and 36% had risk factors. Imaging suggested malignancy in 34%. Disease was mild in 41%, moderate in 33%, and severe in 26%. Antibiotics were used in 77%, whereas corticosteroids (5%) and methotrexate (3%) were rarely used. Surgical debridement was required in 54%, with more procedures and follow-up visits in severe cases. After a median follow-up of 93 months, recurrence occurred in 21%. Disease duration increased with severity but was not statistically significant (P = 0.09).
Discussion
Greater disease severity was associated with increased surgical burden, but not with longer disease duration or recurrence. The low microbiological yield challenges the routine use of antibiotics. The rarity of GM underscores the need for robust data to guide evidence-based management.