Pittsburgh Classification and Treatment Algorithm for Idiopathic Granulomatous Mastitis: A Multicenter Cohort Study

Area of Science:

• Breast pathology
• Inflammatory breast disease
• Medical imaging

Background:

• Idiopathic granulomatous mastitis (IGM) is a rare inflammatory breast condition with no standardized treatment and unpredictable outcomes.
• Clinical and ultrasound findings are crucial for diagnosing and staging IGM.
• Existing treatment strategies for IGM lack standardization, leading to variable patient responses.

Purpose of the Study:

• To develop and evaluate the effectiveness of the Pittsburgh Classification and a corresponding treatment algorithm for idiopathic granulomatous mastitis (IGM).
• To stratify IGM severity using clinical and ultrasound findings.
• To improve treatment outcomes for patients with IGM.

Main Methods:

• Retrospective multicenter study of biopsy-proven IGM patients (2020-2025).
• Development of the Pittsburgh clinical (Type 1-5) and ultrasound (Type A-D) classifications for IGM severity.
• Assessment of treatment responses (CR, nCR, NR) based on the Pittsburgh treatment algorithm.

Main Results:

• Algorithm-concordant treatment was administered to 86.4% of patients, achieving high complete response (CR) rates (68.7%).
• Patients receiving algorithm-discordant treatment had significantly lower CR rates (21.1%) compared to those with CR (65.4%) (p<0.001).
• Multifocal disease and specific clinical types (e.g., Type 4) correlated with poorer outcomes (NR/nCR), while Type 1 IGM showed better response rates.

Conclusions:

• Concordance with the Pittsburgh IGM treatment algorithm significantly enhances complete response rates.
• IGM severity, multifocal disease, and clinical type are important prognostic factors.
• Further prospective global research is recommended to validate these findings.