# Determining the Epidemiologic Aspects and Treatment Results of Patients with Idiopathic Granulomatous Mastitis (IGM) Visiting Rheumatology and Surgery Clinics Using Fuzzy Artificial Intelligence, from 2015 to 2023: Treatment Results of Patients with Idiopathic Granulomatous Mastitis Using Fuzzy Artificial Intelligence

## TL;DR

This study uses fuzzy artificial intelligence to analyze treatment outcomes for granulomatous mastitis patients from 2015 to 2023, finding no significant link between treatment type and recovery.

## Contribution

The novel use of fuzzy AI to evaluate treatment effectiveness for granulomatous mastitis provides new insights into therapeutic approaches.

## Key findings

- No statistically significant relationship was found between treatment type and recovery outcomes.
- Complete recovery was higher in patients treated with oral steroids or steroid plus antibiotic combinations.
- AI analysis can improve decision-making for treatment effectiveness and patient outcomes.

## Abstract

Granulomatous mastitis (GM) is a benign inflammatory disease that affects the
breasts. From a pathological perspective, GM is characterized by chronic
granulomatous and necrosing lesions containing small abscesses and
inflammation of lobules. A variety of cures has been listed for this
condition, including follow-up without intervention, antibiotic therapy, and
consumption of corticosteroids, drainage, excisions, and mastectomy, but
still the best cure remains unknown. This study aims to determine the
epidemiologic aspects and treatment results of patients with idiopathic GM
visiting rheumatology and surgery clinics from 2015 to 2023.

This retrospective cohort study analyzed 39 patients with IGM visiting
rheumatology and surgery clinics from 2015 to 2023. Based on a study by
Kehribar et al., granulomatous mastitis has an annual prevalence of 2.4 in
100,000 cases and an incidence rate of 0.37% [1]. The required sample size
was calculated as 39 people. Data were collected using a census method,
categorized into types of treatment and response to treatment and patient
characteristics, with ethical approval obtained.

The study analyzed 39 patients with an average age of 34.48±5.47 years,
ranging from 22 to 45 years. Treatment strategies varied: oral steroids (25
patients), antibiotics (9 patients), surgical treatment (9 patients),
combined antibiotic and surgical treatment (4 patients), steroids and MTX (2
patients), and combined steroid and antibiotic treatment (15 patients).
Disease recurrence was noted in 15.4% of patients. Recovery outcomes were no
recovery in 7 patients, partial recovery in 15 patients, and complete
recovery in 17 patients.

The results found that the type of treatment has no statistically significant
relationship with the patient’s recovery process. Complete recovery was
higher in the oral steroid and steroid plus antibiotic treatment group
compared to other methods. Using AI to investigate and evaluate treatments
for granulomatous mastitis can provide valuable insights into the
effectiveness and safety of various therapeutic approaches. By leveraging
machine learning and AI techniques, researchers and clinicians can make more
informed decisions that ultimately improve patient outcomes.