CHEN Jin 1 , WU Ruiyang 1 , DAI Jiefang 2 , ZHANG Haiyan 1
  • 1. Department of Breast and Thyroid Surgery, Sichuan Provincial Hospital for Women and Children, Chengdu 610041, P. R. China;
  • 2. Department of Ultrasound, Sichuan Provincial Hospital for Women and Children, Chengdu 610041, P. R. China;
ZHANG Haiyan, Email: 446917513@qq.com
granulomatous mastitis; systemic inflammation index; recurrence; prediction model
10.7507/1007-9424.202412099
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Objective To construct a prediction model for the postoperative recurrence risk of granulomatous lobular mastitis (GM) based on multiple systemic inflammatory indicators and clinicopathologic characteristics, with the aim of guiding clinical treatment. Methods The GM patients who underwent lesion resection at Sichuan Provincial Hospital for Women and Children from January 2017 to March 2024 were retrospectively collected. The univariate and multivariate logistic regression analyses were used to screen the risk factors for recurrence after GM lesion resection, and a nomogram prediction model was constructed based on the risk factors. The test level was set at α=0.05. Results A total of 533 patients with GM were included in this study, of whom 118 cases (22.1%) developed postoperative recurrence. The results of multivariate analysis showed that the not taking oral bromocriptine, having microabscess formation in postoperative pathological examination, systemic immune inflammation index (SII) >789.0×109/L, and immunoglobulin E (IgE) >64.4 U/mL were the independent risk factors for recurrence after GM lesion resection. Based on the risk factors, the nomogram predicting recurrence risk was constructed. The area under the receiver operating characteristic curve (95%CI) was 0.913 (0.895, 0.932), and its sensitivity and specificity were 90.5% and 88.9%, respectively. The calibration curve showed that the probability of recurrence after GM lesion resection predicted by using the nomogram was highly consistent with the actual recurrence probability. The decision curve analysis showed that the nomogram had a good clinical net benefit. Conclusions The findings of this study suggest that close postoperative monitoring for recurrence is warranted in patients who did not receive oral bromocriptine treatment, presented with microabscess formation on pathological examination, and exhibited elevated SII and IgE level. The postoperative GM recurrence prediction nomogram model constructed based on risk factors demonstrates a good predictive performance, providing a valuable reference for early treatment and management strategies of GM.

Citation： CHEN Jin, WU Ruiyang, DAI Jiefang, ZHANG Haiyan. Development of recurrence risk prediction model for granulomatous mastitis after surgery: based on logistic regression analysis. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2025, 32(6): 763-768. doi: 10.7507/1007-9424.202412099 Copy

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