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Risk factor analysis and development of a nomogram prediction model for Plasma Cell Mastitis

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  • Yiming Sun
  • Feng Zhang
  • Xiaowen Ma
  • Wenhui Wang
  • Ruonan Xu

Abstract

Background and objective: The risk factors for plasma cell mastitis (PCM) remain unclear. Understanding and mitigating these factors to prevent PCM before its onset has become a significant concern. This study identifies PCM risk factors, develops a predictive nomogram, and offers insights for targeted prevention and awareness in high-risk groups. Methods: We retrospectively analyzed the clinical data of 82 patients diagnosed with PCM at Hangzhou Women’s Hospital’s Breast Surgery Department from 01/01/2019 to 01/01/2022. A control group was randomly selected, consisting of 82 healthy women aged between 20–60 years who had undergone routine health check-ups during the same period. Using SPSS 26.0 software for univariate analysis, significant risk factors for PCM were identified. R software was used for multivariate logistic regression analysis, and a nomogram prediction model for the risk of developing PCM was established. Results: The average age of patients in the study group was 32.37 ± 6.64 years, the control group was 29.54 ± 5.33 years, with no statistically significant difference between the groups (P = 0.176). The onset time after childbirth or miscarriage was 3.37 ± 1.91 years. Univariate analysis revealed significant differences in BMI, nipple retraction, number of pregnancies, recent trauma history, and hyperlipidemia (P

Suggested Citation

  • Yiming Sun & Feng Zhang & Xiaowen Ma & Wenhui Wang & Ruonan Xu, 2025. "Risk factor analysis and development of a nomogram prediction model for Plasma Cell Mastitis," PLOS ONE, Public Library of Science, vol. 20(12), pages 1-15, December.
    • Handle: RePEc:plo:pone00:0338711
    DOI: 10.1371/journal.pone.0338711
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