Risk Factors and Risk Scoring Tool for Infection during Tissue Expansion in Tissue Expander and Implant Breast Reconstruction

Tissue expander and implant (TE/I) breast reconstruction has been increasing recently. In TE/I breast reconstruction, infection leads to reconstruction failure and is the most serious complication. The infection rate was reported to be higher during the tissue expander period than the implant period. However, few studies have investigated the risk factors for infection during tissue expansion following TE/I breast reconstruction. The goal of this study was to identify risk factors for infection during tissue expansion in TE/I breast reconstruction and to develop a simple risk scoring tool for infection that can be used for clinical application. In this retrospective cohort study, 981 patients who received TE/I breast reconstruction were surveyed and analyzed at one of the main clinics performing TE/I breast reconstruction in Japan. Numerous potential risk factors were collected from the clinical charts. Multiple logistic regression analyses were used to identify risk factors for infection. To develop a risk scoring tool, we converted the coefficients of the identified predictors estimated in the multiple logistic regression analyses into simplified risk scores. We assessed the tool discrimination by drawing a receiver operating characteristic curve and calculating the area under the curve. Infection was noted in 47 patients (4.79%) during tissue expansion. In multiple logistic regression analyses, diabetes, repeated expander insertions, larger expander size (≥400 cc), postoperative hormone therapy before silicone implant surgery, preoperative chemotherapy, and nipple-sparing mastectomy were identified as risk factors for infection during expansion. The area under the curve of the risk scoring tool for infection was 0.734 (95% CI: 0.662-0.807). We have revealed risk factors and proposed a risk scoring tool for infection during tissue expansion in TE/I breast reconstruction. This study may contribute to the prevention and prediction of infection.