Impact of Tissue Expander Surface Texture on Two-Stage Breast Reconstruction Outcomes: A Combined Analysis

Background:With ongoing investigations of the impact of device texturing on breast implant-associated anaplastic large-cell lymphoma (BIA-ALCL), studies have begun comparing complication profiles of tissue expanders. However, there is a paucity of timing and severity data of complications. The aim of this study was to provide a comparative survival analysis of postoperative complications between smooth (STEs) and textured tissue expanders (TTEs) in breast reconstruction. Methods:A single-institution experience with tissue expander breast reconstruction was reviewed for complications up to 1 year after second-stage reconstruction from 2014 to 2020. Demographics, comorbidities, operation-related variables, and complications were evaluated. Kaplan-Meier curves, Cox proportional hazard models, and a consensus-based ordinal logistic regression model were used to compare complication profiles. Results:Of 919 total patients, 600 (65.3%) received TTEs and 319 (34.7%) received STEs. There was increased risk of infection (P < 0.0001), seroma (P = 0.046), expander malposition (P < 0.0001), and wound dehiscence (P = 0.019) in STEs compared with TTEs. However, there was also a decreased risk of capsular contracture (P = 0.005) in STEs compared with TTEs. Failure of breast reconstruction (P < 0.001) and wound dehiscence (P = 0.018) occurred significantly earlier in STEs compared with TTEs. Predictors for significantly higher severity complications included the following: smooth tissue expander use (P = 0.007), shorter time to complication (P < 0.0001), higher body mass index (P = 0.005), smoking history (P = 0.025), and nipple-sparing mastectomy (P = 0.012). Conclusions:Differences in the timing and severity of complications contribute to the safety profiles of tissue expanders. STEs are associated with increased odds of higher severity and earlier complications. Therefore, tissue expander selection may depend on underlying risk factors and severity predictors.