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Expander-phase morbidity in RFID-enabled two-stage breast reconstruction: A multicenter risk prediction model and
Alexandre Mendonça Munhoz1, Antonio Tejerina2, Angela Garcia Ruano3
1Plastic Surgery Division, Hospital Sírio-Libanês, São Paulo, Brazil.
Background:
Two-stage implant-based breast reconstruction (TSBR) using tissue expanders (TE) continues to be a standard procedure. Although TE incorporating non-metallic radiofrequency identification (RFID) ports have been introduced to address the limitations of metallic systems, clinical data are limited, and no validated models exist to guide individualized surgical planning.
Objective:
To develop a clinical prediction model and risk score for complications during RFID-TE reconstruction.
Methods:
We conducted a multicenter cohort study involving 356 patients undergoing TSBR with RFID-enabled TE. The primary endpoint was overall postoperative complications during the expander phase. Candidate predictors included demographic and treatment-related variables. Independent predictors were identified using multivariable logistic regression. Model performance was assessed using receiver operating characteristic (ROC) analysis and Hosmer-Lemeshow testing. Regression coefficients were converted into an integer-based score to improve risk stratification.
Results:
At a mean follow-up of 29.4±16.6 months, complications, most commonly seroma (7.8%), occurred in 21.6% of the patients. Independent predictors of complications included age >50 years (OR: 2.25 years), smoking (OR: 2.00), and radiation therapy (OR: 2.26), whereas use of the submuscular pocket was protective (OR: 0.44). These variables were incorporated into a 0-9 point risk score, which yielded an area under the ROC curve of 0.698 (95% CI: 0.628-0.768; p<0.001), with acceptable calibration (p=0.051). Risk stratification demonstrated complication rates of 8.7 and 39.0% in the low- and high-risk groups, respectively (p<0.001), enabling individualized estimation of expander-phase complication risk during preoperative planning.
Conclusion:
This study derives the first prediction model specific to RFID-TE reconstruction. By translating independent predictors into a preliminary risk score, the model provides a framework for individualized risk stratification and basis for future internal and external validation.
