External validation of the breast reconstruction risk assessment calculator.

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External validation of the breast reconstruction risk assessment calculator.

J Plast Reconstr Aesthet Surg. 2017 Apr 23;:

Authors: Khavanin N, Qiu CS, Mlodinow AS, Vu MM, Dorfman RG, Fine NA, Kim JYS

Abstract
INTRODUCTION: The Breast reconstruction Risk Assessment (BRA) Score estimates patient-specific risk for postsurgical complications using an individual's unique combination of preoperative variables. In this report, we externally validate the BRA Score models for surgical site infection, seroma, and explantation in a large sample of intra-institutional patients who underwent prosthetic breast reconstruction.
METHODS: We reviewed all initiated tissue expander/implant reconstructions by the senior authors from January 2004 to December 2015. BRA Score risk estimates were computed for each patient and compared against observed rates of complications. Hosmer-Lemeshow goodness-of-fit test, concordance statistic, and Brier score were used to assess the calibration, discrimination, and accuracy of the models, respectively.
RESULTS: Of the 1152 patients (1743 breasts) reviewed, 855 patients (1333 breasts) had complete data for BRA-score calculations and were included for analysis. Hosmer-Lemeshow tests for calibration demonstrated a good agreement between observed and predicted outcomes for surgical site infection (SSI) and seroma models (P-values of 0.33 and 0.16, respectively). In contrast, predicted rates of explantation deviated from observed rates (Hosmer-Lemeshow P-value of 0.04). C statistics demonstrated good discrimination for SSI, seroma, and explantation (0.73, 0.69, and 0.78, respectively).
CONCLUSIONS: In this external validation study, the BRA Score tissue expander/implant reconstruction models performed with generally good calibration, discrimination, and accuracy. Some weaknesses in certain models were identified as targets for future improvement. Taken together, these analyses validate the clinical utility of the BRA score risk models in predicting 30-day outcomes.

PMID: 28539245 [PubMed - as supplied by publisher]

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