Risk Prediction of Implant Loss following Implant-Based Breast Reconstruction: A Population-Based Study
Yara L. Blok, Victor D. Plat, Jos A. van der Hage, Hein Putter, N.M.A. Krekel, Marc A.M. Mureau
Abstract
BACKGROUND: Implant loss following implant-based breast reconstruction (IBBR) is a serious complication, resulting in reoperations, patient suffering, and a significant decrease in quality of life. This study aimed to create a validated risk prediction model for implant loss after IBBR using perioperative risk factors. METHODS: Patients who had undergone either a 2-stage or a direct-to-implant postmastectomy IBBR were identified from the Dutch Breast Implant Registry. The cohort was divided into a training cohort (80%) and a validation cohort (20%). A multivariate logistic regression model was used to create a risk prediction model for implant loss in the training cohort, which was subsequently internally validated in the validation cohort. Implant loss was defined as explantation or replacement of the implant because of postoperative wound healing-related complications within 6 months after placement. RESULTS: A total of 5260 IBBRs were divided into a training cohort and a validation cohort. Implant loss occurred after 354 reconstructions (6.7%). The risk prediction model included 4 significant risk factors: body mass index, active smoking status, previous radiotherapy, and prepectoral placement. The model was able to predict an increasing probability of implant loss from 4.5% without any risk factors to 38.0% if 4 risk factors were present. The calibration plot showed good agreement. CONCLUSIONS: Nationwide population-based data were extracted from the Dutch Breast Implant Registry and used to create a risk assessment model for implant loss after IBBR. The model was accurately internally validated, making it applicable to general practice and a valuable aid in preoperative counseling of women who consider IBBR. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.