77 Implant loss and associated risk factors following implant-based breast reconstruction second limitation is the retrospective approach. Because of the retrospective approach, some data, such as the details and timing of radiotherapy, some comorbidities, and information about the decision-making process were lacking. Ultimately, the present results should be tested in a larger cohort to confirm the validity of this risk model. It is hypothesized that preservation of the pectoral fascia may influence the rates of implant loss as well. Removal of the pectoral fascia is routinely performed during oncological mastectomies and was performed preceding all implant-based breast reconstructions included in this study. Therefore, this hypothesis could not be tested in this study. A previous systematic review on this topic showed that preservation of the pectoral fascia may improve breast reconstructive outcomes by enhancing prosthesis coverage, thereby reducing implant extrusion rates and improving cosmetic outcomes. It may also decrease seroma formation, postoperative bleeding, and postoperative pain.19 The incidence of implant extrusion in mastectomies with pectoral fascia preservation varies in the literature, from 0.9% to 1.6%,20, 21 which is substantially lower than the incidence of implant loss in our study. However, current evidence on this topic is limited. For this reason, the effect of pectoral fascia preservation on complications, including implant loss, postoperative pain, and reconstructive outcomes, will be investigated by our study group. CONCLUSION Implant loss after implant-based breast reconstructions occurred in 11.8% of the study population. The following risk factors were significantly associated with implant loss: obesity, a bra cup size larger than C, active smoking, a nipplepreserving procedure, a DTI approach, and a lower oncological surgeon’s volume. A risk model was created based on the following risk factors: obesity, active smoking, a nipple-preserving procedure, and a DTI approach. This model showed that the predicted risk increased up to over 78.2% when the number of present risk factors accumulated. This risk model could be used to better inform patients and decrease the risk of implant extrusion by optimizing the surgical strategy in a personalized fashion. 5
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