Predictors of postoperative lumpectomy size in breast-conserving surgery in breast cancer patients: a retrospective cohort study

Plast Reconstr Surg. 2023 Sep 26. doi: 10.1097/PRS.0000000000011085. Online ahead of print.

Abstract

Background: Oncoplastic reconstructive surgery as an extension of breast-conserving surgery leads to better aesthetic results, an increase in tumor-free margins, and a reduction of re-excision rates. However, oncologic resection is often more extensive than expected, sometimes resulting in the plastic surgeon deviating from the predetermined plan. For optimal planning of the reconstruction, it is mandatory to estimate volume defects after lumpectomy as accurately as possible. This study aims to find preoperative predictors of lumpectomy resection size.

Methods: All consecutive patients diagnosed with invasive breast carcinoma or carcinoma in situ and treated primarily with breast-conserving surgery between 2018 and 2020 at the University Medical Center Utrecht and Alexander Monro Hospital were included. Variables measured were patient characteristics and tumor characteristics. Data was analyzed in a multiple linear regression analysis.

Results: A total of 423 cases (410 patients) were included, with a median age of 58 (range 32-84) and a mean BMI of 25.0 (SD=9.3). The mean maximum radiological tumor diameter was 18.0 mm (SD=13.2), and the mean maximum lumpectomy diameter was 58.8 mm (SD=19.2). Multiple linear regression analysis found an explained variance of R 2 = 0.60 (p = < .00), corrected for operating surgeon. Significant predictors for postoperative lumpectomy size were BMI, breast size, and maximum preoperative radiological tumor diameter. Moreover, a predictive tool for lumpectomy size was developed and a web-based application was created on www.evidencio.com under the title ''Predicted lumpectomy size'', to facilitate the use of our tool in a clinical setting.

Conclusion: Postoperative lumpectomy size can be predicted with BMI, breast size and radiological tumor size. This model could be beneficial for (plastic) breast surgeons in planning reconstructions and to prepare and inform their patients more accurately.