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16-08-2023 | Mastectomy | Global Health Services Research

Oncologic Outcomes in Nipple-sparing Mastectomy with Immediate Reconstruction and Total Mastectomy with Immediate Reconstruction in Women with Breast Cancer: A Machine-Learning Analysis

Authors: Jun-Ho Cho, MD, Jung Mi Park, MS, Hyung Seok Park, MD, PhD, Hye Jin Kim, MD, Dong-Min Shin, MD, PhD, Jee Ye Kim, MD, PhD, Seho Park, MD, PhD, Seung Il Kim, MD, PhD, Byeong-Woo Park, MD, PhD

Published in: Annals of Surgical Oncology | Issue 12/2023

Abstract

Background

This study used a single-institution cohort, the Severance dataset, validated the results by using the surveillance, epidemiology, and end results (SEER) database, adjusted with propensity-score matching (PSM), and analyzed by using a machine learning method.

To determine whether the 5-year, disease-free survival (DFS) and overall survival (OS) of patients undergoing nipple-sparing mastectomy (NSM) with immediate breast reconstruction (IBR) are not inferior to those of women treated with total mastectomy/skin-sparing mastectomy (TM/SSM).

Methods

The Severance dataset enrolled 611 patients with early, invasive breast cancer from 2010 to 2017. The SEER dataset contained data for 485,245 patients undergoing TM and 14,770 patients undergoing NSM between 2000 and 2018. All patients underwent mastectomy and IBR. Intraoperative, frozen-section biopsy for the retro-areolar tissue was performed in the NSM group. The SEER dataset was extracted by using operation types, including TM/SSM and NSM. The primary outcome was DFS for the Severance dataset and OS for the SEER dataset. PSM analysis was applied. Survival outcomes were analyzed by using the Kaplan-Meier method and Cox proportional hazard (Cox PH) regression model. We implemented XGBSE to predict mortality with high accuracy and evaluated model prediction performance using a concordance index. The final model inspected the impact of relevant predictors on the model output using shapley additive explanation (SHAP) values.

Results

In the Severance dataset, 151 patients underwent NSM with IBR and 460 patients underwent TM/SSM with IBR. No significant differences were found between the groups. In multivariate analysis, NSM was not associated with reduced oncologic outcomes. The same results were observed in PSM analysis. In the SEER dataset, according to the SHAP values, the individual feature contribution suggested that AJCC stage ranks first. Analyses from the two datasets confirmed no impact on survival outcomes from the two surgical methods.

Conclusions

NSM with IBR is a safe and feasible procedure in terms of oncologic outcomes. Analysis using machine learning methods can be successfully applied to identify significant risk factors for oncologic outcomes.

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Title: Oncologic Outcomes in Nipple-sparing Mastectomy with Immediate Reconstruction and Total Mastectomy with Immediate Reconstruction in Women with Breast Cancer: A Machine-Learning Analysis
Authors: Jun-Ho Cho, MD
Jung Mi Park, MS
Hyung Seok Park, MD, PhD
Hye Jin Kim, MD
Dong-Min Shin, MD, PhD
Jee Ye Kim, MD, PhD
Seho Park, MD, PhD
Seung Il Kim, MD, PhD
Byeong-Woo Park, MD, PhD
Publication date: 16-08-2023
Publisher: Springer International Publishing
Keywords: Mastectomy
Breast Cancer
Breast Cancer
Published in: Annals of Surgical Oncology / Issue 12/2023
Print ISSN: 1068-9265
Electronic ISSN: 1534-4681
DOI: https://doi.org/10.1245/s10434-023-13963-w

2024 ASCO Annual Meeting

Springer Medicine

Oncologic Outcomes in Nipple-sparing Mastectomy with Immediate Reconstruction and Total Mastectomy with Immediate Reconstruction in Women with Breast Cancer: A Machine-Learning Analysis

Abstract

Background

Methods

Results

Conclusions

2024 ASCO Annual Meeting

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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