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


Journal

Annals of surgical oncology
ISSN: 1534-4681
Titre abrégé: Ann Surg Oncol
Pays: United States
ID NLM: 9420840

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 14 02 2023
accepted: 03 07 2023
medline: 12 10 2023
pubmed: 17 8 2023
entrez: 16 8 2023
Statut: ppublish

Résumé

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). 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. 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. 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.

Sections du résumé

BACKGROUND 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 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 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 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.

Identifiants

pubmed: 37587360
doi: 10.1245/s10434-023-13963-w
pii: 10.1245/s10434-023-13963-w
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

7281-7290

Informations de copyright

© 2023. Society of Surgical Oncology.

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Auteurs

Jun-Ho Cho (JH)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Jung Mi Park (JM)

Department of Biostatistics and Computing, Graduate School, Yonsei University, Seoul, Korea.

Hyung Seok Park (HS)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea. hyungseokpark.md@gmail.com.

Hye Jin Kim (HJ)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Dong-Min Shin (DM)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Jee Ye Kim (JY)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Seho Park (S)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Seung Il Kim (SI)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

Byeong-Woo Park (BW)

Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.

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