Cargando…

Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery

BACKGROUND: The chances of second surgery due to positive margins in patients receiving breast-conversing surgery (BCS) were about 20-40%. This study aims to develop and validate a nomogram to predict the status of breast-conserving margins. METHODS: The database identified patients with core needle...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhao, Rong, Xing, Jun, Gao, Jinnan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133412/
https://www.ncbi.nlm.nih.gov/pubmed/35646633
http://dx.doi.org/10.3389/fonc.2022.875665
_version_ 1784713560911249408
author Zhao, Rong
Xing, Jun
Gao, Jinnan
author_facet Zhao, Rong
Xing, Jun
Gao, Jinnan
author_sort Zhao, Rong
collection PubMed
description BACKGROUND: The chances of second surgery due to positive margins in patients receiving breast-conversing surgery (BCS) were about 20-40%. This study aims to develop and validate a nomogram to predict the status of breast-conserving margins. METHODS: The database identified patients with core needle biopsy-proven ductal carcinoma in situ (DCIS) or invasive breast carcinoma who underwent BCS in Shanxi Bethune Hospital between January 1, 2015 and December 31, 2021 (n = 573). The patients were divided into two models: (1) The first model consists of 398 patients who underwent BCS between 2015 and 2019; (2) The validation model consists of 175 patients who underwent BCS between 2020 and 2021. The development of the nomogram was based on the findings of multivariate logistic regression analysis. Discrimination was assessed by computing the C-index. The Hosmer-Lemeshow goodness-of-fit test was used to validate the calibration performance. RESULTS: The final multivariate regression model was developed as a nomogram, including blood flow signals (OR = 2.88, p = 0.001), grade (OR = 2.46, p = 0.002), microcalcifications (OR = 2.39, p = 0.003), tumor size in ultrasound (OR = 2.12, p = 0.011) and cerbB-2 status (OR = 1.99, p = 0.042). C-indices were calculated of 0.71 (95% CI: 0.64-0.78) and 0.68 (95% CI: 0.59-0.78) for the modeling and the validation group, respectively. The calibration of the model was considered adequate in the validation group (p > 0.05). CONCLUSION: We developed a nomogram that enables the estimation of the preoperative risk of positive BCS margins. Our nomogram provides a valuable tool for identifying high-risk patients who might have to undergo a wider excision.
format Online
Article
Text
id pubmed-9133412
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-91334122022-05-27 Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery Zhao, Rong Xing, Jun Gao, Jinnan Front Oncol Oncology BACKGROUND: The chances of second surgery due to positive margins in patients receiving breast-conversing surgery (BCS) were about 20-40%. This study aims to develop and validate a nomogram to predict the status of breast-conserving margins. METHODS: The database identified patients with core needle biopsy-proven ductal carcinoma in situ (DCIS) or invasive breast carcinoma who underwent BCS in Shanxi Bethune Hospital between January 1, 2015 and December 31, 2021 (n = 573). The patients were divided into two models: (1) The first model consists of 398 patients who underwent BCS between 2015 and 2019; (2) The validation model consists of 175 patients who underwent BCS between 2020 and 2021. The development of the nomogram was based on the findings of multivariate logistic regression analysis. Discrimination was assessed by computing the C-index. The Hosmer-Lemeshow goodness-of-fit test was used to validate the calibration performance. RESULTS: The final multivariate regression model was developed as a nomogram, including blood flow signals (OR = 2.88, p = 0.001), grade (OR = 2.46, p = 0.002), microcalcifications (OR = 2.39, p = 0.003), tumor size in ultrasound (OR = 2.12, p = 0.011) and cerbB-2 status (OR = 1.99, p = 0.042). C-indices were calculated of 0.71 (95% CI: 0.64-0.78) and 0.68 (95% CI: 0.59-0.78) for the modeling and the validation group, respectively. The calibration of the model was considered adequate in the validation group (p > 0.05). CONCLUSION: We developed a nomogram that enables the estimation of the preoperative risk of positive BCS margins. Our nomogram provides a valuable tool for identifying high-risk patients who might have to undergo a wider excision. Frontiers Media S.A. 2022-05-12 /pmc/articles/PMC9133412/ /pubmed/35646633 http://dx.doi.org/10.3389/fonc.2022.875665 Text en Copyright © 2022 Zhao, Xing and Gao https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Zhao, Rong
Xing, Jun
Gao, Jinnan
Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery
title Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery
title_full Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery
title_fullStr Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery
title_full_unstemmed Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery
title_short Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery
title_sort development and validation of a prediction model for positive margins in breast-conserving surgery
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133412/
https://www.ncbi.nlm.nih.gov/pubmed/35646633
http://dx.doi.org/10.3389/fonc.2022.875665
work_keys_str_mv AT zhaorong developmentandvalidationofapredictionmodelforpositivemarginsinbreastconservingsurgery
AT xingjun developmentandvalidationofapredictionmodelforpositivemarginsinbreastconservingsurgery
AT gaojinnan developmentandvalidationofapredictionmodelforpositivemarginsinbreastconservingsurgery