Cargando…

Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study

BACKGROUND: Invasive micropapillary carcinoma (IMPC) is an unusual and distinct subtype of invasive breast tumor with high propensity for regional lymph node metastases. This study was to identify risk factors accounting for IMPC of the breast and to develop a nomogram to preoperatively predict the...

Descripción completa

Detalles Bibliográficos
Autores principales: Ye, Fu-Gui, Xia, Chen, Ma, Ding, Lin, Pei-Yang, Hu, Xin, Shao, Zhi-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6225632/
https://www.ncbi.nlm.nih.gov/pubmed/30409127
http://dx.doi.org/10.1186/s12885-018-4982-5
_version_ 1783369820628058112
author Ye, Fu-Gui
Xia, Chen
Ma, Ding
Lin, Pei-Yang
Hu, Xin
Shao, Zhi-Ming
author_facet Ye, Fu-Gui
Xia, Chen
Ma, Ding
Lin, Pei-Yang
Hu, Xin
Shao, Zhi-Ming
author_sort Ye, Fu-Gui
collection PubMed
description BACKGROUND: Invasive micropapillary carcinoma (IMPC) is an unusual and distinct subtype of invasive breast tumor with high propensity for regional lymph node metastases. This study was to identify risk factors accounting for IMPC of the breast and to develop a nomogram to preoperatively predict the probability of lymph node involvement. METHODS: A retrospective review of the clinical and pathology records was performed in patients diagnosed with IMPC between 2003 and 2014 from Surveillance, Epidemiology, and End Results (SEER) database. The cohort was divided into training and validation sets. Training set comprised patients diagnosed between 2003 and 2009, while validation set included patients diagnosed thereafter. A logistic regression model was used to construct the nomogram in the training set and then varified in the validation set. Nomogram performance was quantified with respect to discrimination and calibration using R 3.4.1 software. RESULTS: Overall, 1407 patients diagnosed with IMPC were enrolled, of which 527 in training set and 880 in validation set. Logistic regression analysis indicated larger lesions, younger age at diagnosis, black ethnic and lack of hormone receptor expression were significantly related to regional nodes involvement. The AUC of the nomogram was 0.735 (95% confidential interval (CI) 0.692 to 0.777), demonstrating a good prediction performance. Calibration curve for the nomogram was plotted and the slope was close to 1, which demonstrated excellent calibration of the nomogram. The performance of the nomogram was further validated in the validation set, with AUC of 0.748 (95% CI 0.701 to 0.767). CONCLUSIONS: The striking difference between IMPC and IDC remains the increased lymph node involvement in IMPC and therefore merits aggressive treatment. The nomogram based on the clinicalpathologic parameters was established, which could accurately preoperatively predict regional lymph node status. This nomogram would facilitate evaluating lymph node state preoperatively and thus treatment decision-making of individual patients.
format Online
Article
Text
id pubmed-6225632
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-62256322018-11-19 Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study Ye, Fu-Gui Xia, Chen Ma, Ding Lin, Pei-Yang Hu, Xin Shao, Zhi-Ming BMC Cancer Research Article BACKGROUND: Invasive micropapillary carcinoma (IMPC) is an unusual and distinct subtype of invasive breast tumor with high propensity for regional lymph node metastases. This study was to identify risk factors accounting for IMPC of the breast and to develop a nomogram to preoperatively predict the probability of lymph node involvement. METHODS: A retrospective review of the clinical and pathology records was performed in patients diagnosed with IMPC between 2003 and 2014 from Surveillance, Epidemiology, and End Results (SEER) database. The cohort was divided into training and validation sets. Training set comprised patients diagnosed between 2003 and 2009, while validation set included patients diagnosed thereafter. A logistic regression model was used to construct the nomogram in the training set and then varified in the validation set. Nomogram performance was quantified with respect to discrimination and calibration using R 3.4.1 software. RESULTS: Overall, 1407 patients diagnosed with IMPC were enrolled, of which 527 in training set and 880 in validation set. Logistic regression analysis indicated larger lesions, younger age at diagnosis, black ethnic and lack of hormone receptor expression were significantly related to regional nodes involvement. The AUC of the nomogram was 0.735 (95% confidential interval (CI) 0.692 to 0.777), demonstrating a good prediction performance. Calibration curve for the nomogram was plotted and the slope was close to 1, which demonstrated excellent calibration of the nomogram. The performance of the nomogram was further validated in the validation set, with AUC of 0.748 (95% CI 0.701 to 0.767). CONCLUSIONS: The striking difference between IMPC and IDC remains the increased lymph node involvement in IMPC and therefore merits aggressive treatment. The nomogram based on the clinicalpathologic parameters was established, which could accurately preoperatively predict regional lymph node status. This nomogram would facilitate evaluating lymph node state preoperatively and thus treatment decision-making of individual patients. BioMed Central 2018-11-08 /pmc/articles/PMC6225632/ /pubmed/30409127 http://dx.doi.org/10.1186/s12885-018-4982-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Ye, Fu-Gui
Xia, Chen
Ma, Ding
Lin, Pei-Yang
Hu, Xin
Shao, Zhi-Ming
Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study
title Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study
title_full Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study
title_fullStr Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study
title_full_unstemmed Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study
title_short Nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a SEER population-based study
title_sort nomogram for predicting preoperative lymph node involvement in patients with invasive micropapillary carcinoma of breast: a seer population-based study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6225632/
https://www.ncbi.nlm.nih.gov/pubmed/30409127
http://dx.doi.org/10.1186/s12885-018-4982-5
work_keys_str_mv AT yefugui nomogramforpredictingpreoperativelymphnodeinvolvementinpatientswithinvasivemicropapillarycarcinomaofbreastaseerpopulationbasedstudy
AT xiachen nomogramforpredictingpreoperativelymphnodeinvolvementinpatientswithinvasivemicropapillarycarcinomaofbreastaseerpopulationbasedstudy
AT mading nomogramforpredictingpreoperativelymphnodeinvolvementinpatientswithinvasivemicropapillarycarcinomaofbreastaseerpopulationbasedstudy
AT linpeiyang nomogramforpredictingpreoperativelymphnodeinvolvementinpatientswithinvasivemicropapillarycarcinomaofbreastaseerpopulationbasedstudy
AT huxin nomogramforpredictingpreoperativelymphnodeinvolvementinpatientswithinvasivemicropapillarycarcinomaofbreastaseerpopulationbasedstudy
AT shaozhiming nomogramforpredictingpreoperativelymphnodeinvolvementinpatientswithinvasivemicropapillarycarcinomaofbreastaseerpopulationbasedstudy