Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After Surgery

ObjectiveThe study aimed to analyze the prognostic factors of patients with triple-negative (TN) metaplastic breast carcinoma (MpBC) after surgery and to construct a nomogram for forecasting the 3-, 5-, and 8-year overall survival (OS).MethodsA total of 998 patients extracted from the Surveillance,...

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Main Authors: Keying Zhu, Yuyuan Chen, Rong Guo, Lanyi Dai, Jiankui Wang, Yiyin Tang, Shaoqiang Zhou, Dedian Chen, Sheng Huang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.924342/full
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author Keying Zhu
Yuyuan Chen
Rong Guo
Lanyi Dai
Jiankui Wang
Yiyin Tang
Shaoqiang Zhou
Dedian Chen
Sheng Huang
author_facet Keying Zhu
Yuyuan Chen
Rong Guo
Lanyi Dai
Jiankui Wang
Yiyin Tang
Shaoqiang Zhou
Dedian Chen
Sheng Huang
author_sort Keying Zhu
collection DOAJ
description ObjectiveThe study aimed to analyze the prognostic factors of patients with triple-negative (TN) metaplastic breast carcinoma (MpBC) after surgery and to construct a nomogram for forecasting the 3-, 5-, and 8-year overall survival (OS).MethodsA total of 998 patients extracted from the Surveillance, Epidemiology, and End Results (SEER) database were assigned to either the training or validation group at random in a ratio of 7:3. The clinical characteristics of patients in the training and validation sets were compared, and multivariate Cox regression analysis was used to identify the independent risk variables for the OS of patients with TN MpBC after surgery. These selected parameters were estimated through the Kaplan–Meier (KM) curves using the log-rank test. The nomogram for predicting the OS was constructed and validated by performing the concordance index (C-index), receiver operating characteristics (ROC) curves with area under the receiver operating characteristic curves (AUC), calibration curves, and decision curve analyses (DCAs). Patients were then stratified as high-risk and low-risk, and KM curves were performed.ResultsMultivariate Cox regression analysis indicated that factors including age, marital status, clinical stage at diagnosis, chemotherapy, and regional node status were independent predictors of prognosis in patients with MpBC after surgery. Separate KM curves for the screened variables revealed the same statistical results as with Cox regression analysis. A prediction model was created and virtualized via nomogram based on these findings. For the training and validation cohorts, the C-index of the nomogram was 0.730 and 0.719, respectively. The AUC values of the 3-, 5-, and 8-year OS were 0.758, 0.757, and 0.785 in the training group, and 0.736, 0.735, and 0.736 for 3, 5, and 8 years in the validation group, respectively. The difference in the OS between the real observation and the forecast was quite constant according to the calibration curves. The generated clinical applicability of the nomogram was further demonstrated by the DCA analysis. In all the training and validation sets, the KM curves for the different risk subgroups revealed substantial differences in survival probabilities (P <0.001).ConclusionThe study showed a nomogram that was built from a parametric survival model based on the SEER database, which can be used to make an accurate prediction of the prognosis of patients with TN MpBC after surgery.
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spelling doaj.art-59ff7c56fc9e45099f23700da81c17d42022-12-22T00:34:22ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-06-011210.3389/fonc.2022.924342924342Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After SurgeryKeying ZhuYuyuan ChenRong GuoLanyi DaiJiankui WangYiyin TangShaoqiang ZhouDedian ChenSheng HuangObjectiveThe study aimed to analyze the prognostic factors of patients with triple-negative (TN) metaplastic breast carcinoma (MpBC) after surgery and to construct a nomogram for forecasting the 3-, 5-, and 8-year overall survival (OS).MethodsA total of 998 patients extracted from the Surveillance, Epidemiology, and End Results (SEER) database were assigned to either the training or validation group at random in a ratio of 7:3. The clinical characteristics of patients in the training and validation sets were compared, and multivariate Cox regression analysis was used to identify the independent risk variables for the OS of patients with TN MpBC after surgery. These selected parameters were estimated through the Kaplan–Meier (KM) curves using the log-rank test. The nomogram for predicting the OS was constructed and validated by performing the concordance index (C-index), receiver operating characteristics (ROC) curves with area under the receiver operating characteristic curves (AUC), calibration curves, and decision curve analyses (DCAs). Patients were then stratified as high-risk and low-risk, and KM curves were performed.ResultsMultivariate Cox regression analysis indicated that factors including age, marital status, clinical stage at diagnosis, chemotherapy, and regional node status were independent predictors of prognosis in patients with MpBC after surgery. Separate KM curves for the screened variables revealed the same statistical results as with Cox regression analysis. A prediction model was created and virtualized via nomogram based on these findings. For the training and validation cohorts, the C-index of the nomogram was 0.730 and 0.719, respectively. The AUC values of the 3-, 5-, and 8-year OS were 0.758, 0.757, and 0.785 in the training group, and 0.736, 0.735, and 0.736 for 3, 5, and 8 years in the validation group, respectively. The difference in the OS between the real observation and the forecast was quite constant according to the calibration curves. The generated clinical applicability of the nomogram was further demonstrated by the DCA analysis. In all the training and validation sets, the KM curves for the different risk subgroups revealed substantial differences in survival probabilities (P <0.001).ConclusionThe study showed a nomogram that was built from a parametric survival model based on the SEER database, which can be used to make an accurate prediction of the prognosis of patients with TN MpBC after surgery.https://www.frontiersin.org/articles/10.3389/fonc.2022.924342/fullmetaplastic breast canceroverall survivalnomogramprognostic modelsurgery
spellingShingle Keying Zhu
Yuyuan Chen
Rong Guo
Lanyi Dai
Jiankui Wang
Yiyin Tang
Shaoqiang Zhou
Dedian Chen
Sheng Huang
Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After Surgery
Frontiers in Oncology
metaplastic breast cancer
overall survival
nomogram
prognostic model
surgery
title Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After Surgery
title_full Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After Surgery
title_fullStr Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After Surgery
title_full_unstemmed Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After Surgery
title_short Prognostic Factor Analysis and Model Construction of Triple-Negative Metaplastic Breast Carcinoma After Surgery
title_sort prognostic factor analysis and model construction of triple negative metaplastic breast carcinoma after surgery
topic metaplastic breast cancer
overall survival
nomogram
prognostic model
surgery
url https://www.frontiersin.org/articles/10.3389/fonc.2022.924342/full
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AT jiankuiwang prognosticfactoranalysisandmodelconstructionoftriplenegativemetaplasticbreastcarcinomaaftersurgery
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