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Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis

BACKGROUND: Primary pulmonary mucoepidermoid carcinoma (PMEC) is an extremely rare malignancy. Its clinical characteristics and prognosis are not fully understood. This study evaluated clinical characteristics and prognostic factors of PMEC and established a nomogram to predict its 1-, 3-, 5- and 10...

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Autores principales: Qiu, Lingxiao, Song, Pan, Chen, Pingmei, Wang, Huaqi, Li, Fangfang, Shu, Mengxuan, Gong, Gen-cheng, Song, Xiangjin, Huang, Chun, Jia, Hongxia, Li, Nana, Zhang, Guojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973275/
https://www.ncbi.nlm.nih.gov/pubmed/33747918
http://dx.doi.org/10.3389/fonc.2021.601185
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author Qiu, Lingxiao
Song, Pan
Chen, Pingmei
Wang, Huaqi
Li, Fangfang
Shu, Mengxuan
Gong, Gen-cheng
Song, Xiangjin
Huang, Chun
Jia, Hongxia
Li, Nana
Zhang, Guojun
author_facet Qiu, Lingxiao
Song, Pan
Chen, Pingmei
Wang, Huaqi
Li, Fangfang
Shu, Mengxuan
Gong, Gen-cheng
Song, Xiangjin
Huang, Chun
Jia, Hongxia
Li, Nana
Zhang, Guojun
author_sort Qiu, Lingxiao
collection PubMed
description BACKGROUND: Primary pulmonary mucoepidermoid carcinoma (PMEC) is an extremely rare malignancy. Its clinical characteristics and prognosis are not fully understood. This study evaluated clinical characteristics and prognostic factors of PMEC and established a nomogram to predict its 1-, 3-, 5- and 10-year cancer-specific survival (CSS) rates. METHODS: In the Surveillance, Epidemiology, and End Results database from January 1, 2016 to December 31, 2016, patients pathologically diagnosed with PMEC were identified. Kaplan–Meier analysis and Cox regression were performed to evaluate the CSS stratified by different covariates. A predictive nomogram model was built and validated by the concordance index (C-index) and calibration curves. RESULTS: A total of 585 PMEC patients were identified. A total of 408 (70%) of patients were placed into the training cohort, and 177 (30%) patients were placed into the validation cohort. The 5- and 10-year CSS rates of stage I–II PMEC patients were 91.4 and 88.9, respectively. The 1-, 3- and 5-year CSS rates of stage III–IV PMEC were 56.5, 39.45, and 32.1%, respectively. Survival curves showed that older age, large tumor size, poor differentiation, and high TNM stage were associated with a significantly worse prognosis. CSS outcomes were significantly better in patients who received surgical treatments (surgical alone, surgery plus radiation and/or chemotherapy). Patients who received radiation and/or chemotherapy had the worst prognosis. Multivariate Cox results revealed that covariates, including age, tumor laterality, tumor sizes, pathological differentiation, lymph node metastasis, distant metastasis, TNM stage and therapy, were independent prognostic factors for PMEC. These factors were used to construct a nomogram. The C-index of the nomogram was 0.921. The calibration curve presented favorable consistency between the predicted CSS and actual observations. This nomogram was validated by the validation cohort. The C-index of the validation cohort was 0.968. CONCLUSION: Age, bilateral tumors, tumor size, pathological differentiation grade, lymph node metastasis, distant metastasis, TNM stage and therapy were independent prognostic factors of PMEC patients. The first nomogram for predicting the CSS of PMEC was built and validated, showing its potential value in practice.
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spelling pubmed-79732752021-03-20 Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis Qiu, Lingxiao Song, Pan Chen, Pingmei Wang, Huaqi Li, Fangfang Shu, Mengxuan Gong, Gen-cheng Song, Xiangjin Huang, Chun Jia, Hongxia Li, Nana Zhang, Guojun Front Oncol Oncology BACKGROUND: Primary pulmonary mucoepidermoid carcinoma (PMEC) is an extremely rare malignancy. Its clinical characteristics and prognosis are not fully understood. This study evaluated clinical characteristics and prognostic factors of PMEC and established a nomogram to predict its 1-, 3-, 5- and 10-year cancer-specific survival (CSS) rates. METHODS: In the Surveillance, Epidemiology, and End Results database from January 1, 2016 to December 31, 2016, patients pathologically diagnosed with PMEC were identified. Kaplan–Meier analysis and Cox regression were performed to evaluate the CSS stratified by different covariates. A predictive nomogram model was built and validated by the concordance index (C-index) and calibration curves. RESULTS: A total of 585 PMEC patients were identified. A total of 408 (70%) of patients were placed into the training cohort, and 177 (30%) patients were placed into the validation cohort. The 5- and 10-year CSS rates of stage I–II PMEC patients were 91.4 and 88.9, respectively. The 1-, 3- and 5-year CSS rates of stage III–IV PMEC were 56.5, 39.45, and 32.1%, respectively. Survival curves showed that older age, large tumor size, poor differentiation, and high TNM stage were associated with a significantly worse prognosis. CSS outcomes were significantly better in patients who received surgical treatments (surgical alone, surgery plus radiation and/or chemotherapy). Patients who received radiation and/or chemotherapy had the worst prognosis. Multivariate Cox results revealed that covariates, including age, tumor laterality, tumor sizes, pathological differentiation, lymph node metastasis, distant metastasis, TNM stage and therapy, were independent prognostic factors for PMEC. These factors were used to construct a nomogram. The C-index of the nomogram was 0.921. The calibration curve presented favorable consistency between the predicted CSS and actual observations. This nomogram was validated by the validation cohort. The C-index of the validation cohort was 0.968. CONCLUSION: Age, bilateral tumors, tumor size, pathological differentiation grade, lymph node metastasis, distant metastasis, TNM stage and therapy were independent prognostic factors of PMEC patients. The first nomogram for predicting the CSS of PMEC was built and validated, showing its potential value in practice. Frontiers Media S.A. 2021-03-05 /pmc/articles/PMC7973275/ /pubmed/33747918 http://dx.doi.org/10.3389/fonc.2021.601185 Text en Copyright © 2021 Qiu, Song, Chen, Wang, Li, Shu, Gong, Song, Huang, Jia, Li and Zhang http://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
Qiu, Lingxiao
Song, Pan
Chen, Pingmei
Wang, Huaqi
Li, Fangfang
Shu, Mengxuan
Gong, Gen-cheng
Song, Xiangjin
Huang, Chun
Jia, Hongxia
Li, Nana
Zhang, Guojun
Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis
title Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis
title_full Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis
title_fullStr Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis
title_full_unstemmed Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis
title_short Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis
title_sort clinical characteristics and prognosis of patients with pulmonary mucoepidermoid carcinoma: a seer-based analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973275/
https://www.ncbi.nlm.nih.gov/pubmed/33747918
http://dx.doi.org/10.3389/fonc.2021.601185
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