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A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study
OBJECTIVE: Sinonasal melanoma (SMM) is a rare but aggressive malignancy with 5‐year overall survival (OS) rates below 40% in published studies. However, the clinicopathological predictors of the prognosis of SMM remain undefined. We aimed to establish a model to predict the survival outcomes of SMM....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764764/ https://www.ncbi.nlm.nih.gov/pubmed/36544933 http://dx.doi.org/10.1002/lio2.951 |
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author | Yang, Jingyi Song, Xiaole Lai, Yuting Liu, Quan Sun, Xicai Wang, Dehui Yu, Hongmeng |
author_facet | Yang, Jingyi Song, Xiaole Lai, Yuting Liu, Quan Sun, Xicai Wang, Dehui Yu, Hongmeng |
author_sort | Yang, Jingyi |
collection | PubMed |
description | OBJECTIVE: Sinonasal melanoma (SMM) is a rare but aggressive malignancy with 5‐year overall survival (OS) rates below 40% in published studies. However, the clinicopathological predictors of the prognosis of SMM remain undefined. We aimed to establish a model to predict the survival outcomes of SMM. METHODS: We searched the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with SMM between 1975 and 2016. Data on patient demographics, treatment modalities, and survival outcomes were retrieved. Risk factors for OS were evaluated by survival and Cox regression analyses. We also developed and validated a nomogram for OS, and compared its performance with that of conventional staging systems. RESULTS: Overall, 305 SMM patients were included in this population‐based study. Multivariate Cox regression showed that primary site, American Joint Committee on Cancer stage, radiotherapy, and surgery were significant risk factors for survival. A nomogram was established using the regression model. The C‐indices, areas under the receiver operating characteristic curves, calibration plots, and decision curve analysis demonstrated reliable performance of the nomogram. CONCLUSION: The nomogram predicting survival outcomes of SMM patients based on clinical information showed good discriminative ability and prognostic accuracy compared with conventional stage classifications. Our nomogram could be used to predict the survival probabilities for SMM patients at different timepoints. LEVEL OF EVIDENCE: 2b. |
format | Online Article Text |
id | pubmed-9764764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97647642022-12-20 A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study Yang, Jingyi Song, Xiaole Lai, Yuting Liu, Quan Sun, Xicai Wang, Dehui Yu, Hongmeng Laryngoscope Investig Otolaryngol Head and Neck, and Tumor Biology OBJECTIVE: Sinonasal melanoma (SMM) is a rare but aggressive malignancy with 5‐year overall survival (OS) rates below 40% in published studies. However, the clinicopathological predictors of the prognosis of SMM remain undefined. We aimed to establish a model to predict the survival outcomes of SMM. METHODS: We searched the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with SMM between 1975 and 2016. Data on patient demographics, treatment modalities, and survival outcomes were retrieved. Risk factors for OS were evaluated by survival and Cox regression analyses. We also developed and validated a nomogram for OS, and compared its performance with that of conventional staging systems. RESULTS: Overall, 305 SMM patients were included in this population‐based study. Multivariate Cox regression showed that primary site, American Joint Committee on Cancer stage, radiotherapy, and surgery were significant risk factors for survival. A nomogram was established using the regression model. The C‐indices, areas under the receiver operating characteristic curves, calibration plots, and decision curve analysis demonstrated reliable performance of the nomogram. CONCLUSION: The nomogram predicting survival outcomes of SMM patients based on clinical information showed good discriminative ability and prognostic accuracy compared with conventional stage classifications. Our nomogram could be used to predict the survival probabilities for SMM patients at different timepoints. LEVEL OF EVIDENCE: 2b. John Wiley & Sons, Inc. 2022-11-22 /pmc/articles/PMC9764764/ /pubmed/36544933 http://dx.doi.org/10.1002/lio2.951 Text en © 2022 The Authors. Laryngoscope Investigative Otolaryngology published by Wiley Periodicals LLC. on behalf of The Triological Society. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Head and Neck, and Tumor Biology Yang, Jingyi Song, Xiaole Lai, Yuting Liu, Quan Sun, Xicai Wang, Dehui Yu, Hongmeng A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study |
title | A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study |
title_full | A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study |
title_fullStr | A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study |
title_full_unstemmed | A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study |
title_short | A nomogram for predicting overall survival of patients with sinonasal melanoma: A population‐based study |
title_sort | nomogram for predicting overall survival of patients with sinonasal melanoma: a population‐based study |
topic | Head and Neck, and Tumor Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9764764/ https://www.ncbi.nlm.nih.gov/pubmed/36544933 http://dx.doi.org/10.1002/lio2.951 |
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