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Nomogram for predicting the survival of patients with malignant melanoma: A population analysis
The aim of the current study was to develop and validate a nomogram based on a large population to estimate the 3- and 5-year survival rates of patients with malignant melanoma (MM). Patients were selected from the Surveillance, Epidemiology and End Results database and randomly divided into the tra...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6732986/ https://www.ncbi.nlm.nih.gov/pubmed/31516573 http://dx.doi.org/10.3892/ol.2019.10720 |
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author | Yang, Jin Pan, Zhenyu Zhou, Quan Liu, Qingqing Zhao, Fanfan Feng, Xiaojie Lyu, Jun |
author_facet | Yang, Jin Pan, Zhenyu Zhou, Quan Liu, Qingqing Zhao, Fanfan Feng, Xiaojie Lyu, Jun |
author_sort | Yang, Jin |
collection | PubMed |
description | The aim of the current study was to develop and validate a nomogram based on a large population to estimate the 3- and 5-year survival rates of patients with malignant melanoma (MM). Patients were selected from the Surveillance, Epidemiology and End Results database and randomly divided into the training and validation cohorts. A nomogram was developed, and was used to assess the accuracy of the model. Independent prognostic factors associated with overall survival (OS) rate were identified through multivariate analysis, and were included in the internal validation of the nomogram. The nomogram provided high C-indexes for the training cohort [area under the time-dependent receiver operating characteristic curve (AUC) of 0.877 for 3-year OS rate and 0.872 for 5-year OS rate] and the validation cohort (AUC of 0.880 for 3-year OS rate and 0.874 for 5-year OS rate), indicating that the model had good discrimination ability. Calibration plots showed that the predicted 3- and 5-year OS rates probabilities for the training and validation groups were almost identical to the actual observations. The 3- and 5-year decision curves indicated net benefits for both the training and validation cohorts. The nomogram may aid clinicians to provide more accurate prognosis prediction in patient consultations and more personalized postoperative management plans. |
format | Online Article Text |
id | pubmed-6732986 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-67329862019-09-12 Nomogram for predicting the survival of patients with malignant melanoma: A population analysis Yang, Jin Pan, Zhenyu Zhou, Quan Liu, Qingqing Zhao, Fanfan Feng, Xiaojie Lyu, Jun Oncol Lett Articles The aim of the current study was to develop and validate a nomogram based on a large population to estimate the 3- and 5-year survival rates of patients with malignant melanoma (MM). Patients were selected from the Surveillance, Epidemiology and End Results database and randomly divided into the training and validation cohorts. A nomogram was developed, and was used to assess the accuracy of the model. Independent prognostic factors associated with overall survival (OS) rate were identified through multivariate analysis, and were included in the internal validation of the nomogram. The nomogram provided high C-indexes for the training cohort [area under the time-dependent receiver operating characteristic curve (AUC) of 0.877 for 3-year OS rate and 0.872 for 5-year OS rate] and the validation cohort (AUC of 0.880 for 3-year OS rate and 0.874 for 5-year OS rate), indicating that the model had good discrimination ability. Calibration plots showed that the predicted 3- and 5-year OS rates probabilities for the training and validation groups were almost identical to the actual observations. The 3- and 5-year decision curves indicated net benefits for both the training and validation cohorts. The nomogram may aid clinicians to provide more accurate prognosis prediction in patient consultations and more personalized postoperative management plans. D.A. Spandidos 2019-10 2019-08-06 /pmc/articles/PMC6732986/ /pubmed/31516573 http://dx.doi.org/10.3892/ol.2019.10720 Text en Copyright: © Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Yang, Jin Pan, Zhenyu Zhou, Quan Liu, Qingqing Zhao, Fanfan Feng, Xiaojie Lyu, Jun Nomogram for predicting the survival of patients with malignant melanoma: A population analysis |
title | Nomogram for predicting the survival of patients with malignant melanoma: A population analysis |
title_full | Nomogram for predicting the survival of patients with malignant melanoma: A population analysis |
title_fullStr | Nomogram for predicting the survival of patients with malignant melanoma: A population analysis |
title_full_unstemmed | Nomogram for predicting the survival of patients with malignant melanoma: A population analysis |
title_short | Nomogram for predicting the survival of patients with malignant melanoma: A population analysis |
title_sort | nomogram for predicting the survival of patients with malignant melanoma: a population analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6732986/ https://www.ncbi.nlm.nih.gov/pubmed/31516573 http://dx.doi.org/10.3892/ol.2019.10720 |
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