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A novel nomogram and risk classification system for predicting overall survival in head and neck squamous cell cancer with distant metastasis at initial diagnosis

Introduction Head and neck squamous cell carcinoma (HNSCC) is one of the most invasive cancer types globally, and distant metastasis (DM) is associated with a poor prognosis. The objective of this study was designed to construct a novel nomogram and risk classification system to predict overall surv...

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Published in:European archives of oto-rhino-laryngology 2023-03, Vol.280 (3), p.1467-1478
Main Authors: Zhu, Run-Qiu, Zhang, Ya-Min, Luo, Xia-Yan, Shen, Wen-Yi, Zhu, Hui-Yong
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description Introduction Head and neck squamous cell carcinoma (HNSCC) is one of the most invasive cancer types globally, and distant metastasis (DM) is associated with a poor prognosis. The objective of this study was designed to construct a novel nomogram and risk classification system to predict overall survival (OS) in HNSCC patients presenting with DM at initial diagnosis. Methods HNSCC patients with initially diagnosed DM between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Firstly, all patients were randomly assigned to a training cohort and validation cohort (8:2), respectively. The Cox proportional hazards regression model was used to analyze the prognostic factors associated with OS. Then, the nomogram based on the prognostic factors and the predictive ability of the nomogram were assessed by the calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Finally, a risk classification system was established according to the nomogram scores. Results A total of 1240 patients initially diagnosed with HNSCC with DM were included, and the 6-, 12- and 18-month OS of HNSCC with DM were 62.7%, 40.8% and 30%, respectively. The independent prognostic factors for HNSCC patients with DM included age, marital status, primary site, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery, radiotherapy and chemotherapy. Based on the independent prognostic factors, a nomogram was constructed to predict OS in HNSCC patients with DM. The C-index values of the nomogram were 0.713 in the training cohort and 0.674 in the validation cohort, respectively. The calibration curves and DCA also indicated the good predictability of the nomogram. Finally, a risk classification system was built and it revealed a statistically significant difference among the three groups of patients according to the nomogram scores. Conclusions Factors associated with the overall survival of HNSCC patients with DM were found. According to the identified factors, we generated a nomogram and risk classification system to predict the OS of patients with initially diagnosed HNSCC with DM. The prognostic nomogram and risk classification system can help to assess survival time and provide guidance when making treatment decisions for HNSCC patients with DM.
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The objective of this study was designed to construct a novel nomogram and risk classification system to predict overall survival (OS) in HNSCC patients presenting with DM at initial diagnosis. Methods HNSCC patients with initially diagnosed DM between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Firstly, all patients were randomly assigned to a training cohort and validation cohort (8:2), respectively. The Cox proportional hazards regression model was used to analyze the prognostic factors associated with OS. Then, the nomogram based on the prognostic factors and the predictive ability of the nomogram were assessed by the calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Finally, a risk classification system was established according to the nomogram scores. Results A total of 1240 patients initially diagnosed with HNSCC with DM were included, and the 6-, 12- and 18-month OS of HNSCC with DM were 62.7%, 40.8% and 30%, respectively. The independent prognostic factors for HNSCC patients with DM included age, marital status, primary site, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery, radiotherapy and chemotherapy. Based on the independent prognostic factors, a nomogram was constructed to predict OS in HNSCC patients with DM. The C-index values of the nomogram were 0.713 in the training cohort and 0.674 in the validation cohort, respectively. The calibration curves and DCA also indicated the good predictability of the nomogram. Finally, a risk classification system was built and it revealed a statistically significant difference among the three groups of patients according to the nomogram scores. Conclusions Factors associated with the overall survival of HNSCC patients with DM were found. According to the identified factors, we generated a nomogram and risk classification system to predict the OS of patients with initially diagnosed HNSCC with DM. The prognostic nomogram and risk classification system can help to assess survival time and provide guidance when making treatment decisions for HNSCC patients with DM.</description><identifier>ISSN: 0937-4477</identifier><identifier>EISSN: 1434-4726</identifier><identifier>DOI: 10.1007/s00405-022-07716-w</identifier><identifier>PMID: 36316576</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Databases, Factual ; Head and Neck ; Head and Neck Neoplasms - diagnosis ; Head and Neck Neoplasms - therapy ; Head and Neck Surgery ; Humans ; Medicine ; Medicine &amp; Public Health ; Neoplasms, Squamous Cell ; Neurosurgery ; Nomograms ; Otorhinolaryngology ; SEER Program ; Squamous Cell Carcinoma of Head and Neck</subject><ispartof>European archives of oto-rhino-laryngology, 2023-03, Vol.280 (3), p.1467-1478</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2022. 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The objective of this study was designed to construct a novel nomogram and risk classification system to predict overall survival (OS) in HNSCC patients presenting with DM at initial diagnosis. Methods HNSCC patients with initially diagnosed DM between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Firstly, all patients were randomly assigned to a training cohort and validation cohort (8:2), respectively. The Cox proportional hazards regression model was used to analyze the prognostic factors associated with OS. Then, the nomogram based on the prognostic factors and the predictive ability of the nomogram were assessed by the calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Finally, a risk classification system was established according to the nomogram scores. Results A total of 1240 patients initially diagnosed with HNSCC with DM were included, and the 6-, 12- and 18-month OS of HNSCC with DM were 62.7%, 40.8% and 30%, respectively. The independent prognostic factors for HNSCC patients with DM included age, marital status, primary site, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery, radiotherapy and chemotherapy. Based on the independent prognostic factors, a nomogram was constructed to predict OS in HNSCC patients with DM. The C-index values of the nomogram were 0.713 in the training cohort and 0.674 in the validation cohort, respectively. The calibration curves and DCA also indicated the good predictability of the nomogram. Finally, a risk classification system was built and it revealed a statistically significant difference among the three groups of patients according to the nomogram scores. Conclusions Factors associated with the overall survival of HNSCC patients with DM were found. According to the identified factors, we generated a nomogram and risk classification system to predict the OS of patients with initially diagnosed HNSCC with DM. 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The objective of this study was designed to construct a novel nomogram and risk classification system to predict overall survival (OS) in HNSCC patients presenting with DM at initial diagnosis. Methods HNSCC patients with initially diagnosed DM between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Firstly, all patients were randomly assigned to a training cohort and validation cohort (8:2), respectively. The Cox proportional hazards regression model was used to analyze the prognostic factors associated with OS. Then, the nomogram based on the prognostic factors and the predictive ability of the nomogram were assessed by the calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Finally, a risk classification system was established according to the nomogram scores. Results A total of 1240 patients initially diagnosed with HNSCC with DM were included, and the 6-, 12- and 18-month OS of HNSCC with DM were 62.7%, 40.8% and 30%, respectively. The independent prognostic factors for HNSCC patients with DM included age, marital status, primary site, T stage, N stage, bone metastasis, brain metastasis, liver metastasis, lung metastasis, surgery, radiotherapy and chemotherapy. Based on the independent prognostic factors, a nomogram was constructed to predict OS in HNSCC patients with DM. The C-index values of the nomogram were 0.713 in the training cohort and 0.674 in the validation cohort, respectively. The calibration curves and DCA also indicated the good predictability of the nomogram. Finally, a risk classification system was built and it revealed a statistically significant difference among the three groups of patients according to the nomogram scores. Conclusions Factors associated with the overall survival of HNSCC patients with DM were found. According to the identified factors, we generated a nomogram and risk classification system to predict the OS of patients with initially diagnosed HNSCC with DM. The prognostic nomogram and risk classification system can help to assess survival time and provide guidance when making treatment decisions for HNSCC patients with DM.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>36316576</pmid><doi>10.1007/s00405-022-07716-w</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-9618-0103</orcidid><orcidid>https://orcid.org/0000-0003-0883-5355</orcidid></addata></record>
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subjects Databases, Factual
Head and Neck
Head and Neck Neoplasms - diagnosis
Head and Neck Neoplasms - therapy
Head and Neck Surgery
Humans
Medicine
Medicine & Public Health
Neoplasms, Squamous Cell
Neurosurgery
Nomograms
Otorhinolaryngology
SEER Program
Squamous Cell Carcinoma of Head and Neck
title A novel nomogram and risk classification system for predicting overall survival in head and neck squamous cell cancer with distant metastasis at initial diagnosis
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