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Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors
Despite a considerable expansion in the present therapeutic repertoire for other malignancy managements, mortality from head and neck cancer (HNC) has not significantly improved in recent decades. Moreover, the second primary cancer (SPC) diagnoses increased in patients with HNC, but studies providi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657249/ https://www.ncbi.nlm.nih.gov/pubmed/34886225 http://dx.doi.org/10.3390/ijerph182312499 |
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author | Chang, Chi-Chang Huang, Tse-Hung Shueng, Pei-Wei Chen, Ssu-Han Chen, Chun-Chia Lu, Chi-Jie Tseng, Yi-Ju |
author_facet | Chang, Chi-Chang Huang, Tse-Hung Shueng, Pei-Wei Chen, Ssu-Han Chen, Chun-Chia Lu, Chi-Jie Tseng, Yi-Ju |
author_sort | Chang, Chi-Chang |
collection | PubMed |
description | Despite a considerable expansion in the present therapeutic repertoire for other malignancy managements, mortality from head and neck cancer (HNC) has not significantly improved in recent decades. Moreover, the second primary cancer (SPC) diagnoses increased in patients with HNC, but studies providing evidence to support SPCs prediction in HNC are lacking. Several base classifiers are integrated forming an ensemble meta-classifier using a stacked ensemble method to predict SPCs and find out relevant risk features in patients with HNC. The balanced accuracy and area under the curve (AUC) are over 0.761 and 0.847, with an approximately 2% and 3% increase, respectively, compared to the best individual base classifier. Our study found the top six ensemble risk features, such as body mass index, primary site of HNC, clinical nodal (N) status, primary site surgical margins, sex, and pathologic nodal (N) status. This will help clinicians screen HNC survivors before SPCs occur. |
format | Online Article Text |
id | pubmed-8657249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86572492021-12-10 Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors Chang, Chi-Chang Huang, Tse-Hung Shueng, Pei-Wei Chen, Ssu-Han Chen, Chun-Chia Lu, Chi-Jie Tseng, Yi-Ju Int J Environ Res Public Health Article Despite a considerable expansion in the present therapeutic repertoire for other malignancy managements, mortality from head and neck cancer (HNC) has not significantly improved in recent decades. Moreover, the second primary cancer (SPC) diagnoses increased in patients with HNC, but studies providing evidence to support SPCs prediction in HNC are lacking. Several base classifiers are integrated forming an ensemble meta-classifier using a stacked ensemble method to predict SPCs and find out relevant risk features in patients with HNC. The balanced accuracy and area under the curve (AUC) are over 0.761 and 0.847, with an approximately 2% and 3% increase, respectively, compared to the best individual base classifier. Our study found the top six ensemble risk features, such as body mass index, primary site of HNC, clinical nodal (N) status, primary site surgical margins, sex, and pathologic nodal (N) status. This will help clinicians screen HNC survivors before SPCs occur. MDPI 2021-11-27 /pmc/articles/PMC8657249/ /pubmed/34886225 http://dx.doi.org/10.3390/ijerph182312499 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chang, Chi-Chang Huang, Tse-Hung Shueng, Pei-Wei Chen, Ssu-Han Chen, Chun-Chia Lu, Chi-Jie Tseng, Yi-Ju Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors |
title | Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors |
title_full | Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors |
title_fullStr | Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors |
title_full_unstemmed | Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors |
title_short | Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors |
title_sort | developing a stacked ensemble-based classification scheme to predict second primary cancers in head and neck cancer survivors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657249/ https://www.ncbi.nlm.nih.gov/pubmed/34886225 http://dx.doi.org/10.3390/ijerph182312499 |
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