Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors.

By means of a mathematical score previously generated by discriminant analysis on 90 lung cancer patients, a new and larger group of 261 subjects [209 with non-small-cell lung cancer (NSCLC) and 52 with small-cell lung cancer (SCLC)] was analysed to confirm the ability of the method to distinguish b...

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Autores principales: Paone, G., De Angelis, G., Portalone, L., Greco, S., Giosué, S., Taglienti, A., Bisetti, A., Ameglio, F.
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group|1 1997
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2063371/
https://www.ncbi.nlm.nih.gov/pubmed/9020496
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author Paone, G.
De Angelis, G.
Portalone, L.
Greco, S.
Giosué, S.
Taglienti, A.
Bisetti, A.
Ameglio, F.
author_facet Paone, G.
De Angelis, G.
Portalone, L.
Greco, S.
Giosué, S.
Taglienti, A.
Bisetti, A.
Ameglio, F.
author_sort Paone, G.
collection PubMed
description By means of a mathematical score previously generated by discriminant analysis on 90 lung cancer patients, a new and larger group of 261 subjects [209 with non-small-cell lung cancer (NSCLC) and 52 with small-cell lung cancer (SCLC)] was analysed to confirm the ability of the method to distinguish between these two types of cancers. The score, which included the serum neuron-specific enolase (NSE) and CYFRA-21.1 levels, permitted correct classification of 93% of the patients. When the misclassifications were analysed in detail, the most frequent errors were associated with limited disease SCLC with low NSE levels and with advanced NSCLC with high NSE levels. This demonstrates the importance of the marker in correctly categorizing patients.
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spelling pubmed-20633712009-09-10 Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors. Paone, G. De Angelis, G. Portalone, L. Greco, S. Giosué, S. Taglienti, A. Bisetti, A. Ameglio, F. Br J Cancer Research Article By means of a mathematical score previously generated by discriminant analysis on 90 lung cancer patients, a new and larger group of 261 subjects [209 with non-small-cell lung cancer (NSCLC) and 52 with small-cell lung cancer (SCLC)] was analysed to confirm the ability of the method to distinguish between these two types of cancers. The score, which included the serum neuron-specific enolase (NSE) and CYFRA-21.1 levels, permitted correct classification of 93% of the patients. When the misclassifications were analysed in detail, the most frequent errors were associated with limited disease SCLC with low NSE levels and with advanced NSCLC with high NSE levels. This demonstrates the importance of the marker in correctly categorizing patients. Nature Publishing Group|1 1997 /pmc/articles/PMC2063371/ /pubmed/9020496 Text en https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Paone, G.
De Angelis, G.
Portalone, L.
Greco, S.
Giosué, S.
Taglienti, A.
Bisetti, A.
Ameglio, F.
Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors.
title Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors.
title_full Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors.
title_fullStr Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors.
title_full_unstemmed Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors.
title_short Validation of an algorithm able to differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) patients by means of a tumour marker panel: analysis of the errors.
title_sort validation of an algorithm able to differentiate small-cell lung cancer (sclc) from non-small-cell lung cancer (nsclc) patients by means of a tumour marker panel: analysis of the errors.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2063371/
https://www.ncbi.nlm.nih.gov/pubmed/9020496
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