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Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data
BACKGROUND: There is a lack of useful diagnostic tools to identify EGFR mutated NSCLC patients with long-term survival. This study develops a prognostic model using real world data to assist clinicians to predict survival beyond 24 months. METHODS: EGFR mutated stage IIIB and IV NSCLC patients diagn...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8406921/ https://www.ncbi.nlm.nih.gov/pubmed/34465283 http://dx.doi.org/10.1186/s12885-021-08713-8 |
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author | Gutiérrez, Lourdes Royuela, Ana Carcereny, Enric López-Castro, Rafael Rodríguez-Abreu, Delvys Massuti, Bartomeu González-Larriba, José Luis García-Campelo, Rosario Bosch-Barrera, Joaquim Guirado, María Camps, Carlos Dómine, Manuel Bernabé, Reyes Casal, Joaquín Oramas, Juana Ortega, Ana Laura Sala, Mª. Angeles Padilla, Airam Aguiar, David Juan-Vidal, Oscar Blanco, Remei del Barco, Edel Martínez-Banaclocha, Natividad Benítez, Gretel de Vega, Blanca Hernández, Ainhoa Saigi, Maria Franco, Fernando Provencio, Mariano |
author_facet | Gutiérrez, Lourdes Royuela, Ana Carcereny, Enric López-Castro, Rafael Rodríguez-Abreu, Delvys Massuti, Bartomeu González-Larriba, José Luis García-Campelo, Rosario Bosch-Barrera, Joaquim Guirado, María Camps, Carlos Dómine, Manuel Bernabé, Reyes Casal, Joaquín Oramas, Juana Ortega, Ana Laura Sala, Mª. Angeles Padilla, Airam Aguiar, David Juan-Vidal, Oscar Blanco, Remei del Barco, Edel Martínez-Banaclocha, Natividad Benítez, Gretel de Vega, Blanca Hernández, Ainhoa Saigi, Maria Franco, Fernando Provencio, Mariano |
author_sort | Gutiérrez, Lourdes |
collection | PubMed |
description | BACKGROUND: There is a lack of useful diagnostic tools to identify EGFR mutated NSCLC patients with long-term survival. This study develops a prognostic model using real world data to assist clinicians to predict survival beyond 24 months. METHODS: EGFR mutated stage IIIB and IV NSCLC patients diagnosed between January 2009 and December 2017 included in the Spanish Lung Cancer Group (SLCG) thoracic tumor registry. Long-term survival was defined as being alive 24 months after diagnosis. A multivariable prognostic model was carried out using binary logistic regression and internal validation through bootstrapping. A nomogram was developed to facilitate the interpretation and applicability of the model. RESULTS: 505 of the 961 EGFR mutated patients identified in the registry were included, with a median survival of 27.73 months. Factors associated with overall survival longer than 24 months were: being a woman (OR 1.78); absence of the exon 20 insertion mutation (OR 2.77); functional status (ECOG 0–1) (OR 4.92); absence of central nervous system metastases (OR 2.22), absence of liver metastases (OR 1.90) or adrenal involvement (OR 2.35) and low number of metastatic sites (OR 1.22). The model had a good internal validation with a calibration slope equal to 0.781 and discrimination (optimism corrected C-index 0.680). CONCLUSIONS: Survival greater than 24 months can be predicted from six pre-treatment clinicopathological variables. The model has a good discrimination ability. We hypothesized that this model could help the selection of the best treatment sequence in EGFR mutation NSCLC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08713-8. |
format | Online Article Text |
id | pubmed-8406921 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84069212021-08-31 Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data Gutiérrez, Lourdes Royuela, Ana Carcereny, Enric López-Castro, Rafael Rodríguez-Abreu, Delvys Massuti, Bartomeu González-Larriba, José Luis García-Campelo, Rosario Bosch-Barrera, Joaquim Guirado, María Camps, Carlos Dómine, Manuel Bernabé, Reyes Casal, Joaquín Oramas, Juana Ortega, Ana Laura Sala, Mª. Angeles Padilla, Airam Aguiar, David Juan-Vidal, Oscar Blanco, Remei del Barco, Edel Martínez-Banaclocha, Natividad Benítez, Gretel de Vega, Blanca Hernández, Ainhoa Saigi, Maria Franco, Fernando Provencio, Mariano BMC Cancer Research BACKGROUND: There is a lack of useful diagnostic tools to identify EGFR mutated NSCLC patients with long-term survival. This study develops a prognostic model using real world data to assist clinicians to predict survival beyond 24 months. METHODS: EGFR mutated stage IIIB and IV NSCLC patients diagnosed between January 2009 and December 2017 included in the Spanish Lung Cancer Group (SLCG) thoracic tumor registry. Long-term survival was defined as being alive 24 months after diagnosis. A multivariable prognostic model was carried out using binary logistic regression and internal validation through bootstrapping. A nomogram was developed to facilitate the interpretation and applicability of the model. RESULTS: 505 of the 961 EGFR mutated patients identified in the registry were included, with a median survival of 27.73 months. Factors associated with overall survival longer than 24 months were: being a woman (OR 1.78); absence of the exon 20 insertion mutation (OR 2.77); functional status (ECOG 0–1) (OR 4.92); absence of central nervous system metastases (OR 2.22), absence of liver metastases (OR 1.90) or adrenal involvement (OR 2.35) and low number of metastatic sites (OR 1.22). The model had a good internal validation with a calibration slope equal to 0.781 and discrimination (optimism corrected C-index 0.680). CONCLUSIONS: Survival greater than 24 months can be predicted from six pre-treatment clinicopathological variables. The model has a good discrimination ability. We hypothesized that this model could help the selection of the best treatment sequence in EGFR mutation NSCLC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08713-8. BioMed Central 2021-08-31 /pmc/articles/PMC8406921/ /pubmed/34465283 http://dx.doi.org/10.1186/s12885-021-08713-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Gutiérrez, Lourdes Royuela, Ana Carcereny, Enric López-Castro, Rafael Rodríguez-Abreu, Delvys Massuti, Bartomeu González-Larriba, José Luis García-Campelo, Rosario Bosch-Barrera, Joaquim Guirado, María Camps, Carlos Dómine, Manuel Bernabé, Reyes Casal, Joaquín Oramas, Juana Ortega, Ana Laura Sala, Mª. Angeles Padilla, Airam Aguiar, David Juan-Vidal, Oscar Blanco, Remei del Barco, Edel Martínez-Banaclocha, Natividad Benítez, Gretel de Vega, Blanca Hernández, Ainhoa Saigi, Maria Franco, Fernando Provencio, Mariano Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data |
title | Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data |
title_full | Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data |
title_fullStr | Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data |
title_full_unstemmed | Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data |
title_short | Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data |
title_sort | prognostic model of long-term advanced stage (iiib-iv) egfr mutated non-small cell lung cancer (nsclc) survivors using real-life data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8406921/ https://www.ncbi.nlm.nih.gov/pubmed/34465283 http://dx.doi.org/10.1186/s12885-021-08713-8 |
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