dc.contributor.author
Gutiérrez, Lourdes
dc.contributor.author
Royuela, Ana
dc.contributor.author
Carcereny, Enric
dc.contributor.author
López-Castro, Rafael
dc.contributor.author
Rodríguez-Abreu, Delvys
dc.contributor.author
Massuti, Bartomeu
dc.contributor.author
González-Larriba, José Luis
dc.contributor.author
García-Campelo, Rosario
dc.contributor.author
Bosch Barrera, Joaquim
dc.contributor.author
Guirado, María
dc.contributor.author
Camps, Carlos
dc.contributor.author
Dómine, Manuel
dc.contributor.author
Bernabé, Reyes
dc.contributor.author
Casal, Joaquín
dc.contributor.author
Oramas, Juana
dc.contributor.author
Ortega, Ana Laura
dc.contributor.author
Sala, Mª Angeles
dc.contributor.author
Padilla, Airam
dc.contributor.author
Aguiar, David
dc.contributor.author
Juan-Vidal, Oscar
dc.contributor.author
Blanco, Remei
dc.contributor.author
Del Barco, Edel
dc.contributor.author
Martínez-Banaclocha, Natividad
dc.contributor.author
Benítez, Gretel
dc.contributor.author
De Vega, Blanca
dc.contributor.author
Hernández, Ainhoa
dc.contributor.author
Saigi, Maria
dc.contributor.author
Franco, Fernando
dc.contributor.author
Provencio, Mariano
dc.date.accessioned
2026-02-06T05:52:50Z
dc.date.available
2026-02-06T05:52:50Z
dc.date.issued
2021-08-31
dc.identifier
http://hdl.handle.net/10256/28256
dc.identifier.uri
https://hdl.handle.net/10256/28256
dc.description.abstract
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
dc.format
application/pdf
dc.relation
info:eu-repo/semantics/altIdentifier/doi/10.1186/s12885-021-08713-8
dc.relation
info:eu-repo/semantics/altIdentifier/issn/1471-2407
dc.relation
info:eu-repo/semantics/altIdentifier/eissn/1471-2407
dc.rights
Attribution 4.0 International (CC BY 4.0)
dc.rights
http://creativecommons.org/licenses/by/4.0/deed.ca
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Bmc Cancer, 2021, vol. 21, núm. 1, p. 977-977
dc.source
Articles publicats (IDIBGI)
dc.subject
Non-small cell lung cancer
dc.subject
Predictive modeling
dc.title
Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion