Publication: Prognostic model of long-term advanced stage (IIIB-IV) EGFR mutated non-small cell lung cancer (NSCLC) survivors using real-life data.
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Identifiers
Date
2021-08-31
Authors
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
Advisors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
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. 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. 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). 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.
Description
MeSH Terms
Aged
Biomarkers, Tumor
Cancer Survivors
Carcinoma, Non-Small-Cell Lung
Chemoradiotherapy
ErbB Receptors
Female
Follow-Up Studies
Humans
Lung Neoplasms
Male
Middle Aged
Models, Statistical
Mutation
Nomograms
Prognosis
Retrospective Studies
Survival Rate
Biomarkers, Tumor
Cancer Survivors
Carcinoma, Non-Small-Cell Lung
Chemoradiotherapy
ErbB Receptors
Female
Follow-Up Studies
Humans
Lung Neoplasms
Male
Middle Aged
Models, Statistical
Mutation
Nomograms
Prognosis
Retrospective Studies
Survival Rate
DeCS Terms
CIE Terms
Keywords
EGFR, Long survival, Nomogram, Non-small cell lung cancer, Predictive modeling