Publication: Risk Factors for Short-Term Lung Cancer Survival.
Loading...
Identifiers
Date
2021-02-01
Authors
Caballero-Vázquez, Alberto
Romero-Béjar, José Luis
Albendín-García, Luis
Suleiman-Martos, Nora
Gómez-Urquiza, José Luis
Cañadas, Gustavo Raúl
Cañadas-De la Fuente, Guillermo Arturo
Advisors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Lung cancer is typically diagnosed in an advanced phase of its natural history. Explanatory models based on epidemiological and clinical variables provide an approximation of patient survival less than one year using information extracted from the case history only, whereas models involving therapeutic variables must confirm that any treatment applied is worse than surgery in survival terms. Models for classifying less than one year survival for patients diagnosed with lung cancer which are able to identify risk factors and quantify their effect for prognosis are analyzed. Two stepwise binary logistic regression models, based on a retrospective study of 521 cases of patients diagnosed with lung cancer in the Interventional Pneumology Unit at the Hospital "Virgen de las Nieves", Granada, Spain. The first model included variables age, history of pulmonary neoplasm, tumor location, dyspnea, dysphonia, and chest pain. The independent risk factors age greater than 70 years, a peripheral location, dyspnea and dysphonia were significant. For the second model, treatments were also significant. Age, history of pulmonary neoplasm, tumor location, dyspnea, dysphonia, and chest pain are predictors for survival in patients diagnosed with lung cancer at the time of diagnosis. The treatment applied is significant for classifying less than one year survival time which confirms that any treatment is markedly inferior to surgery in terms of survival. This allows to consider applications of more or less aggressive treatments, anticipation of palliative cares or comfort measures, inclusion in clinical trials, etc.
Description
MeSH Terms
DeCS Terms
CIE Terms
Keywords
epidemiological risk factors, logistic regression, lung cancer, short-term survival, treatments