Background: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with advanced lung cancer (aLC). We assessed the external validity of our NLP-extracted data by comparing our findings to those reported in the literature.
View Article and Find Full Text PDFIntroduction: Real-world evidence is important in regulatory and funding decisions. Manual data extraction from electronic health records (EHRs) is time-consuming and challenging to maintain. Automated extraction using natural language processing (NLP) and artificial intelligence may facilitate this process.
View Article and Find Full Text PDFIntroduction: In addition to the higher prevalence of mutations found among lung cancer cases in East Asian patients, it is unclear whether there are differences in treatment outcomes by ethnicity-that is, East Asian versus non-East Asian.
Methods: Patients diagnosed with EGFR-mutant lung cancer between January 2004 and October 2014 at a single center were reviewed. Data captured included demographics, tumor and treatment information, and survival.
Background: Tobacco exposure contributes to over 80 % of lung cancer cases. Smoking is associated with programmed death-ligand 1 (PD-L1) tumor expression and better outcomes from anti-programmed cell death protein 1 (anti-PD-1) therapy in patients with advanced non-small cell lung cancer (NSCLC). PD-L1 tumor expression is now routinely used to predict benefit from anti-PD-1 therapy in patients with advanced NSCLC.
View Article and Find Full Text PDFIntroduction: Programmed death-1 (PD-1) axis inhibitors have become standard therapy in advanced non-small-cell lung cancer (NSCLC). Response might be delayed and pseudo-progression occasionally occurs in patients who eventually benefit from treatment. Additional markers beyond programmed death ligand 1 (PD-L1) expression are needed to assist in patient selection, response evaluation, and treatment decisions.
View Article and Find Full Text PDFBackground: Molecular testing in advanced lung cancer is standard in guiding treatment selection. However, population-wide implementation of testing remains a challenge. We developed a knowledge translation intervention to improve understanding among diagnostic specialists about molecular testing and appropriate diagnostic sampling in lung cancer.
View Article and Find Full Text PDFIntroduction: Lung cancer is associated with higher levels of symptom distress and unmet needs than other cancer types. We assessed changes in symptoms, function, understanding, and preferences of patients with advanced lung cancer over a 10-year period.
Materials And Methods: A 26-item self-administered questionnaire was used to assess symptom burden, functional impairment, knowledge of disease and treatment, and information preferences.
Objectives: Clinical trials of therapies for non-small cell lung cancer (NSCLC) are increasingly requiring mandatory tumor samples or research biopsies, both of which are potential barriers to trial participation. We assessed the impact of performance of research biopsies on the enrollment of patients with advanced NSCLC in clinical trials.
Methods: The cases of patients with advanced NSCLC who had been evaluated for clinical trials of systemic therapy at the Princess Margaret Cancer Centre from January 2007 to March 2015 were reviewed.