Identification of Prognostic and Chemopredictive microRNAs for Non-Small-Cell Lung Cancer by Integrating SEER-Medicare Data.

This study developed a novel methodology to correlate genome-scale microRNA (miRNA) expression profiles in a lung squamous cell carcinoma (LUSC) cohort ( = 57) with Surveillance, Epidemiology, and End Results (SEER)-Medicare LUSC patients ( = 33,897) as a function of composite tumor progression indicators of T, N, and M cancer stage and tumor grade. The selected prognostic and chemopredictive miRNAs were extensively validated with miRNA expression profiles of non-small-cell lung cancer (NSCLC) patient samples collected from US hospitals ( = 156) and public consortia including NCI-60, The Cancer Genome Atlas (TCGA; = 1016), and Cancer Cell Line Encyclopedia (CCLE; = 117). Hsa-miR-142-3p was associated with good prognosis and chemosensitivity in all the studied datasets.

Combining COPD with clinical, pathological and demographic information refines prognosis and treatment response prediction of non-small cell lung cancer.

Background: Accurate assessment of a patient's risk of recurrence and treatment response is an important prerequisite of personalized therapy in lung cancer. This study extends a previously described non-small cell lung cancer prognostic model by the addition of chemotherapy and co-morbidities through the use of linked SEER-Medicare data.

Methodology/principal Findings: Data on 34,203 lung adenocarcinoma and 26,967 squamous cell lung carcinoma patients were used to determine the contribution of Chronic Obstructive Pulmonary Disease (COPD) to prognostication in 30 treatment combinations.

Association of arsenic exposure with lung cancer incidence rates in the United States.

Background: Although strong exposure to arsenic has been shown to be carcinogenic, its contribution to lung cancer incidence in the United States is not well characterized. We sought to determine if the low-level exposures to arsenic seen in the U.S.

Combining clinical, pathological, and demographic factors refines prognosis of lung cancer: a population-based study.

Background: In the treatment of lung cancer, an accurate estimation of patient clinical outcome is essential for choosing an appropriate course of therapy. It is important to develop a prognostic stratification model which combines clinical, pathological and demographic factors for individualized clinical decision making.

Methodology/principal Findings: A total of 234,412 patients diagnosed with adenocarcinomas or squamous cell carcinomas of the lung or bronchus between 1988 and 2006 were retrieved from the SEER database to construct a prognostic model.