%0 Journal Article
%T Diagnosis of Non-small Cell Lung Cancer for Early Stage Asymptomatic Patients
%A ANDREW WACHTEL
%A CHERYLLE GOEBEL
%A CHRISTOPHER L. LOUDEN
%A OSITA ONUGHA
%A ROBERT Jr MCKENNA
%A THOMAS LONG
%J Archive of "Cancer Genomics & Proteomics".
%D 2019
%R 10.21873/cgp.20128
%X Background/Aim: In 2016 in the United States, 7 of 10 patients were estimated to die following lung cancer diagnosis. This is due to a lack of a reliable screening method that detects early-stage lung cancer. Our aim is to accurately detect early stage lung cancer using algorithms and protein biomarkers. Patients and Methods: A total of 1,479 human plasma samples were processed using a multiplex immunoassay platform. 82 biomarkers and 6 algorithms were explored. There were 351 NSCLC samples (90.3% Stage I, 2.3% Stage II, and 7.4% Stage III/IV). Results: We identified 33 protein biomarkers and developed a classifier using Random Forest. Our test detected early-stage Non-Small Cell Lung Cancer (NSCLC) with a 90% accuracy, 80% sensitivity, and 95% specificity in the validation set using the 33 markers. Conclusion: A specific, non-invasive, early-detection test, in combination with low-dose computed tomography, could increase survival rates and reduce false positives from screenings
%K Early stage lung cancer
%K biomarkers
%K proteomics
%K immunoassay
%K detection
%K diagnosis
%K non-small cell lung cancer
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609262/