Version 1
: Received: 11 October 2024 / Approved: 14 October 2024 / Online: 15 October 2024 (11:50:17 CEST)
How to cite:
Kim, S. Y.; Park, Y. S.; Kim, I. A.; Kim, H. J.; Lee, K. Y. Assessing the 9G Technology Blood Test for Predicting Lung Cancer in Patients with CT-Detected Lung Nodules: A Multicenter Clinical Trial. Preprints2024, 2024100991. https://doi.org/10.20944/preprints202410.0991.v1
Kim, S. Y.; Park, Y. S.; Kim, I. A.; Kim, H. J.; Lee, K. Y. Assessing the 9G Technology Blood Test for Predicting Lung Cancer in Patients with CT-Detected Lung Nodules: A Multicenter Clinical Trial. Preprints 2024, 2024100991. https://doi.org/10.20944/preprints202410.0991.v1
Kim, S. Y.; Park, Y. S.; Kim, I. A.; Kim, H. J.; Lee, K. Y. Assessing the 9G Technology Blood Test for Predicting Lung Cancer in Patients with CT-Detected Lung Nodules: A Multicenter Clinical Trial. Preprints2024, 2024100991. https://doi.org/10.20944/preprints202410.0991.v1
APA Style
Kim, S. Y., Park, Y. S., Kim, I. A., Kim, H. J., & Lee, K. Y. (2024). Assessing the 9G Technology Blood Test for Predicting Lung Cancer in Patients with CT-Detected Lung Nodules: A Multicenter Clinical Trial. Preprints. https://doi.org/10.20944/preprints202410.0991.v1
Chicago/Turabian Style
Kim, S. Y., Hee Joung Kim and Kye Young Lee. 2024 "Assessing the 9G Technology Blood Test for Predicting Lung Cancer in Patients with CT-Detected Lung Nodules: A Multicenter Clinical Trial" Preprints. https://doi.org/10.20944/preprints202410.0991.v1
Abstract
Lung nodules detected by chest computed tomography (CT) often require invasive biopsies for definitive diagnosis, leading to unnecessary procedures for benign lesions. A blood-based biomarker test that predicts lung cancer risk in CT-detected nodules could help stratify patients and direct invasive diagnostics toward high-risk individuals. In this multicenter, single-blinded clinical trial, we evaluated a test measuring plasma levels of p53, anti-p53 autoantibody, CYFRA 21-1, and anti-CYFRA 21-1 autoantibody in patients with CT-detected lung nodules. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated, and subgroup analyses by gender, age, and smoking status were performed. A total of 1,132 patients who had CT-detected lung nodules, including 885 lung cancer cases and 247 benign lesions, were enrolled from two academic hospitals in South Korea. The test demonstrated a sensitivity of 78.4% (95% CI: 75.7-81.1) and specificity of 93.1% (95% CI: 90.0-96.3) in predicting lung cancer in CT-detected nodules. The PPV was 97.6%, and the NPV was 54.6%. Performance was consistent across gender (sensitivity 79.3% in men and 76.8% in women) and age groups, with a specificity of 93.4% in men and 92.7% in women. Stage I lung cancer was detected with a sensitivity of 80.6%. The lung cancer test based on 9G technology presented here offers a non-invasive method for stratifying lung cancer risk in patients with CT-detected nodules. Its integration into clinical practice could reduce unnecessary interventions and foster earlier detection.
Keywords
lung nodule; chest CT; biomarker; 9G technology; lung cancer
Subject
Biology and Life Sciences, Biology and Biotechnology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
