AptoDetect™-Lung Assay as a Blood-Based Predictor of Advanced-Stage Lung Cancer in Patients with Lung-RADS 3-4 Pulmonary Nodules: A Multicenter Prospective Cohort Study

초록

Background: The AptoDetect (TM)-Lung assay is an aptamer-based test designed for risk assessment in patients with pulmonary nodules, but its potential role in predicting lung cancer stage has not been evaluated. We investigated whether the assay could predict advanced-stage disease beyond conventional diagnostic modalities. Methods: This multicenter prospective cohort study enrolled 1672 patients with Lung-RADS 3-4 pulmonary nodules across ten university-affiliated hospitals in South Korea between June 2023 and December 2024. Among them, 934 patients with histologically confirmed lung cancer were retrospectively selected, and 852 patients were included in the final analysis after exclusions. The AptoDetect (TM)-Lung assay was performed before invasive diagnostic procedures. Results: Among the 852 patients, 450 (52.8%) had advanced-stage disease. The AptoDetect (TM)-Lung score was significantly higher in advanced-stage than in early-stage lung cancer (median, 6.2 vs. 2.8, p < 0.001). In a multivariable logistic regression analysis, a high AptoDetect (TM)-Lung score (>= 5) was independently associated with advanced disease (odds ratio 1.99, 95% confidence interval 1.35-2.95, p < 0.001). The AptoDetect (TM)-Lung assay showed moderate discrimination of advanced-stage disease (area under the curve [AUC] 0.696) and in non-small cell lung cancer (AUC 0.720), whereas its discriminative ability was limited in small cell lung cancer (AUC 0.561). A combined prediction model incorporating the AptoDetect (TM)-Lung assay, serum CEA, and radiologic findings demonstrated improved discriminative performance (AUC 0.821). Conclusions: The AptoDetect (TM)-Lung assay score was independently associated with advanced-stage lung cancer and could provide clinically useful information for early risk stratification before definitive diagnosis and staging are available.

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