WCLC 2025 - Posters & ePosters-EP.06.71 Clinical Application of Expert Software Based on Tumor Biomarkers to Stratify Lc-Risk in a Hospital Thoracic Tumor Committee

EP.06.71 Clinical Application of Expert Software Based on Tumor Biomarkers to Stratify Lc-Risk in a Hospital Thoracic Tumor Committee

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This study evaluates the clinical application of the expert software “CLAUDIA” that uses tumor biomarker (TB) panels combined with clinical and computed tomography (CT) data to stratify lung cancer (LC) risk in patients assessed by a hospital Thoracic Tumor Committee. Lung cancer causes 1.8 million deaths annually, and although CT imaging is commonly used, it is costly, resource-intensive, and prone to false positives, particularly due to indeterminate nodules. Tumor biomarkers offer a cheaper, readily available diagnostic alternative, and their combined use enhances diagnostic accuracy.<br /><br />CLAUDIA software analyzes six biomarkers—CEA, CA 15-3, SCC-Ag, CYFRA 21-1, NSE, and ProGRP—considering clinical variables and CT data to classify patients into high, moderate, or low LC risk groups. The study was prospective, conducted at Macarena University Hospital in 2023, including all patients reviewed for suspected lung cancer. Serum TB concentrations were measured by electrochemiluminescent assays and interpreted by CLAUDIA, which was trained on over 5,000 cases.<br /><br />Results showed the software achieved an overall diagnostic accuracy of 89.57%, with sensitivity at 91%, specificity at 84.6%, positive predictive value of 95.3%, and negative predictive value of 73.3%. Among moderate-risk cases, some had cancer upon follow-up, supporting reanalysis in these groups. Furthermore, CLAUDIA accurately predicted lung cancer histological subtypes (small-cell vs. non-small-cell) with 99% success.<br /><br />In conclusion, the integration of a six-tumor biomarker panel with CLAUDIA software significantly improves lung cancer risk stratification and diagnostic accuracy, aiding rapid decision-making and patient management. This tool holds promise as a cost-effective, accessible adjunct in lung cancer diagnosis, especially in settings like Rapid Diagnostic Units, potentially optimizing resource use and improving patient outcomes.

Asset Subtitle

Antonio Barco Sánchez

Meta Tag

Speaker Antonio Barco Sánchez

Topic Pathology and Biomarkers

Keywords

CLAUDIA software

lung cancer risk stratification

tumor biomarkers

computed tomography

diagnostic accuracy

CEA biomarker

electrochemiluminescent assays

small-cell lung cancer

non-small-cell lung cancer

Rapid Diagnostic Units