2023 North America Conference on Lung Cancer (NACLC) - Posters and Abstracts-PP01.120 Patrick_Meyers_NACLC23

PP01.120 Patrick_Meyers_NACLC23_Abstract

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Lung cancer is a significant global health issue with low survival rates. Prognosis stratification is crucial for determining treatment intensity, and current treatments are largely based on the stage of the cancer. However, integrating biological markers could enhance personalized care. This study aims to determine if a panel of biomarkers can improve the prognostic stratification of lung cancer compared to clinical variables alone.<br /><br />The study enrolled 338 treatment-naïve patients and collected serum and chest CT scans from two centers in Nashville, Tennessee. Malignant diagnoses were confirmed through biopsy. Clinical variables such as age, sex, smoking status, cancer history, and nodule location were collected for each patient. Serum biomarkers including CA-125, CEA, HE4, ProGRP, Cyfra 21-1, NSE, CRP, SCC, and ferritin were assessed. Survival analysis categorized patients based on biomarker levels, and Kaplan-Meier plots and Cox Proportional-Hazard models were used to compare survival rates.<br /><br />Among the 224 patients in the final cohort, significant differences were observed between biomarker tertiles for CA-125, HE4, Cyfra 21-1, ProGRP, and CRP. A combination of seven biomarkers and clinical variables effectively differentiated between risk groups compared to clinical variables alone. Specifically, for stage I patients, the combination of biomarkers and clinical variables predicted lower survival.<br /><br />This study demonstrates the potential of a biomarker panel to improve lung cancer prognosis. However, more research is needed due to the small sample size. If further studies confirm these findings, a biomarker-driven approach could transform lung cancer care and enable more personalized treatments.

Keywords

lung cancer

global health

survival rates

prognosis stratification

treatment intensity

biological markers

clinical variables

serum biomarkers

Kaplan-Meier plots

Cox Proportional-Hazard models