Predictive modeling of peripheral blood EGFR positivity in patients with advanced primary non-small cell lung cancer

Lung cancer is the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of cases. Epidermal growth factor receptor (EGFR) mutations are the most prevalent driver alterations in NSCLC, and tyrosine kinase inhibitors (TKIs) have markedly improved survival outcomes. Accurate molecular testing is essential for guiding targeted therapy. However, tissue biopsy, the current gold standard, is often limited by insufficient samples, invasive procedure risks, or tumor heterogeneity, some patients experiencing sampling failure. Liquid biopsy based on circulating tumor DNA (ctDNA) offers a minimally invasive alternative and can shorten the detection cycle by 2 to 3 weeks, but its sensitivity depends on ctDNA shedding, and patient selection for blood-based testing remains challenging in clinical practice. This study aimed to develop a peripheral blood EGFR positivity prediction model and a simple scoring system to identify high probability candidates for liquid biopsy and prioritize blood-based EGFR testing when tissue samples are inadequate.

A retrospective case-control study design was employed. Data were collected from 384 patients with NSCLC who were hospitalized at The First Affiliated Hospital of Guangzhou Medical University between June 2018 and September 2024 and met the study's inclusion criteria. The patients were categorized into two groups: the peripheral blood EGFR-positive group (191 cases) and peripheral blood EGFR-negative group (193 cases). Univariate and binary logistic regression analyses were conducted to establish a predictive model for EGFR in peripheral blood, which was subsequently converted into a scoring system.

The results of multi-factor analysis showed that gender, smoking status, pulmonary lymphangitic carcinomatosis, non-vertebral bone metastasis, brain metastasis, and liver metastasis were independent factors for the prediction of EGFR positivity in peripheral blood (P<0.05). The receiver operating characteristic (ROC) curve analysis of predicted peripheral blood EGFR positivity showed that the area under the curve (AUC) was 0.884. A score of ≥3 was considered a high-probability population with positive EGFR in peripheral blood. The sensitivity for diagnosing positive EGFR in peripheral blood was 84.8%, and the specificity was 73.1%. Taking the next-generation sequencing (NGS) detection results as the reference standard, the sensitivity of amplification refractory mutation system polymerase chain reaction (ARMS-PCR) detection was 94.96%, the specificity was 100%, and the overall compliance rate was 96.2% [Kappa (Cohen's kappa coefficient) =0.903, P<0.001].

The Gspnbl score demonstrates good predictive performance in identifying patients with a high probability of peripheral blood EGFR positivity. This easy‑to‑apply tool helps clinicians rapidly select appropriate candidates for liquid‑biopsy EGFR testing. ARMS‑PCR and NGS have high consistency in detecting common EGFR‑sensitive mutations. ARMS‑PCR can be adopted for rapid initial screening in critically‑ill patients with high suspicion of EGFR mutations.