Association between tumor heterogeneity and progression-free survival in non-small cell lung cancer patients with EGFR mutations undergoing tyrosine kinase inhibitors therapy.

Abstract

For non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations, current staging methods do not accurately predict the risk of disease recurrence after tyrosine kinase inhibitors (TKI) therapy. Developing a noninvasive method to predict whether individual could benefit from TKI therapy has great clinical significance. In this research, a radiomics approach was proposed to determine whether the tumor heterogeneity of NSCLC, which was measured by the texture on computed tomography (CT), could make an independent prediction of progression-free survival (PFS). A primary dataset contained 80 patients (median PFS, 9.5 months) with positive EGFR mutations and a validation dataset contained 72 NSCLC (median PFS, 10.2 months) patients were used for prognosis trial. The experiment results indicated that the features: "Cluster Prominence of Gray Level Co-occurrence" (hazard ratio [HR]: 2.13, 95% confidence interval [CI]: (1.33, 3.40), P = 0.010) and "Short Run High Gray Level Emphasis of Run Length" (HR: 2.43, 95%CI: (1.46, 4.05), P = 0.005) were significantly associated with PFS in the primary dataset, and these two texture features also make a consistent performance on the validation cohort. Our study further supported that the quantitative measurement of tumor heterogeneity can be associated with prognosis of NSCLC patients with EGFR mutation.