Prediction Model for Tumor Volume Nadir in EGFR -mutant NSCLC Patients Treated With EGFR Tyrosine Kinase Inhibitors.

Abstract

In patients with advanced non-small cell lung cancer (NSCLC) and oncogenic driver mutations treated with effective targeted therapy, a characteristic pattern of tumor volume dynamics with an initial regression, nadir, and subsequent regrowth is observed on serial computed tomography (CT) scans. We developed and validated a linear model to predict the tumor volume nadir in EGFR -mutant advanced NSCLC patients treated with EGFR tyrosine kinase inhibitors (TKI). Patients with EGFR -mutant advanced NSCLC treated with EGFR-TKI as their first EGFR-directed therapy were studied for CT tumor volume kinetics during therapy, using a previously validated CT tumor measurement technique. A linear regression model was built to predict tumor volume nadir in a training cohort of 34 patients, and then was validated in an independent cohort of 84 patients. The linear model for tumor nadir prediction was obtained in the training cohort of 34 patients, which utilizes the baseline tumor volume before initiating therapy (V 0 ) to predict the volume decrease (mm 3 ) when the nadir volume (V p ) was reached: V 0 -V p =0.717×V 0 -1347 ( P =2×10 -16 ; R2 =0.916). The model was tested in the validation cohort, resulting in the R2 value of 0.953, indicating that the prediction model generalizes well to another cohort of EGFR -mutant patients treated with EGFR-TKI. Clinical variables were not significant predictors of tumor volume nadir. The linear model was built to predict the tumor volume nadir in EGFR -mutant advanced NSCLC patients treated with EGFR-TKIs, which provide an important metrics in treatment monitoring and therapeutic decisions at nadir such as additional local abrasive therapy.