CT-Based Radiomic Signature as a Prognostic Factor in Stage IV ALK-Positive Non-small-cell Lung Cancer Treated With TKI Crizotinib: A Proof-of-Concept Study - Li, Hailin; Zhang, Rui; Wang, Siwen; Fang, Mengjie; Zhu, Yongbei; Hu, Zhenhua; Dong, Di; Shi, Jingyun; Tian, Jie (Frontiers in Oncology, 2020)
Objectives: To identify a computed tomography (CT)-based radiomic signature for predicting progression-free survival (PFS) in stage IV anaplastic lymphoma kinase (ALK)-positive non-small-cell lung cancer (NSCLC) patients treated with tyrosine kinase inhibitor (TKI) crizotinib. Materials and Methods: This retrospective proof-of-concept study included a cohort of 63 stage IV ALK-positive NSCLC patients who had received TKI crizotinib therapy for model construction and validation. Another independent cohort including 105 stage IV EGFR-positive NSCLC patients was also used for external validation in EGFR-TKI treatment. We initially extracted 481 quantitative three-dimensional features derived from manually segmented tumor volumes of interest. Pearson correlation analysis along with the least absolute shrinkage and selection operator (LASSO) penalized Cox proportional hazards regression was successively performed to select critical radiomic features. A CT-based radiomic signature for PFS prediction was obtained using multivariate Cox regression. The performance evaluation of the radiomic signature was conducted using concordance index (C-index), time-dependent receiver operating characteristic (ROC) analysis, and Kaplan-Meier survival analysis. Results: A radiomic signature containing 3 features showed significant prognostic performance for ALK-positive NSCLC patients in both the training cohort (C-index, 0.744; time-dependent AUC, 0.895) and validation cohort (C-index, 0.717; time-dependent AUC, 0.824). The radiomic signature could significantly risk stratify ALK-positive NSCLC patients (hazard ratio, 2.181; P < 0.001) and outperformed other prognostic factors. However, no significant association with PFS was captured for the radiomic signature in EGFR-positive NSCLC cohort (log-rank tests, P = 0.41). Conclusions: The CT-based radiomic features can capture valuable information regarding the tumor phenotype. The proposed radiomic signature was found an effective prognostic factor in stage IV ALK mutated none-synchronous nodules NSCLC patients treated with TKI.