Applicability of a prognostic CT-based radiomic signature model trained on stage I-III non-small cell lung cancer in stage IV non-small cell lung cancer. (October 2018)

• Record Type: Journal Article
• Authors: de Jong, Evelyn E.C.; van Elmpt, Wouter; Rizzo, Stefania; Colarieti, Anna; Spitaleri, Gianluca; Leijenaar, Ralph T.H.; Jochems, Arthur; Hendriks, Lizza E.L.; Troost, Esther G.C.; Reymen, Bart; Dingemans, Anne-Marie C.; Lambin, Philippe
• Is Part Of: Lung cancer. Volume 124(2018)
• Page Start: 6
• Page End: 11
• Publication Date: 2018-10
• Subjects: Stage IV NSCLC -- Prognostic model -- Radiomics -- CT; Lungs -- Cancer -- Periodicals; Lung Neoplasms -- Abstracts; Lung Neoplasms -- Periodicals; Poumons -- Cancer -- Périodiques; Lungs -- Cancer; Periodicals; Electronic journals; Electronic journals; 616.99424
• DOI: 10.1016/j.lungcan.2018.07.023
• Languages: English
• ISSNs: 0169-5002

Abstract

Highlights: Radiomic CT features are prognostic in stage I-III non-small cell lung cancer. Radiomic signature trained on stage I-III is as well prognostic in stage IV NSCLC. Primary tumor radiomics shows to be prognostic for metastatic NSCLC patients. Abstract: Objectives: Recently it has been shown that radiomic features of computed tomography (CT) have prognostic information in stage I-III non-small cell lung cancer (NSCLC) patients. We aim to validate this prognostic radiomic signature in stage IV adenocarcinoma patients undergoing chemotherapy. Materials and methods: Two datasets of chemo-naive stage IV adenocarcinoma patients were investigated, dataset 1: 285 patients with CTs performed in a single center; dataset 2: 223 patients included in a multicenter clinical trial. The main exclusion criteria were EGFR mutation or unknown mutation status and non-delineated primary tumor. Radiomic features were calculated for the primary tumor. The c-index of cox regression was calculated and compared to the signature performance for overall survival (OS). Results: In total CT scans from 195 patients were eligible for analysis. Patients having a prognostic index (PI) lower than the signature median (n = 92) had a significantly better OS than patients with a PI higher than the median (n = 103, HR 1.445, 95% CI 1.07–1.95, p = 0.02, c-index 0.576, 95% CI 0.527–0.624). Conclusion: The radiomic signature, derived from daily practice CT scans, has prognostic value for stage IV NSCLC, however the signature performs less than previously described for stage I-III NSCLC stages. In the future, machine learning techniques can potentially lead to a better prognostic imaging based model for stage IV NSCLC.