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A CT‐based radiomics model to predict subsequent brain metastasis in patients with ALK‐rearranged non–small cell lung cancer undergoing crizotinib treatment

Authors :
Yongluo Jiang
Yixing Wang
Sha Fu
Tao Chen
Yixin Zhou
Xuanye Zhang
Chen Chen
Li‐na He
Wei Du
Haifeng Li
Zuan Lin
Yuanyuan Zhao
Yunpeng Yang
Hongyun Zhao
Wenfeng Fang
Yan Huang
Shaodong Hong
Li Zhang
Source :
Thoracic Cancer, Vol 13, Iss 11, Pp 1558-1569 (2022)
Publication Year :
2022
Publisher :
Wiley, 2022.

Abstract

Abstract Background Brain metastasis (BM) comprises the most common reason for crizotinib failure in patients with anaplastic lymphoma kinase (ALK)‐rearranged non–small cell lung cancer (NSCLC). We hypothesize that its occurrence could be predicted by a computed tomography (CT)‐based radiomics model, therefore, allowing for selection of enriched patient populations for prevention therapies. Methods A total of 75 eligible patients were enrolled from Sun Yat‐sen University Cancer Center between June 2014 and September 2019. The primary endpoint was brain metastasis‐free survival (BMFS), estimated from the initiation of crizotinib to the date of the occurrence of BM. Patients were randomly divided into two cohorts for model training (n = 51) and validation (n = 24), respectively. A radiomics signature was constructed based on features extracted from chest CT before crizotinib treatment. Clinical model was developed using the Cox proportional hazards model. Log‐rank test was performed to describe the difference of BMFS risk. Results Patients with low radiomics score had significantly longer BMFS than those with higher, both in the training cohort (p = 0.019) and validation cohort (p = 0.048). The nomogram combining smoking history and the radiomics signature showed good performance for the estimation of BMFS, both in the training (concordance index [C‐index], 0.762; 95% confidence interval [CI], 0.663–0.861) and validation cohort (C‐index, 0.724; 95% CI, 0.601–0.847). Conclusion We have developed a CT‐based radiomics model to predict subsequent BM in patients with non‐brain metastatic NSCLC undergoing crizotinib treatment. Selection of an enriched patient population at high BM risk will facilitate the design of clinical trials or strategies to prevent BM.

Details

Language :
English
ISSN :
17597714 and 17597706
Volume :
13
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Thoracic Cancer
Publication Type :
Academic Journal
Accession number :
edsdoj.1813850a98a94b6db579f9e23f06634c
Document Type :
article
Full Text :
https://doi.org/10.1111/1759-7714.14386