CT-based nomogram for early identification of T790M resistance in metastatic non-small cell lung cancer before first-line epidermal growth factor receptor-tyrosine kinase inhibitors therapy

Ye Li; Xinna Lv; Yichuan Wang; Zexuan Xu; Yan Lv; Dailun Hou

doi:10.1186/s41747-023-00380-7

CT-based nomogram for early identification of T790M resistance in metastatic non-small cell lung cancer before first-line epidermal growth factor receptor-tyrosine kinase inhibitors therapy

Eur Radiol Exp. 2023 Nov 2;7(1):64. doi: 10.1186/s41747-023-00380-7.

Authors

Ye Li^#¹, Xinna Lv^#¹, Yichuan Wang², Zexuan Xu¹, Yan Lv³, Dailun Hou⁴

Affiliations

¹ Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China.
² Department of Radiology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China.
³ Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China. yanlvlv@126.com.
⁴ Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China. hou.dl@mail.ccmu.edu.cn.

^# Contributed equally.

Abstract

Background: To evaluate the value of computed tomography (CT) radiomics in predicting the risk of developing epidermal growth factor receptor (EGFR) T790M resistance mutation for metastatic non-small lung cancer (NSCLC) patients before first-line EGFR-tyrosine kinase inhibitors (EGFR-TKIs) therapy.

Methods: A total of 162 metastatic NSCLC patients were recruited and split into training and testing cohort. Radiomics features were extracted from tumor lesions on nonenhanced CT (NECT) and contrast-enhanced CT (CECT). Radiomics score (rad-score) of two CT scans was calculated respectively. A nomogram combining two CT scans was developed to evaluate T790M resistance within up to 14 months. Patients were followed up to calculate the time of T790M occurrence. Models were evaluated by area under the curve at receiver operating characteristic analysis (ROC-AUC), calibration curve, and decision curve analysis (DCA). The association of the nomogram with the time of T790M occurrence was evaluated by Kaplan-Meier survival analysis.

Results: The nomogram constructed with the rad-score of NECT and CECT for predicting T790M resistance within 14 months achieved the highest ROC-AUCs of 0.828 and 0.853 in training and testing cohorts, respectively. The DCA showed that the nomogram was clinically useful. The Kaplan-Meier analysis showed that the occurrence time of T790M difference between the high- and low-risk groups distinguished by the rad-score was significant (p < 0.001).

Conclusions: The CT-based radiomics signature may provide prognostic information and improve pretreatment risk stratification in EGFR NSCLC patients before EGFR-TKIs therapy. The multimodal radiomics nomogram further improved the capability.

Relevance statement: Radiomics based on NECT and CECT images can effectively identify and stratify the risk of T790M resistance before the first-line TKIs treatment in metastatic non-small cell lung cancer patients.

Key points: • Early identification of the risk of T790M resistance before TKIs treatment is clinically relevant. • Multimodel radiomics nomogram holds potential to be a diagnostic tool. • It provided an imaging surrogate for identifying the pretreatment risk of T790M.

Keywords: Carcinoma (non-small cell lung); ErbB receptors; Nomograms; Radiomics; Tomography (x-ray computed).

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carcinoma, Non-Small-Cell Lung* / diagnostic imaging
Carcinoma, Non-Small-Cell Lung* / drug therapy
Carcinoma, Non-Small-Cell Lung* / genetics
ErbB Receptors / genetics
Humans
Lung Neoplasms* / diagnostic imaging
Lung Neoplasms* / drug therapy
Mutation
Nomograms
Protein Kinase Inhibitors / therapeutic use
Risk Assessment
Tomography, X-Ray Computed / methods
Tyrosine Kinase Inhibitors

Substances

Tyrosine Kinase Inhibitors
ErbB Receptors
Protein Kinase Inhibitors