radiomics signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non–Small Cell Lung Cancer
To develop a radiomics signature to estimate disease-free survival (DFS) in patients with early-stage (stage I–II) non–small cell lung cancer (NSCLC) and assess its incre- mental value to the traditional staging system and clinical- pathologic risk factors for individual DFS estimation.
Materials and Methods:
Ethical approval by the institutional review board was ob- tained for this retrospective analysis, and the need to ob- tain informed consent was waived. This study consisted of 282 consecutive patients with stage IA–IIB NSCLC. A ra- diomics signature was generated by using the least absolute shrinkage and selection operator, or LASSO, Cox regres- sion model. Association between the radiomics signature and DFS was explored. Further validation of the radiomics signature as an independent biomarker was performed by using multivariate Cox regression. A radiomics nomogram with the radiomics signature incorporated was constructed to demonstrate the incremental value of the radiomics sig- nature to the traditional staging system and other clinical- pathologic risk factors for individualized DFS estimation, which was then assessed with respect to calibration, dis- crimination, reclassification, and clinical usefulness.
The radiomics signature was significantly associated with DFS, independent of clinical-pathologic risk factors. Incor- porating the radiomics signature into the radiomics-based nomogram resulted in better performance (P , .0001) for the estimation of DFS (C-index: 0.72; 95% confidence inter- val [CI]: 0.71, 0.73) than with the clinical-pathologic nomo- gram (C-index: 0.691; 95% CI: 0.68, 0.70), as well as a bet- ter calibration and improved accuracy of the classification of survival outcomes (net reclassification improvement: 0.182; 95% CI: 0.02, 0.31; P = .02). Decision curve analysis demonstrated that in terms of clinical usefulness, the ra- diomics nomogram outperformed the traditional staging system and the clinical-pathologic nomogram.
The radiomics signature is an independent biomarker for the estimation of DFS in patients with early-stage NSCLC. Combination of the radiomics signature, traditional stag- ing system, and other clinical-pathologic risk factors per- formed better for individualized DFS estimation in pa- tients with early-stage NSCLC, which might enable a step forward precise medicine.