Radiomics-based predictive risk score: A scoring system for preoperatively predicting risk of lymph node metastasis in patients with resectable non-small cell lung cancer

摘要

Objective: To develop and validate a radiomics-based predictive risk score(RPRS) for preoperative prediction of lymph node(LN) metastasis in patients with resectable non-small cell lung cancer(NSCLC).Methods: We retrospectively analyzed 717 who underwent surgical resection for primary NSCLC with systematic mediastinal lymphadenectomy from October 2007 to July 2016. By using the method of radiomics analysis, 591 computed tomography(CT)-based radiomics features were extracted, and the radiomics-based classifier was constructed. Then, using multivariable logistic regression analysis, a weighted score RPRS was derived to identify LN metastasis. Apparent prediction performance of RPRS was assessed with its calibration,discrimination, and clinical usefulness.Results: The radiomics-based classifier was constructed, which consisted of 13 selected radiomics features.Multivariate models demonstrated that radiomics-based classifier, age group, tumor diameter, tumor location, and CT-based LN status were independent predictors. When we assigned the corresponding score to each variable,patients with RPRSs of 0-3, 4-5, 6, 7-8, and 9 had distinctly very low(0%-20%), low(21%-40%), intermediate(41%-60%), high(61%-80%), and very high(81%-100%) risks of LN involvement, respectively. The developed RPRS showed good discrimination and satisfactory calibration (C-index: 0.785, 95% confidence interval(95% CI):0.780-0.790)Additionally, RPRS outperformed the clinicopathologic-based characteristics model with net reclassification index(NRI) of 0.711(95% CI: 0.555-0.867).Conclusions: The novel clinical scoring system developed as RPRS can serve as an easy-to-use tool to facilitate the preoperatively individualized prediction of LN metastasis in patients with resectable NSCLC. This stratification of patients according to their LN status may provide a basis for individualized treatment.