Huanlei Zhang1,2, Ying Zou3, Fengyue Tian4, Wenfei Li5, Xiaodong Ji6, Yu Guo6, Qing Li6, Shuangyan Sun1,7, Fang Sun1,8, Lianfang Shen1,2, Shuang Xia9. 1. Department of Radiology, First Central Clinical College, Tianjin Medical University, No. 24 Fu Kang Road, Nankai District, Tianjin, 300192, China. 2. Department of Radiology, Yidu Central Hospital of Weifang, No. 4138 Linglongshan South Road, Qingzhou City, 262500, Shandong, China. 3. Department of Radiology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, No. 314 Anshan West Road, Nankai District, Tianjin, 300193, China. 4. Department of Radiology, Affiliated Hospital of Nankai University (Tianjin No. 4 Hospital), Tianjin, 300222, China. 5. Department of Radiology, The First Hospital of Qinhuangdao, No. 258 Wenhua Road, Haigang District, Qinhuangdao, 066000, China. 6. Department of Radiology, Tianjin First Central Hospital, School of Medicine, Nankai University, No. 24 Fu Kang Road, Nankai District, Tianjin, 300192, China. 7. Department of Radiology, Jilin Cancer Hospital, No. 1066 JinHu Road, Chaoyang District, , Changchun, 130000, China. 8. Department of Ultrasonography, Binzhou Medical University Hospital, No. 661 Huanghe 2nd Road, Binzhou City, Shandong, 256603, China. 9. Department of Radiology, Tianjin First Central Hospital, School of Medicine, Nankai University, No. 24 Fu Kang Road, Nankai District, Tianjin, 300192, China. xiashuang77@163.com.
Abstract
OBJECTIVES: To establish and validate a predictive model integrating with clinical and dual-energy CT (DECT) variables for individual recurrence-free survival (RFS) prediction in early-stage glottic laryngeal cancer (EGLC) after larynx-preserving surgery. METHODS: This retrospective study included 212 consecutive patients with EGLC who underwent DECT before larynx-preserving surgery between January 2015 and December 2018. Using Cox proportional hazard regression model to determine independent predictors for RFS and presented on a nomogram. The model's performance was assessed using Harrell's concordance index (C-index), time-dependent area under curve (TD-AUC) plot, and calibration curve. A risk stratification system was established using the nomogram with median scores of all cases to divide all patients into two prognostic groups. RESULTS: Recurrence occurred in 39/212 (18.4%) cases. Normalized iodine concentration in arterial (NICAP) and venous phases (NICVP) were verified as significant predictors of RFS in multivariate Cox regression (hazard ratio [HR], 4.2; 95% confidence interval [CI]: 2.3, 7.7, p < .001 and HR, 3.0; 95% CI: 1.5, 5.9, p = .002, respectively). Nomogram based on clinical and DECT variables was better than did only clinical variables. The prediction model proved well-calibrated and had good discriminative ability in the training and validation samples. A risk stratification system was built that could effectively classify EGLC patients into two risk groups. CONCLUSIONS: DECT could provide independent RFS indicators in patients with EGLC, and the nomogram based on DECT and clinical variables was useful in predicting RFS at several time points. KEY POINTS: • Dual-energy CT(DECT) variables can predict recurrence-free survival (RFS) after larynx-preserving surgery in patients with early-stage glottic laryngeal cancer (EGLC). • The model that integrates clinical and DECT variables predicted RFS better than did only clinical variables. • A risk stratification system based on the nomogram could effectively classify EGLC patients into two risk groups.
OBJECTIVES: To establish and validate a predictive model integrating with clinical and dual-energy CT (DECT) variables for individual recurrence-free survival (RFS) prediction in early-stage glottic laryngeal cancer (EGLC) after larynx-preserving surgery. METHODS: This retrospective study included 212 consecutive patients with EGLC who underwent DECT before larynx-preserving surgery between January 2015 and December 2018. Using Cox proportional hazard regression model to determine independent predictors for RFS and presented on a nomogram. The model's performance was assessed using Harrell's concordance index (C-index), time-dependent area under curve (TD-AUC) plot, and calibration curve. A risk stratification system was established using the nomogram with median scores of all cases to divide all patients into two prognostic groups. RESULTS: Recurrence occurred in 39/212 (18.4%) cases. Normalized iodine concentration in arterial (NICAP) and venous phases (NICVP) were verified as significant predictors of RFS in multivariate Cox regression (hazard ratio [HR], 4.2; 95% confidence interval [CI]: 2.3, 7.7, p < .001 and HR, 3.0; 95% CI: 1.5, 5.9, p = .002, respectively). Nomogram based on clinical and DECT variables was better than did only clinical variables. The prediction model proved well-calibrated and had good discriminative ability in the training and validation samples. A risk stratification system was built that could effectively classify EGLC patients into two risk groups. CONCLUSIONS: DECT could provide independent RFS indicators in patients with EGLC, and the nomogram based on DECT and clinical variables was useful in predicting RFS at several time points. KEY POINTS: • Dual-energy CT(DECT) variables can predict recurrence-free survival (RFS) after larynx-preserving surgery in patients with early-stage glottic laryngeal cancer (EGLC). • The model that integrates clinical and DECT variables predicted RFS better than did only clinical variables. • A risk stratification system based on the nomogram could effectively classify EGLC patients into two risk groups.