Bei-Bei Xiao1,2, Da-Feng Lin1,2, Xue-Song Sun1,2, Xu Zhang1,3, Shan-Shan Guo1,2, Li-Ting Liu1,2, Dong-Hua Luo1,2, Rui Sun1,2, Yue-Feng Wen1,2, Ji-Bin Li1,4, Xiao-Fei Lv1,5, Lu-Jun Han1,5, Li Yuan1, Sai-Lan Liu1,2, Qing-Nan Tang1,2, Yu-Jing Liang1,2, Xiao-Yun Li1,2, Ling Guo1,2, Qiu-Yan Chen1,2, Wei Fan1,3, Hai-Qiang Mai6,7, Lin-Quan Tang8,9. 1. State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. 2. Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. 3. Department of Nuclear Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. 4. Department of Clinical Research, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. 5. Department of Medical Imaging, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. 6. State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. maihq@sysucc.org.cn. 7. Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. maihq@sysucc.org.cn. 8. State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. tanglq@sysucc.org.cn. 9. Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People's Republic of China. tanglq@sysucc.org.cn.
Abstract
PURPOSE: This study aimed to establish an effective nomogram to predict primary distant metastasis (DM) in patients with nasopharyngeal carcinoma (NPC) to guide the application of PET/CT. METHODS: In total, 3591 patients with pathologically confirmed NPC were consecutively enrolled. The nomogram was constructed based on 1922 patients treated between 2007 and 2014. Multivariate logistical regression was applied to identify the independent risk factors of DM. The predictive value of the nomogram was evaluated using the concordance index (C-index), calibration curve, probability density functions (PDFs), and clinical utility curve (CUC). The results were validated in 1669 patients enrolled from 2015 to 2016. Net reclassification improvement (NRI) was applied to compare performances of the nomogram with other clinical factors. The best cut-off value of the nomogram chosen for clinical application was analyzed. RESULTS: A total of 355 patients showed primary DM among 3591 patients, yielding an incidence rate of 9.9%. Sex, N stage, EBV DNA level, lactate dehydrogenase level, and hemoglobin level were independent predictive factors for primary DM. C-indices in the training and validation cohort were 0.796 (95% CI, 0.76-0.83) and 0.779 (95% CI, 0.74-0.81), respectively. The NRI indices demonstrated that this model had better predictive performance than plasma EBV DNA level and N stage. We advocate for a threshold probability of 3.5% for guiding the application of PET/CT depending on the clinical utility analyses. CONCLUSION: This nomogram is a useful tool to predict primary DM of NPC and guide the clinical application of PET/CT individually at the initial staging.
PURPOSE: This study aimed to establish an effective nomogram to predict primary distant metastasis (DM) in patients with nasopharyngeal carcinoma (NPC) to guide the application of PET/CT. METHODS: In total, 3591 patients with pathologically confirmed NPC were consecutively enrolled. The nomogram was constructed based on 1922 patients treated between 2007 and 2014. Multivariate logistical regression was applied to identify the independent risk factors of DM. The predictive value of the nomogram was evaluated using the concordance index (C-index), calibration curve, probability density functions (PDFs), and clinical utility curve (CUC). The results were validated in 1669 patients enrolled from 2015 to 2016. Net reclassification improvement (NRI) was applied to compare performances of the nomogram with other clinical factors. The best cut-off value of the nomogram chosen for clinical application was analyzed. RESULTS: A total of 355 patients showed primary DM among 3591 patients, yielding an incidence rate of 9.9%. Sex, N stage, EBV DNA level, lactate dehydrogenase level, and hemoglobin level were independent predictive factors for primary DM. C-indices in the training and validation cohort were 0.796 (95% CI, 0.76-0.83) and 0.779 (95% CI, 0.74-0.81), respectively. The NRI indices demonstrated that this model had better predictive performance than plasma EBV DNA level and N stage. We advocate for a threshold probability of 3.5% for guiding the application of PET/CT depending on the clinical utility analyses. CONCLUSION: This nomogram is a useful tool to predict primary DM of NPC and guide the clinical application of PET/CT individually at the initial staging.
Authors: Dominique Delbeke; R Edward Coleman; Milton J Guiberteau; Manuel L Brown; Henry D Royal; Barry A Siegel; David W Townsend; Lincoln L Berland; J Anthony Parker; Karl Hubner; Michael G Stabin; George Zubal; Marc Kachelriess; Valerie Cronin; Scott Holbrook Journal: J Nucl Med Date: 2006-05 Impact factor: 10.057