Wang-Zhong Li1, Shu-Hui Lv1, Guo-Ying Liu1, Hu Liang1, Xiang Guo1, Xing Lv1, Kui-Yuan Liu1, Meng-Yun Qiang1, Xi Chen1, Sophie Z Gu2, Chang-Qing Xie3, Wei-Xiong Xia4, Yan-Qun Xiang5. 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, Guangzhou, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, China. 2. Johns Hopkins University School of Medicine, Baltimore, Maryland. 3. Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, Maryland. Electronic address: changqing.xie@nih.gov. 4. 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, Guangzhou, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, China. Electronic address: xiawx@sysucc.org.cn. 5. 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, Guangzhou, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, China. Electronic address: xiangyq@sysucc.org.cn.
Abstract
PURPOSE: We aimed to develop an accurate prognostic model to identify suitable candidates for definitive radiation therapy (DRT) in addition to palliative chemotherapy (PCT) among patients with de novo metastatic nasopharyngeal carcinoma (mNPC). METHODS AND MATERIALS: Patients with de novo mNPC who received first-line PCT with or without DRT were included. Overall survival for patients who received PCT alone versus PCT plus DRT was estimated using inverse probability of treatment weighting-adjusted survival analyses. We developed and validated a prognostic model to predict survival and stratify risks in de novo mNPC. A model-based trees approach was applied to estimate stratified treatment effects using prognostic scores obtained from the prognostic model and to identify suitable DRT candidates. Dominance analysis was used to determine the relative importance of each predictor of receiving DRT. RESULTS: A total of 460 patients were enrolled; 244 received PCT plus DRT and 216 received PCT alone. The 6-month conditional landmark, inverse probability of treatment weighting-adjusted Cox regression analysis showed that PCT plus DRT was associated with a significant survival benefit (hazard ratio: 0.516; 95% confidence interval, 0.403-0.660; P < .001). A prognostic model based on 5 independent prognostic factors, including serum lactate dehydrogenase, number of metastatic sites, presence of liver metastasis, posttreatment Epstein-Barr virus DNA level, and response of metastases to chemotherapy was developed and subsequently validated. Prognostic scores obtained from the prognostic model were used for risk stratification and efficacy estimation. High-risk patients identified using the proposed model would not benefit from additional DRT, whereas low-risk patients experienced significant survival benefits. Socioeconomic factors, including insurance status and education level, played an important role in receipt of DRT. CONCLUSIONS: Additional DRT after PCT was associated with increased overall survival in patients with de novo mNPC, especially low-risk patients identified with a newly developed prognostic model.
PURPOSE: We aimed to develop an accurate prognostic model to identify suitable candidates for definitive radiation therapy (DRT) in addition to palliative chemotherapy (PCT) among patients with de novo metastatic nasopharyngeal carcinoma (mNPC). METHODS AND MATERIALS: Patients with de novo mNPC who received first-line PCT with or without DRT were included. Overall survival for patients who received PCT alone versus PCT plus DRT was estimated using inverse probability of treatment weighting-adjusted survival analyses. We developed and validated a prognostic model to predict survival and stratify risks in de novo mNPC. A model-based trees approach was applied to estimate stratified treatment effects using prognostic scores obtained from the prognostic model and to identify suitable DRT candidates. Dominance analysis was used to determine the relative importance of each predictor of receiving DRT. RESULTS: A total of 460 patients were enrolled; 244 received PCT plus DRT and 216 received PCT alone. The 6-month conditional landmark, inverse probability of treatment weighting-adjusted Cox regression analysis showed that PCT plus DRT was associated with a significant survival benefit (hazard ratio: 0.516; 95% confidence interval, 0.403-0.660; P < .001). A prognostic model based on 5 independent prognostic factors, including serum lactate dehydrogenase, number of metastatic sites, presence of liver metastasis, posttreatment Epstein-Barr virus DNA level, and response of metastases to chemotherapy was developed and subsequently validated. Prognostic scores obtained from the prognostic model were used for risk stratification and efficacy estimation. High-risk patients identified using the proposed model would not benefit from additional DRT, whereas low-risk patients experienced significant survival benefits. Socioeconomic factors, including insurance status and education level, played an important role in receipt of DRT. CONCLUSIONS: Additional DRT after PCT was associated with increased overall survival in patients with de novo mNPC, especially low-risk patients identified with a newly developed prognostic model.