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Liu Y, Zuo ZC, Zeng XY, Ma J, Ma CX, Chen RZ, Liang ZG, Chen KH, Li L, Qu S, Lu JY, Zhu XD. Establishing subdivisions of M1 stage nasopharyngeal carcinoma based on decision tree classification: A multicenter retrospective study. Oral Oncol 2024; 153:106834. [PMID: 38718458 DOI: 10.1016/j.oraloncology.2024.106834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 04/09/2024] [Accepted: 05/03/2024] [Indexed: 05/21/2024]
Abstract
OBJECTIVES To meet the demand for personalized treatment, effective stratification of patients with metastatic nasopharyngeal carcinoma (mNPC) is essential. Hence, our study aimed to establish an M1 subdivision for prognostic prediction and treatment planning in patients with mNPC. MATERIALS AND METHODS This study included 1239 patients with mNPC from three medical centers divided into the synchronous mNPC cohort (smNPC, n = 556) to establish an M1 stage subdivision and the metachronous mNPC cohort (mmNPC, n = 683) to validate this subdivision. The primary endpoint was overall survival. Univariate and multivariate Cox analyses identified covariates for the decision-tree model, proposing an M1 subdivision. Model performance was evaluated using time-dependent receiver operating characteristic curves, Harrell's concordance index, calibration plots, and decision curve analyses. RESULTS The proposed M1 subdivisions were M1a (≤5 metastatic lesions), M1b (>5 metastatic lesions + absent liver metastases), and M1c (>5 metastatic lesions + existing liver metastases) with median OS of 34, 22, and 13 months, respectively (p < 0.001). This M1 subdivision demonstrated superior discrimination (C-index = 0.698; 3-year AUC = 0.707) and clinical utility over those of existing staging systems. Calibration curves exhibited satisfactory agreement between predictions and actual observations. Internal and mmNPC cohort validation confirmed the robustness. Survival benefits from local metastatic treatment were observed in M1a, while immunotherapy improved survival in patients with M1b and M1c disease. CONCLUSION This novel M1 staging strategy provides a refined approach for prognostic prediction and treatment planning in patients with mNPC, emphasizing the potential benefits of local and immunotherapeutic interventions based on individualized risk stratification.
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Affiliation(s)
- Yang Liu
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Zhi-Chao Zuo
- Department of Radiology, Xiangtan Central Hospital, Xiangtan, People's Republic of China
| | - Xiao-Yi Zeng
- Department of Radiation Oncology, Wuzhou Red Cross Hospital, Wuzhou, People's Republic of China
| | - Jie Ma
- Medical Imaging Department, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Cheng-Xian Ma
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Rui-Zhong Chen
- Department of Radiation Oncology, Wuzhou Red Cross Hospital, Wuzhou, People's Republic of China
| | - Zhong-Guo Liang
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Kai-Hua Chen
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Ling Li
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China; Key Laboratory of Early Prevention and Treatment for Regional High-Incidence-Tumor, Guangxi Medical University, Ministry of Education, Nanning, Guangxi, People's Republic of China
| | - Song Qu
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China; Key Laboratory of Early Prevention and Treatment for Regional High-Incidence-Tumor, Guangxi Medical University, Ministry of Education, Nanning, Guangxi, People's Republic of China
| | - Jie-Yan Lu
- Medical Imaging Department, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China
| | - Xiao-Dong Zhu
- Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, People's Republic of China; Key Laboratory of Early Prevention and Treatment for Regional High-Incidence-Tumor, Guangxi Medical University, Ministry of Education, Nanning, Guangxi, People's Republic of China; Department of Oncology, Affiliated Wu-Ming Hospital of Guangxi Medical University, Nanning, People's Republic of China.
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Suryani L, Lee HPY, Teo WK, Chin ZK, Loh KS, Tay JK. Precision Medicine for Nasopharyngeal Cancer-A Review of Current Prognostic Strategies. Cancers (Basel) 2024; 16:918. [PMID: 38473280 DOI: 10.3390/cancers16050918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/02/2024] [Accepted: 02/19/2024] [Indexed: 03/14/2024] Open
Abstract
Nasopharyngeal carcinoma (NPC) is an Epstein-Barr virus (EBV) driven malignancy arising from the nasopharyngeal epithelium. Current treatment strategies depend on the clinical stage of the disease, including the extent of the primary tumour, the extent of nodal disease, and the presence of distant metastasis. With the close association of EBV infection with NPC development, EBV biomarkers have shown promise in predicting treatment outcomes. Among the omic technologies, RNA and miRNA signatures have been widely studied, showing promising results in the research setting to predict treatment response. The transformation of radiology images into measurable features has facilitated the use of radiomics to generate predictive models for better prognostication and treatment selection. Nonetheless, much of this work remains in the research realm, and challenges remain in clinical implementation.
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Affiliation(s)
- Luvita Suryani
- Department of Otolaryngology-Head & Neck Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Hazel P Y Lee
- Department of Otolaryngology-Head & Neck Surgery, National University Hospital, Singapore 119228, Singapore
| | - Wei Keat Teo
- Department of Otolaryngology-Head & Neck Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Zhi Kang Chin
- Department of Otolaryngology-Head & Neck Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Kwok Seng Loh
- Department of Otolaryngology-Head & Neck Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Joshua K Tay
- Department of Otolaryngology-Head & Neck Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
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Chen Y, Chen C, Peng H, Lin S, Pan J, Zheng H, Zong J, Lin C. Risk-adapted locoregional radiotherapy strategies based on a prognostic nomogram for de novo metastatic nasopharyngeal carcinoma patients treated with chemoimmunotherapy. Sci Rep 2024; 14:3950. [PMID: 38366057 PMCID: PMC10873310 DOI: 10.1038/s41598-024-54230-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 02/10/2024] [Indexed: 02/18/2024] Open
Abstract
To develop a prognostic nomogram for individualized strategies on locoregional radiation therapy (LRRT) in patients with de novo metastatic nasopharyngeal carcinoma (dmNPC) treated with chemoimmunotherapy. Ninety patients with dmNPC treated with chemoimmunotherapy and diagnosed between 2019 and 2022 were included in our study. Cox regression analysis was performed to identify independent prognostic factors for overall survival (OS) and progression-free survival (PFS) to establish a nomogram. With a median follow-up of 17.5 months, the median PFS and OS were 24.9 months and 29.4 months, respectively. Sixty-nine patients and twenty-one patients were included in the LRRT group and without LRRT group, respectively. Multivariate analysis revealed that younger age, lower EBV DNA copy number before treatment, a single metastatic site, more cycles of chemotherapy and immunotherapy were significantly associated with better OS. A prognostic nomogram was constructed incorporating the above 5 independent factors, with a C-index of 0.894. Patients were divided into low- and high-risk cohorts based on nomogram scores. A significant improvement in OS was revealed in the LRRT group compared with the without-LRRT group for patients in the high-risk cohort (HR = 2.46, 95% CI 1.01-6.00, P = 0.049), while the OS was comparable between the two groups in the low-risk cohort. Our study indicates that LRRT may be associated with better prognosis in high-risk patients with dmNPC in the era of immunotherapy.
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Affiliation(s)
- Yuebing Chen
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Chuying Chen
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Hewei Peng
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, Fujian Province, China
| | - Shaojun Lin
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Jianji Pan
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
- Department of Radiation Oncology, Fujian Medical University Xiamen Humanity Hospital, Xiamen, Fujian Province, China
| | - Huiping Zheng
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China
| | - Jingfeng Zong
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China.
| | - Cheng Lin
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China.
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Lu T, Zeng F, Hu Y, Fang M, Zhong F, Chen B, Zhang H, Guo Q, Pan J, Gong X, Huang SH, Liao Z, Xia Y, Li J. Anatomic prognostic factors and their potential roles in refining M1 classification for de novo metastatic nasopharyngeal carcinoma. Cancer Med 2023; 12:22091-22102. [PMID: 38073447 PMCID: PMC10757129 DOI: 10.1002/cam4.6816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 07/03/2023] [Accepted: 12/03/2023] [Indexed: 12/31/2023] Open
Abstract
BACKGROUND AND PURPOSE To identify anatomic prognostic factors and their potential roles in refining M1 classification for de novo metastatic nasopharyngeal carcinoma (M1-NPC). MATERIALS AND METHODS All M1-NPC treated with chemotherapy and/or radiotherapy between 2010 and 2019 from two centers (training and validation cohort) were included. The prognostic value of metastatic disease extent and involved organs for overall survival (OS) were assessed by several multivariable analyses (MVA) models. A new M1 classification was proposed and validated in a separate cohort who received immuno-chemotherapy. RESULTS A total of 197 M1-NPC in the training and 307 in the validation cohorts were included for M1 subdivision study with median follow-up of 46 and 57 months. MVA model with "≤2 organs/≤5 lesions" as the definition of oligometastasis had the highest C-index (0.623) versus others (0.606-0.621). Patients with oligometastasis had better OS versus polymetastasis (hazard ratio [HR] 0.47/0.63) while liver metastases carried worse OS (HR 1.57/1.45) in MVA in the training/validation cohorts, respectively. We proposed to divide M1-NPC into M1a (oligometastasis without liver metastases) and M1b (liver metastases or polymetastasis) with 3-year OS of 66.5%/31.7% and 64.9%/35.0% in the training/validation cohorts, respectively. M1a subset had a better median progress-free survival (not reach vs. 17 months, p < 0.001) in the immuno-chemotherapy cohort (n = 163). CONCLUSION Oligometastasis (≤2 organs/≤5 lesions) and liver metastasis are prognostic for M1-NPC. Subdivision of M1-NPC into M1a (oligometastasis without liver metastasis) and M1b (liver metastasis or polymetastasis) depicts the prognosis well in M1-NPC patients who received immuno-chemotherapy.
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Affiliation(s)
- Tian‐Zhu Lu
- NHC Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal CarcinomaJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
- Department of Radiation OncologyJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
| | - Fu‐juan Zeng
- NHC Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal CarcinomaJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
- Department of Radiation OncologyJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
| | - Yu‐Jun Hu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Radiation OncologySun Yat‐sen University Cancer CenterGuangzhouChina
| | - Min Fang
- NHC Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal CarcinomaJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
- Department of Radiation OncologyJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
| | - Fang‐yan Zhong
- NHC Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal CarcinomaJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
- Department of Radiation OncologyJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
| | - Bi‐juan Chen
- Department of Radiation OncologyFujian Medical University Cancer Hospital & Fujian Cancer HospitalFuzhouChina
| | - Hao Zhang
- Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Qiao‐juan Guo
- Department of Radiation OncologyFujian Medical University Cancer Hospital & Fujian Cancer HospitalFuzhouChina
| | - Jian‐ji Pan
- Department of Radiation OncologyFujian Medical University Cancer Hospital & Fujian Cancer HospitalFuzhouChina
| | - Xiao‐chang Gong
- NHC Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal CarcinomaJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
- Department of Radiation OncologyJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
| | - Shao Hui Huang
- Department of Radiation Oncology, Princess Margaret Cancer CentreUniversity of TorontoTorontoOntarioCanada
| | - Zhao‐hui Liao
- NHC Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal CarcinomaJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
- Nursing Education Training CenterJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
| | - Yunfei Xia
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineSun Yat‐sen University Cancer CenterGuangzhouChina
- Department of Radiation OncologySun Yat‐sen University Cancer CenterGuangzhouChina
| | - Jin‐gao Li
- NHC Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal CarcinomaJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
- Department of Radiation OncologyJiangxi Clinical Research Center for Cancer, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical CollegeNanchangJiangxiChina
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An Exploratory Study of Refining TNM-8 M1 Categories and Prognostic Subgroups Using Plasma EBV DNA for Previously Untreated De Novo Metastatic Nasopharyngeal Carcinoma. Cancers (Basel) 2022; 14:cancers14081923. [PMID: 35454830 PMCID: PMC9031957 DOI: 10.3390/cancers14081923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 04/04/2022] [Accepted: 04/06/2022] [Indexed: 11/25/2022] Open
Abstract
(1) Background: NPC patients with de novo distant metastasis appears to be a heterogeneous group who demonstrate a wide range of survival, as suggested by growing evidence. Nevertheless, the current 8th edition of TNM staging (TNM-8) grouping all these patients into the M1 category is not able to identify their survival differences. We sought to identify any anatomic and non-anatomic subgroups in this study. (2) Methods: Sixty-nine patients with treatment-naive de novo M1 NPC (training cohort) were prospectively recruited from 2007 to 2018. We performed univariable and multivariable analyses (UVA and MVA) to explore anatomic distant metastasis factors, which were significantly prognostic of overall survival (OS). Recursive partitioning analysis (RPA) with the incorporation of significant factors from MVA was then performed to derive a new set of RPA stage groups with OS segregation (Set 1 Anatomic-RPA stage groups); another run of MVA was performed with the addition of pre-treatment plasma EBV DNA. A second-round RPA with significant prognostic factors of OS identified in this round of MVA was performed again to derive another set of stage groups (Set 2 Prognostic-RPA stage groups). Both sets were then validated externally with an independent validation cohort of 67 patients with distant relapses of their initially non-metastatic NPC (rM1) after radical treatment. The performance of models in survival segregation was evaluated by the Akaike information criterion (AIC) and concordance index (C-index) under 1000 bootstrapping samples for the validation cohort; (3) Results: The 3-year OS and median follow-up in the training cohort were 36.0% and 17.8 months, respectively. Co-existence of liver-bone metastases was the only significant prognostic factor of OS in the first round UVA and MVA. Set 1 RPA based on anatomic factors that subdivide the M1 category into two groups: M1a (absence of co-existing liver-bone metastases; median OS 28.1 months) and M1b (co-existing liver-bone metastases; median OS 19.2 months, p = 0.023). When pre-treatment plasma EBV DNA was also added, it became the only significant prognostic factor in UVA (p = 0.001) and MVA (p = 0.015), while co-existing liver-bone metastases was only significant in UVA. Set 2 RPA with the incorporation of pre-treatment plasma EBV DNA yielded good segregation (M1a: EBV DNA ≤ 2500 copies/mL and M1b: EBV DNA > 2500 copies/mL; median OS 44.2 and 19.7 months, respectively, p < 0.001). Set 2 Prognostic-RPA groups (AIC: 228.1 [95% CI: 194.8−251.8] is superior to Set 1 Anatomic-RPA groups (AIC: 278.5 [254.6−301.2]) in the OS prediction (p < 0.001). Set 2 RPA groups (C-index 0.59 [95% CI: 0.54−0.67]) also performed better prediction agreement in the validation cohort (vs. Set 1: C-index 0.47 [95% CI: 0.41−0.53]) (p < 0.001); (4) Conclusions: Our Anatomic-RPA stage groups yielded good segregation for de novo M1 NPC, and prognostication was further improved by incorporating plasma EBV DNA. These new RPA stage groups for M1 NPC can be applied to countries/regions regardless of whether reliable and sensitive plasma EBV DNA assays are available or not.
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