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基于图像的转移性鼻咽癌 TNM 分期系统 M1 亚类的多层次细分。

Image-based Multilevel Subdivision of M1 Category in TNM Staging System for Metastatic Nasopharyngeal Carcinoma.

机构信息

From the Department of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center, Guangzhou 510060, People's Republic of China (L.S., W.L., Q.Z., F.S., W.S., P.W.); State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University, Guangzhou, People's Republic of China (L.S., C.C., Y.Z., M.W., Y.X., P.W.); Department of Radiation Oncology, Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, People's Republic of China (S.W., Q.Z., C.C., Y.X.); Department of Radiation Oncology, Cancer Center of Guangzhou Medical University, Guangzhou, People's Republic of China (G.X.); Department of Medical Oncology, Sichuan Cancer Hospital and Institute, Chengdu,, People's Republic of China (C.P.); and Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, People's Republic of China (Y.Z., M.W., W.S.).

出版信息

Radiology. 2016 Sep;280(3):805-14. doi: 10.1148/radiol.2016151344. Epub 2016 Mar 29.

Abstract

Purpose To establish an image-based M1 category subdivision system for personalized prognosis prediction and treatment planning in patients with metastatic nasopharyngeal carcinoma (NPC). Materials and Methods A total of 1172 patients with metachronous metastasic NPC were retrospectively enrolled (the dataset is from Sun Yat-sen University Cancer Center for derivation, and the combined datasets are from Guangzhou Medical University Cancer Center and the Fifth Affiliated Hospital of Sun Yat-sen University for validation). The Ethics Committee of the three centers approved this study. A general subdivision system of the M1 category was established on the basis of the most influential metastatic features for overall survival (OS). The following multilevel subdivision system for precise subdivision of the M1 category was designed: M [number of locations]-Location [number of lesions], with B indicating bone, L indicating the lung, H indicating the liver, and N indicating a node. The correlation of the M1 subdivisions with OS was determined with Cox regression. The best treatment response was assessed with Response Evaluation Criteria in Solid Tumors 1.1 guidelines and modified Response Evaluation Criteria in Solid Tumors criteria. Results Multivariate analysis in the derivation cohort showed that the number of metastatic lesions (multiple or single), the number of metastatic locations (multiple or single), liver involvement, and bone involvement were independent prognostic factors for OS. In general, subdividing the cohort by the number of metastatic lesions and the number of metastatic locations resulted in three subcategories of differential OS: M1a, a single lesion in a single organ or location; M1b, multiple lesions in a single organ or location; and M1c, metastases in multiple locations (for M1b vs M1a, hazard ratio [HR] = 2.28, 95% confidence interval [CI]: 1.71, 3.05; for M1c vs M1a, HR = 3.65, 95% CI: 2.75, 4.85); these subdivisions were externally validated. The multilevel subdivision system could be further used to discriminate among subgroups of differential OS under the M1b subcategory. Findings from analysis of multilevel subgroups suggested that patients with a single metastatic lesion (M1-B1, M1-L1, M1-H1, M1-N1) or two lesions in the liver only (M1-H2) had high rates of complete response (CR) or complete surgical resection (CSR) and 3-year OS after treatment (CR plus CSR rates >30%, and 3-year OS rates >50%); there were high 3-year OS rates (>50%) in patients with stage M1-B2, M1-L2, or M1-H3 disease but relatively low rates of CR or CSR. Conclusion Use of the multilevel M1 subdivision system in patients with NPC could facilitate more precise prognosis prediction and better identification of patients who will respond well to treatment than the conventional subdivision strategy. (©) RSNA, 2016 Online supplemental material is available for this article.

摘要

目的 建立基于影像的转移性鼻咽癌(NPC)患者 M1 亚类细分系统,以进行个性化预后预测和治疗计划。

材料与方法 回顾性纳入 1172 例 NPC 患者(数据集来源于中山大学肿瘤防治中心,联合数据集来源于广州医科大学肿瘤医院和中山大学第五附属医院)。三个中心的伦理委员会批准了这项研究。在影响总生存(OS)的最具影响力的转移特征的基础上,建立了 M1 亚类的一般细分系统。设计了以下 M1 类的精确细分的多层次细分系统:M[位置数量]-Location[病变数量],其中 B 表示骨,L 表示肺,H 表示肝,N 表示淋巴结。使用 Cox 回归确定 M1 亚类与 OS 的相关性。使用实体瘤反应评价标准 1.1 指南和改良实体瘤反应评价标准评估最佳治疗反应。

结果 在推导队列中的多变量分析显示,转移灶数量(多个或单个)、转移灶部位数量(多个或单个)、肝受累和骨受累是 OS 的独立预后因素。一般来说,根据转移灶数量和转移灶部位数量对队列进行细分,会导致 OS 存在三个不同的亚类:M1a,单个器官或部位的单个病变;M1b,单个器官或部位的多个病变;M1c,多个部位转移(M1b 与 M1a 相比,危险比[HR] = 2.28,95%置信区间[CI]:1.71,3.05;M1c 与 M1a 相比,HR = 3.65,95%CI:2.75,4.85);这些亚类在外部得到验证。多层次细分系统可进一步用于区分 M1b 亚类中具有不同 OS 的亚组。多水平亚组分析的结果表明,治疗后具有单个转移灶(M1-B1、M1-L1、M1-H1、M1-N1)或仅肝内两个转移灶(M1-H2)的患者具有高完全缓解(CR)或完全手术切除(CSR)率和 3 年 OS(CR+CSR 率>30%,3 年 OS 率>50%);M1-B2、M1-L2 或 M1-H3 疾病患者的 3 年 OS 率较高(>50%),但 CR 或 CSR 率相对较低。

结论 与常规细分策略相比,在 NPC 患者中使用多层次 M1 亚类细分系统可更精确地预测预后,并更好地识别对治疗反应良好的患者。

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