Zhang Yue, Zhang Juan, Zeng Hui, Zhou Xiao-Huan, Zhou He-Bing
Department of Hematology, Beijing Luhe Hospital, Capital Medical University, Tongzhou, Beijing 101149, People's Republic of China.
Oncotarget. 2017 Oct 9;8(54):92978-92988. doi: 10.18632/oncotarget.21722. eCollection 2017 Nov 3.
The aim of this study was to establish nomograms, based on significant clinicopathologic parameters, for predicting the overall survival (OS) and the cancer-specific survival (CSS) of patients with classical Hodgkin lymphoma (CHL). The data of 43,330 CHL patients, diagnosed between 1983 and 2014, were obtainedfrom the database of the Surveillance, Epidemiology, and End Results (SEER) program. These patients were randomly divided into training (n = 30,339) and validation (n = 12,991) cohorts. The Kaplan-Meier method and Cox proportional hazards regression model were used to evaluate the prognostic effects of multiple clinicopathologic parameters on survival. Significant prognostic factors were combined to build nomograms. The predictive performance of nomograms was evaluated using the index of concordance (C-index) and calibration curves. In the training cohort, on univariate and multivariate analyses, age at diagnosis, gender, race, Ann Arbor stage, and histological type significantly correlated with the survival outcomes. These characteristics were used to establish nomograms. The nomograms showed good accuracy in predicting 1-, 5-, and 10-year OS and CSS, with a C-index of 0.794 (95% confidence interval [CI], 0.789-0.799) for OS and 0.760 (95% CI, 0.753-0.767) for CSS. In the validation cohort, the C-index for nomogram-based predictions was 0.787 (95% CI, 0.779-0.795) for OS and 0.769 (95% CI, 0.758-0.780) for CSS. All calibration curves revealed excellent consistency between predicted and actual survival. In summary, novel nomograms were established and validated to predict OS and CSS for patients with CHL. These new prognostic models could aid in improved prediction of survival outcomes leading to reasonable treatment recommendations.
本研究的目的是基于显著的临床病理参数建立列线图,以预测经典型霍奇金淋巴瘤(CHL)患者的总生存期(OS)和癌症特异性生存期(CSS)。从监测、流行病学和最终结果(SEER)项目数据库中获取了1983年至2014年间诊断的43330例CHL患者的数据。这些患者被随机分为训练队列(n = 30339)和验证队列(n = 12991)。采用Kaplan-Meier法和Cox比例风险回归模型评估多个临床病理参数对生存的预后影响。将显著的预后因素合并以构建列线图。使用一致性指数(C-index)和校准曲线评估列线图的预测性能。在训练队列中,单因素和多因素分析显示,诊断时年龄、性别、种族、Ann Arbor分期和组织学类型与生存结果显著相关。利用这些特征建立列线图。列线图在预测1年、5年和10年OS和CSS方面显示出良好的准确性,OS的C-index为0.794(95%置信区间[CI],0.789 - 0.799),CSS的C-index为0.760(95%CI,0.753 - 0.767)。在验证队列中,基于列线图预测的OS的C-index为0.787(95%CI,0.779 - 0.795),CSS的C-index为0.769(95%CI,0.758 - 0.780)。所有校准曲线显示预测生存期与实际生存期之间具有良好的一致性。总之,建立并验证了用于预测CHL患者OS和CSS的新型列线图。这些新的预后模型有助于更好地预测生存结果,从而给出合理的治疗建议。