Nomograms for predicting the overall and cancer-specific survival of patients with classical Hodgkin lymphoma: a SEER-based study
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Yue Zhang1, Juan Zhang1, Hui Zeng1, Xiao-Huan Zhou1 and He-Bing Zhou1
1Department of Hematology, Beijing Luhe Hospital, Capital Medical University, Tongzhou, Beijing 101149, People’s Republic of China
He-Bing Zhou, email: [email protected]
Keywords: classical Hodgkin lymphoma, nomogram, overall survival, cancer-specific survival
Received: July 17, 2017 Accepted: August 27, 2017 Published: October 09, 2017
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.
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