A Nomogram for Predicting Cancer-Specific Survival of Hodgkin lymphoma in Children and Young Adulthood: an Observational Study using SEER Population-based Data

Abstract

Background Hodgkin lymphoma (HL) is the most common neoplasm in children and young adults; GLOBOCAN 2020 shows a total of 83,087 new cases and 23,376 deaths of HL worldwide. This study developed a prognostic nomogram of HL in children and young adulthood for purpose to discuss independent risk factors for HL patients with the Surveillance, Epidemiology and End Results (SEER) database. Methods We downloaded the clinicopathological data of children and young adulthood with HL from 1975 to 2020 in the SEER database. Univariate and multivariate Cox regression analyses were used to screen children and young adulthood independent risk factors for Cancer-Specific Survival (CSS). These risk factors were used to construct a nomogram to predict the CSS of children and young adulthood with HL. A series of validation methods, including calibration curve, consistency index (C-index), and area under the receiver operating characteristic curve (AUC), were used to validate the accuracy and reliability of the prediction model. Decision curve analysis (DCA) was used to validate the clinical application efficacy of predictive models. All patients were divided into low- and high-risk groups based on the nomogram score. Kaplan-Meier curve and log-rank test were used to compare survival differences between the two groups. Results A total of 13,529 children and young adulthood with HL were included. Univariate and multivariate analysis suggested that Age, sex, stage, radiation, chemotherapy, histological type were independent risk factors. Nomograms were established based on these factors to predict 3-, 5-, and 10-years CSS of children and young adulthood with HL. The calibration plots showed that the predicted value was highly consistent with the actual value. In the training and validation cohorts, the C-index was 0.682 (0.665–0.700) and 0.694 (0.672–0.716), respectively. The AUC of the training and validation cohorts also showed similar results. The DCA showed that the nomogram had good clinical value. Conclusion We constructed a new nomogram to predict the CSS of HL in children and young adults. This predictive model is accurate and reliable and can help doctors and patients develop clinical strategies.