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<p>As survival for classical Hodgkin lymphoma (cHL) improves, cardiac disease is a leading cause of non-relapse mortality, yet the risk of cardiac-specific mortality (CSM) in adolescents and young adults (AYAs) is unclear. This study developed and validated a nomogram to predict CSM for AYAs with cHL using data from the SEER database, with a training cohort of 7,475 patients for model development and a validation cohort of 3,205 patients for internal validation. A Fine-Gray competing risk model was used, with the cumulative incidence of CSM surpassing that of cHL over time. Analysis identified Black race, male sex, older age, earlier diagnosis year, and radiotherapy as significant risk factors for CSM. The resulting nomogram estimates the 15- and 25-year risks of CSM using age, race, sex, diagnosis year, Ann Arbor stage, and radiotherapy. Validation demonstrated strong discriminatory ability via ROC curves, with calibration plots and decision curve analysis confirming its accuracy and clinical utility. This nomogram is a useful tool for predicting CSM in the AYA population and may aid physicians in managing clinical risk factors.</p>

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Cardiac-specific mortality prediction in adolescents and young adults with classical hodgkin lymphoma: a nomogram development and validation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Rui Yan,
  • Jiaying Niu,
  • Weijia Zhang,
  • Yufeng Zhang,
  • Jinglian Li,
  • Sijin Li

摘要

As survival for classical Hodgkin lymphoma (cHL) improves, cardiac disease is a leading cause of non-relapse mortality, yet the risk of cardiac-specific mortality (CSM) in adolescents and young adults (AYAs) is unclear. This study developed and validated a nomogram to predict CSM for AYAs with cHL using data from the SEER database, with a training cohort of 7,475 patients for model development and a validation cohort of 3,205 patients for internal validation. A Fine-Gray competing risk model was used, with the cumulative incidence of CSM surpassing that of cHL over time. Analysis identified Black race, male sex, older age, earlier diagnosis year, and radiotherapy as significant risk factors for CSM. The resulting nomogram estimates the 15- and 25-year risks of CSM using age, race, sex, diagnosis year, Ann Arbor stage, and radiotherapy. Validation demonstrated strong discriminatory ability via ROC curves, with calibration plots and decision curve analysis confirming its accuracy and clinical utility. This nomogram is a useful tool for predicting CSM in the AYA population and may aid physicians in managing clinical risk factors.