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Background <p>Pediatric brain tumors are the leading cause of cancer-related death in children. Reliable tools for predicting postoperative mortality in children remain limited. The aim of the study is to develop and validate a clinically applicable prognostic nomogram.</p> Methods <p>We developed and externally validated a prognostic nomogram using data from two prospective cohorts in South China. The model included 375 patients (internal cohort) and 224 patients (external validation). Multivariate Cox regression identified independent predictors, which were integrated into the nomogram to estimate 12-, 36-, and 60-month survival.</p> Results <p>Here we show that five factors-age, World Health Organization classification, extent of resection, systemic immune-inflammation index, and Count of major neurological dysfunctions (muscle weakness, disorientation)—are independently associated with mortality. The model shows good discrimination with C-index values of 0.789 (training), 0.841 (test), and 0.789 (external). Area Under Curves at all timepoints exceed 0.80. Sensitivities and specificities ranged from 0.824–0.905 and 0.619–0.671, respectively. Calibration and clinical utility are satisfactory.</p> Conclusion <p>This nomogram enables individualized prediction of postoperative mortality in pediatric brain tumor patients, aiding surgical and perioperative decision-making.</p>

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Prognostic nomogram predicts postoperative mortality in children with brain tumors in a multicentre study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月29日

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  • Na Zhang,
  • Huiyuan Zhong,
  • Siyi Zhang,
  • Lerong Liu,
  • Xinxu Ou,
  • Yawei Guo,
  • Wei Rong,
  • Shuai Yang,
  • Chongyang Yuan,
  • Zhongzhi Xu,
  • Mingming Yang,
  • Yingyi Xu

摘要

Background

Pediatric brain tumors are the leading cause of cancer-related death in children. Reliable tools for predicting postoperative mortality in children remain limited. The aim of the study is to develop and validate a clinically applicable prognostic nomogram.

Methods

We developed and externally validated a prognostic nomogram using data from two prospective cohorts in South China. The model included 375 patients (internal cohort) and 224 patients (external validation). Multivariate Cox regression identified independent predictors, which were integrated into the nomogram to estimate 12-, 36-, and 60-month survival.

Results

Here we show that five factors-age, World Health Organization classification, extent of resection, systemic immune-inflammation index, and Count of major neurological dysfunctions (muscle weakness, disorientation)—are independently associated with mortality. The model shows good discrimination with C-index values of 0.789 (training), 0.841 (test), and 0.789 (external). Area Under Curves at all timepoints exceed 0.80. Sensitivities and specificities ranged from 0.824–0.905 and 0.619–0.671, respectively. Calibration and clinical utility are satisfactory.

Conclusion

This nomogram enables individualized prediction of postoperative mortality in pediatric brain tumor patients, aiding surgical and perioperative decision-making.