Construction of nomogram for the clinical outcome for pediatric acute lymphoblastic leukemia patients

Acute lymphoblastic leukemia (ALL) is one of the most common hematologic cancers in children, accounting for about 25% of all pediatric cancers. However, survival data for pediatric ALL patients remain limited. We selected clinicopathological data from pediatric ALL patients diagnosed between 2000 and 2019 from the SEER database. Univariable and multivariable Cox proportional hazards regression analyses were applied to identify independent prognostic factors for overall survival (OS) in ALL patients. A predictive nomogram was then constructed. Calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were used to evaluate the nomogram’s performance. A total of 13,869 ALL patients were included in the study, with 1447 (10%) patients dying from various causes. On univariable analysis, survival was significantly worse in male patients, those aged 13–17, and Black patients. Multivariable analysis identified age, race, and radiotherapy as independent prognostic factors for OS, whereas sex was not independently associated with survival. The nomogram predicted the 1-year, 3-year, and 5-year OS rates with AUCs of 0.807, 0.796, and 0.772 in the training cohort, and 0.854, 0.837, and 0.816 in the validation cohort, respectively. Good agreement was observed between observed outcomes and predicted probabilities in the calibration curves. DCA further demonstrated the nomogram’s clinical utility. The nomogram demonstrates good accuracy and reliability in predicting OS for pediatric ALL patients, providing valuable theoretical support for clinicians in making treatment decisions.

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Publication Details

Journal
Medicine
Published
2026-08-28
DOI
https://doi.org/10.1097/md.0000000000050259
Primary Topic
Acute Lymphoblastic Leukemia research
Type
article
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article

Construction of nomogram for the clinical outcome for pediatric acute lymphoblastic leukemia patients

Rouxin Li, Jiahua Hu, Wenhua Zhang, Yutong Sang et al.
Medicine
Acute Lymphoblastic Leukemia research
article

Construction of nomogram for the clinical outcome for pediatric acute lymphoblastic leukemia patients

Rouxin Li, Jiahua Hu, Wenhua Zhang, Yutong Sang, Yiwen Gao
article en

Abstract

Acute lymphoblastic leukemia (ALL) is one of the most common hematologic cancers in children, accounting for about 25% of all pediatric cancers. However, survival data for pediatric ALL patients remain limited. We selected clinicopathological data from pediatric ALL patients diagnosed between 2000 and 2019 from the SEER database. Univariable and multivariable Cox proportional hazards regression analyses were applied to identify independent prognostic factors for overall survival (OS) in ALL patients. A predictive nomogram was then constructed. Calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were used to evaluate the nomogram’s performance. A total of 13,869 ALL patients were included in the study, with 1447 (10%) patients dying from various causes. On univariable analysis, survival was significantly worse in male patients, those aged 13–17, and Black patients. Multivariable analysis identified age, race, and radiotherapy as independent prognostic factors for OS, whereas sex was not independently associated with survival. The nomogram predicted the 1-year, 3-year, and 5-year OS rates with AUCs of 0.807, 0.796, and 0.772 in the training cohort, and 0.854, 0.837, and 0.816 in the validation cohort, respectively. Good agreement was observed between observed outcomes and predicted probabilities in the calibration curves. DCA further demonstrated the nomogram’s clinical utility. The nomogram demonstrates good accuracy and reliability in predicting OS for pediatric ALL patients, providing valuable theoretical support for clinicians in making treatment decisions.

MedicineVol. 105(35)
Weifang Medical University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Acute Lymphoblastic Leukemia research
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