ArticleMedicine2026
Construction of nomogram for the clinical outcome for pediatric acute lymphoblastic leukemia patients.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
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.
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