ArticleDiscover oncology2025
Identifying predictive factors for recurrence risk in pediatric craniopharyngioma after surgery using a clinical prediction model.
Article in Discover oncology, 2025. 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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Abstract
backgroundCraniopharyngioma (CP) tumors are histologically benign (WHO grade I) and can occur at any age. Postoperative pediatric craniopharyngioma (CO-CP) patients have a high long-term survival rate but are at risk of poor quality of life. In this study, we propose a novel nomogram that graphically expresses the numerical relationship between patients with postoperative CO-CP and risk factors for recurrence.
methodsA retrospective analysis was conducted on data from 192 patients treated at XXX Hospital between January 2012 and July 2019. Utilizing R software, a random sampling method was employed to select 115 patients (3/5) for the training cohort and 77 patients (2/5) for the internal test cohort. LASSO regression analysis identified significant risk factors for recurrence, leading to the construction of a nomogram based on these factors. The accuracy of the nomogram was evaluated using receiver operating characteristic (ROC) curves and clinical decision curve analysis (DCA).
resultsThe analysis revealed that tumor diameter was the most significant risk factor for recurrence in post-operative CO-CP patients (95% CI 2.72-35.01, OR = 9.22). Other notable risk factors included visual disturbances (95% CI 0.98-17.35, OR = 4.13), preoperative neuroendocrine function impairment scoring (95% CI 0.76-8.37, OR = 2.45), and the extent of resection (gross-total resection: 95% CI 0.08-0.86, OR = 0.27). The ROC analysis indicated areas under the curve of 0.777 and 0.766 for the training and internal test cohorts, respectively. The clinical DCA curves associated with the nomogram in the training and internal test cohorts ranged from 2 to 78% and 1%-80%, respectively.
conclusionsOur proposed nomogram accurately predicts risk factors for postoperative CO-CP recurrence. By incorporating LASSO-selected endocrinological variables, it builds on prior classifications such as Puget et al. (2007) and may serve as a practical tool for identifying patients at increased risk of recurrence.
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