Utilizing the Lactate Dehydrogenase-to-Albumin Ratio for Survival Prediction in Patients with Neuroblastoma

TL;DR

This study shows that the lactate dehydrogenase-to-albumin ratio (LAR) can predict survival in neuroblastoma patients, and a new nomogram model based on LAR improves prognosis prediction.

Contribution

The study introduces LAR as a novel prognostic biomarker and develops a validated nomogram model for neuroblastoma survival prediction.

Findings

High LAR was significantly associated with worse prognosis in neuroblastoma patients.

A nomogram incorporating LAR and other factors achieved a C-index of 0.727 for survival prediction.

LAR, along with INSS stage, bone metastasis, and MYCN, was identified as an independent prognostic factor.

Abstract

Purpose: This study aimed to investigate the association between lactate dehydrogenase-to-albumin ratio (LAR) and the clinical characteristics and overall survival (OS) of patients with neuroblastoma (NB). Methods: We conducted a retrospective data analysis of 443 patients diagnosed with neuroblastoma. The optimal cut-off value for the LAR was determined using receiver operating characteristic (ROC) curves. We utilized Kaplan–Meier curves and Cox regression analysis to evaluate the relationship between LAR and OS. Independent factors identified through multivariate analysis were employed to construct a nomogram. The performance of the nomogram model was assessed using calibration curves, ROC curves, concordance index (C-index), and decision curve analysis (DCA). Results: The 2-year time-dependent ROC curve indicated that the optimal cut-off value for the LAR was 21.814. Kaplan–Meier survival curve analysis revealed that the prognosis for the high LAR group was significantly worse than that for the low LAR group. Results from multivariate Cox analysis identified INSS stage, bone metastasis, MYCN, and LAR as independent prognostic factors for OS. A nomogram for predicting the prognosis of NB was established based on multivariate Cox regression analysis. Internal validation through the Bootstrap method revealed that the nomogram’s C-index was 0.727. Both the calibration curve and ROC curve suggested that the model possessed significant predictive potential. DCA further demonstrated that the nomogram model exhibited substantial clinical applicability. Conclusions: LAR served as an aussichtsreich prognostic indicator for neuroblastoma, and the nomogram model based on LAR can predict the OS of patients with this condition.

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