Risk factors and risk prediction model for recurrence in medulloblastoma.

IF 1.5 4区 医学 Q2 PEDIATRICS
Translational pediatrics Pub Date : 2025-01-24 Epub Date: 2025-01-20 DOI:10.21037/tp-24-392
Ruyu Ai, Qiandong Liang, Guanhua Deng, Mingyao Lai, Qingjun Hu, Shaoqun Li, Minting Ye, Linbo Cai, Juan Li
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引用次数: 0

Abstract

Background: At present, there is a lack of established treatment protocols for recurrent medulloblastoma. The assessment of recurrence risk prior to treatment is of utmost importance in determining the most suitable treatment modality and intensity for medulloblastoma. Consequently, the creation of a predictive model for medulloblastoma recurrence is imperative in aiding clinical decision-making. The objective of this study is to construct an enhanced risk prediction model for relapse in medulloblastoma by integrating molecular subtyping and straightforward immune markers, such as neutrophil-to-lymphocyte ratio (NLR), into a nomogram.

Methods: A retrospective analysis was conducted on the clinical data of 273 patients diagnosed with medulloblastoma. The NLR was calculated prior to radiotherapy, and various clinical characteristics including age, gender, molecular subtype, dissemination, and residual lesions after resection were collected. Survival analysis was performed utilizing the Kaplan-Meier method, while Cox regression models were employed to identify independent prognostic factors. Furthermore, a column chart illustrating all independent prognostic factors was generated using R. The nomogram's prognostic predictive ability was evaluated using the Concordance Index (C-index), area under the curve (AUC), and calibration curve.

Results: The median progression-free survival (PFS) for the entire cohort was determined to be 63.8 months. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic factors that were associated with PFS in patients diagnosed with medulloblastoma. These factors included age, residual tumor volume exceeding 1.5 cm3, NLR exceeding 4.5, dissemination occurring prior radiotherapy, and molecular subtype classified as Group 3. These identified factors were then utilized to construct a column chart. The nomogram C-index for the predicted PFS in the training and validation cohorts was 0.749 and 0.736, respectively. The AUC for predicting the 3-year PFS exhibited satisfactory accuracy in the validation cohort (AUC =0.71). Furthermore, the calibration curve indicated a strong concordance between the predicted and ideal values. Additionally, the Kaplan-Meier curve, based on PFS, demonstrated a statistically significant distinction between the low-risk and high-risk groups as predicted by the nomogram (P<0.001).

Conclusions: Our study revealed that the NLR prior to treatment serves as an autonomous prognostic determinant for the recurrence or metastasis of medulloblastoma subsequent to treatment. By integrating NLR with clinical variables, the utilization of a nomogram demonstrates the capability to anticipate PFS following radiotherapy in medulloblastoma patients. This nomogram exhibits potential in facilitating more accurate risk stratification, thereby guiding the implementation of personalized treatment strategies for individuals with medulloblastoma.

成神经管细胞瘤复发的危险因素及风险预测模型。
背景:目前,对于复发性成神经管细胞瘤缺乏成熟的治疗方案。治疗前的复发风险评估对于确定髓母细胞瘤最合适的治疗方式和强度至关重要。因此,髓母细胞瘤复发的预测模型的创建是必要的,以帮助临床决策。本研究的目的是通过将分子分型和直接的免疫标记(如中性粒细胞与淋巴细胞比率(NLR))整合到图中,构建髓母细胞瘤复发的增强风险预测模型。方法:对273例髓母细胞瘤患者的临床资料进行回顾性分析。放疗前计算NLR,收集患者的年龄、性别、分子亚型、播散、切除后病变残留等临床特征。生存分析采用Kaplan-Meier法,Cox回归模型确定独立预后因素。此外,使用r生成一个柱状图,显示所有独立的预后因素。使用一致性指数(C-index)、曲线下面积(AUC)和校准曲线评估nomogram预后预测能力。结果:整个队列的中位无进展生存期(PFS)确定为63.8个月。对髓母细胞瘤患者进行单因素和多因素Cox回归分析,以确定与PFS相关的独立预后因素。这些因素包括年龄,残余肿瘤体积超过1.5 cm3, NLR超过4.5,放疗前发生播散,分子亚型分类为3组。然后利用这些确定的因素构建柱状图。训练组和验证组预测PFS的nomogram C-index分别为0.749和0.736。预测3年PFS的AUC在验证队列中显示出令人满意的准确性(AUC =0.71)。此外,校正曲线显示预测值与理想值之间有较强的一致性。此外,基于PFS的Kaplan-Meier曲线显示,正如nomogram预测的那样,低风险组和高风险组之间存在统计学上的显著差异(结论:我们的研究表明,治疗前的NLR可以作为髓母细胞瘤治疗后复发或转移的自主预后决定因素。通过将NLR与临床变量相结合,nomogram成像技术证明了预测髓母细胞瘤患者放疗后PFS的能力。该图显示出促进更准确的风险分层的潜力,从而指导髓母细胞瘤患者个性化治疗策略的实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Translational pediatrics
Translational pediatrics Medicine-Pediatrics, Perinatology and Child Health
CiteScore
4.50
自引率
5.00%
发文量
108
期刊介绍: Information not localized
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