Published models inconsistently associate glioblastoma size with overall survival (OS). This study aimed to investigate the prognostic effect of tumour size in a large cohort of patients diagnosed with GBM and interrogate how sample size and non-linear transformations may impact on the likelihood of finding a prognostic effect. In total, 279 patients with a IDH-wildtype unifocal WHO grade 4 GBM between 2014 and 2020 from a retrospective cohort were included. Uni-/multivariable association between core volume, whole volume (CV and WV), and diameter with OS was assessed with (1) Cox proportional hazard models +/− log transformation and (2) resampling with 1,000,000 repetitions and varying sample size to identify the percentage of models, which showed a significant effect of tumour size. Models adjusted for operation type and a diameter model adjusted for all clinical variables remained significant (p= 0.03). Multivariable resampling increased the significant effects (p< 0.05) of all size variables as sample size increased. Log transformation also had a large effect on the chances of a prognostic effect of WV. For models adjusted for operation type, 19.5% of WV vs. 26.3% log-WV (n= 50) and 69.9% WV and 89.9% log-WV (n= 279) were significant. In this large well-curated cohort, multivariable modelling and resampling suggest tumour volume is prognostic at larger sample sizes and with log transformation for WV.
已发表的研究模型在胶质母细胞瘤大小与总生存期（OS）之间的关联性上存在不一致的结论。本研究旨在通过大样本胶质母细胞瘤（GBM）患者队列，探讨肿瘤大小的预后效应，并分析样本量及非线性变换如何影响发现预后效应的可能性。研究纳入了2014年至2020年间来自回顾性队列的279例IDH野生型、单灶性WHO 4级GBM患者。通过（1）Cox比例风险模型（应用/未应用对数变换）及（2）进行1,000,000次重复、不同样本量的重抽样分析，评估了肿瘤核心体积、整体体积（CV与WV）及直径与OS之间的单变量/多变量关联，以确定显示肿瘤大小具有显著预后效应的模型比例。经手术类型校正的模型以及经所有临床变量校正的直径模型均保持显著（p=0.03）。多变量重抽样分析显示，随着样本量增加，所有肿瘤大小变量的显著效应（p<0.05）均增强。对数变换对WV预后效应检出概率亦有显著影响。在经手术类型校正的模型中，当样本量为50时，WV显著比例为19.5%，而对数变换后WV（log-WV）为26.3%；当样本量为279时，WV显著比例升至69.9%，log-WV则达89.9%。在此大规模精心整理的队列中，多变量建模与重抽样分析表明，在较大样本量下肿瘤体积具有预后价值，且对WV进行对数变换可进一步增强其预后效应。
肿瘤(癌症)患者之家