Supplementary Material for: Tumor Growth Rate to Predict the Outcome of Patients with Neuroendocrine Tumors: Performance and Sources of Variability

Introduction: Tumor growth rate (TGR), percentage of change in tumor volume/month, has been previously identified as an early radiological biomarker for treatment monitoring in neuroendocrine tumor (NET) patients. We assessed the performance and reproducibility of TGR at 3 months (TGR3m) as a predictor factor of progression-free survival (PFS), including the impact of imaging method and reader variability. Methods: Baseline and 3-month (±1 month) CT/MRI images from patients with advanced, grade 1–2 NETs were retrospectively reviewed by 2 readers. Influence of number of targets, tumor burden, and location of lesion on the performance of TGR3m to predict PFS was assessed by uni/multivariable Cox regression analysis. Agreement between readers was assessed by Lin’s concordance coefficient (LCC) and kappa coefficient (KC). Results: A total of 790 lesions were measured in 222 patients. Median PFS was 22.9 months. On univariable analysis, number of lesions (3m ≥0.8%/month (HR: 4.01 [95% CI: 2.31–6.97]), and watch and wait correlated with shorter PFS. No correlation was found between TGR3m and number of lesions (rho: −0.2; p value: 0.1930). No difference in mean TGR3m across organs was shown (p value: 0.6). Concordance between readers was acceptable (LCC: 0.52 [95% CI: 0.38–0.65]; KC: 0.57, agreement: 81.55%). TGR3m remained a significant prognostic factor when data from the second reader were employed (HR: 4.35 [95% CI: 2.44–7.79]; p value <0.001) regardless his expertise (HR: 1.21 [95% CI: 0.70–2.09]; p value: 0.493). Discussion/Conclusion: TGR3m is a robust and early radiological biomarker able to predict PFS. It may be used to identify patients with advanced NETs who require closer radiological follow-up.

引言：肿瘤生长速率（Tumor growth rate, TGR），即每月肿瘤体积变化百分比，此前已被证实为神经内分泌肿瘤（Neuroendocrine tumor, NET）患者治疗监测的早期放射学生物标志物。本研究评估了3个月时的TGR（TGR3m）作为无进展生存期（Progression-free survival, PFS）预测因子的性能与可重复性，同时探讨了成像方法以及阅片者变异性的影响。
方法：对222例晚期1~2级NET患者的基线及3个月（±1个月）CT/MRI影像进行回顾性分析，由2名阅片者独立阅片。通过单变量/多变量Cox回归分析，评估靶病灶数量、肿瘤负荷以及病灶位置对TGR3m预测PFS性能的影响。采用Lin一致性系数（Lin’s concordance coefficient, LCC）与kappa系数（Kappa coefficient, KC）评估阅片者间的一致性。
结果：共对222例患者的790个病灶进行测量。患者中位PFS为22.9个月。单变量分析显示，病灶数量（≥4个）、肿瘤负荷以及肝转移情况与PFS显著相关。多变量分析显示，病灶数量≥4个（风险比HR: 1.89 [95%置信区间CI: 1.01–3.57]）、TGR3m≥0.8%/月（HR: 4.01 [95% CI: 2.31–6.97]）以及观望治疗策略与更短的PFS相关。未发现TGR3m与病灶数量存在相关性（rho: −0.2; P值: 0.1930）。不同器官的平均TGR3m无显著差异（P值: 0.6）。阅片者间一致性尚可（LCC: 0.52 [95% CI: 0.38–0.65]; KC: 0.57; 一致率: 81.55%）。无论第二位阅片者的专业背景如何（HR: 1.21 [95% CI: 0.70–2.09]; P值: 0.493），采用其阅片数据时，TGR3m仍为显著的预后因子（HR: 4.35 [95% CI: 2.44–7.79]; P值 <0.001）。
讨论与结论：TGR3m是一种稳健的早期放射学生物标志物，可有效预测PFS，可用于识别需要加强放射学随访的晚期NET患者。