Wang Stephanie J, Whitman Julia, Paciorek Alan, Le Bryan Khuong, Nakakura Eric K, Behr Spencer C, Joseph Nancy, Zhang Li, Hope Thomas A, Bergsland Emily K
School of Medicine, University of California San Francisco, San Francisco, California, USA.
Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA.
J Neuroendocrinol. 2023 Apr;35(4):e13260. doi: 10.1111/jne.13260. Epub 2023 Apr 1.
Refined risk stratification for gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has the potential to improve comparisons of study populations across clinical trials and facilitate drug development. Tumor growth rate (TGR) is a radiological metric with demonstrated prognostic value in well differentiated grade 1 and 2 (G1-2) GEP-NETs, but little is known about TGR in G3 NETs. In this retrospective study of 48 patients with advanced G1-3 GEP-NET, we calculated baseline TGR (TGR ) from radiological images of metastases acquired prior to first-line therapy and evaluated its association with disease characteristics and outcomes. The median pretreatment Ki67 proliferation index for G1-3 tumors combined was 5% (range = 0.1%-52%) and median TGR was 4.8%/month (m) (range = 0%-45.9%/m). TGR correlated with pretreatment Ki67 across G1-3 pooled and within G3 GEP-NET. Patients with higher TGR (>11.7%/m) tumors, which were primarily G3 pancreatic NETs, exhibited decreased time to first therapy (median, 2.2 vs. 5.3 months; p = .03) and shorter overall survival (median, 4.1 years vs. not reached; p = .003). Independent of therapies given, higher TGR GEP-NETs experienced a greater incidence of Ki67 increase (100 vs. 50%; p = .02) and greater magnitude of Ki67 change (median, 14.0 vs. 0.1%; p = .04) upon serial biopsy. Importantly, TGR , but not grade, predicted for future Ki67 increase in this series. Given the heterogeneity of well differentiated GEP-NETs, future clinical trials may benefit from stratification for TGR , particularly in G1-2 tumors, in which TGR does not correlate with Ki67. TGR has the potential to noninvasively identify patients with previously undiagnosed grade progression and those in whom more or less frequent monitoring may be appropriate. Additional research is needed to determine the prognostic and predictive value of TGR in larger and more homogeneously treated cohorts, and to ascertain if post-treatment TGR has value in previously treated patients starting a new line of therapy.
胃肠胰神经内分泌肿瘤(GEP-NETs)的精细风险分层有潜力改善不同临床试验研究人群之间的比较,并促进药物研发。肿瘤生长率(TGR)是一种影像学指标,已证实在高分化1级和2级(G1-2)GEP-NETs中具有预后价值,但关于G3 NETs中的TGR情况却知之甚少。在这项对48例晚期G1-3 GEP-NET患者的回顾性研究中,我们根据一线治疗前获取的转移灶影像学图像计算基线TGR(TGR ),并评估其与疾病特征及预后的关联。G1-3肿瘤联合的预处理Ki67增殖指数中位数为5%(范围=0.1%-52%),TGR中位数为4.8%/月(m)(范围=0%-45.9%/m)。在G1-3总体以及G3 GEP-NET内部,TGR与预处理Ki67相关。TGR较高(>11.7%/m)的患者,主要为G3胰腺NETs,其首次治疗时间缩短(中位数,2.2个月对5.3个月;p=0.03),总生存期缩短(中位数,4.1年对未达到;p=0.003)。不考虑所给予的治疗,较高TGR的GEP-NETs在系列活检时Ki67增加的发生率更高(100%对50%;p=0.02),Ki67变化幅度更大(中位数,14.0%对0.1%;p=0.04)。重要的是,在本系列中,TGR而非分级可预测未来Ki67的增加。鉴于高分化GEP-NETs的异质性,未来的临床试验可能会从TGR分层中获益,尤其是在G1-2肿瘤中,其中TGR与Ki67不相关。TGR有潜力无创地识别先前未诊断出分级进展的患者以及那些可能适合更频繁或更不频繁监测的患者。需要进一步研究以确定TGR在更大且治疗更同质化的队列中的预后和预测价值,并确定治疗后TGR对开始新一线治疗的既往治疗患者是否有价值。