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血液分子基因组分析可预测胃肠胰腺神经内分泌肿瘤患者的疾病进程:NETest®预测价值的验证研究

Blood Molecular Genomic Analysis Predicts the Disease Course of Gastroenteropancreatic Neuroendocrine Tumor Patients: A Validation Study of the Predictive Value of the NETest®.

作者信息

van Treijen Mark J C, van der Zee Dennis, Heeres Birthe C, Staal Femke C R, Vriens Menno R, Saveur Lisette J, Verbeek Wieke H M, Korse Catharina M, Maas Monique, Valk Gerlof D, Tesselaar Margot E T

机构信息

Department of Endocrine Oncology, University Medical Center Utrecht, Utrecht, The Netherlands,

Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands,

出版信息

Neuroendocrinology. 2021;111(6):586-598. doi: 10.1159/000509091. Epub 2020 Jun 3.

Abstract

Reliable prediction of disease status is a major challenge in managing gastroenteropancreatic neuroendocrine tumors (GEP-NETs). The aim of the study was to validate the NETest®, a blood molecular genomic analysis, for predicting the course of disease in individual patients compared to chromogranin A (CgA). NETest® score (normal ≤20%) and CgA level (normal <100 µg/L) were measured in 152 GEP-NETs. The median follow-up was 36 (4-56) months. Progression-free survival was blindly assessed (Response Evaluation Criteria in Solid Tumors [RECIST] version 1.1). Optimal cutoffs (area under the receiver operating characteristic curve [AUC]), odds ratios, as well as negative and positive predictive values (NPVs/PPVs) were calculated for predicting stable disease (SD) and progressive disease (PD). Of the 152 GEP-NETs, 86% were NETest®-positive and 52% CgA-positive. -NETest® AUC was 0.78 versus CgA 0.73 (p = ns). The optimal cutoffs for predicting SD/PD were 33% for the NETest® and 140 µg/L for CgA. Multivariate analyses identified NETest® as the strongest predictor for PD (odds ratio: 5.7 [score: 34-79%]; 12.6 [score: ≥80%]) compared to CgA (odds ratio: 3.0), tumor grade (odds ratio: 3.1), or liver metastasis (odds ratio: 7.7). The NETest® NPV for SD was 87% at 12 months. The PPV for PD was 47 and 64% (scores 34-79% and ≥80%, respectively). NETest® metrics were comparable in the watchful waiting, treatment, and no evidence of disease (NED) subgroups. For CgA (>140 ng/mL), NPV and PPV were 83 and 52%. CgA could not predict PD in the watchful waiting or NED subgroups. The NETest® reliably predicted SD and was the strongest predictor of PD. CgA had lower utility. The -NETest® anticipates RECIST-defined disease status up to 1 year before imaging alterations are apparent.

摘要

可靠预测疾病状态是胃肠胰神经内分泌肿瘤(GEP-NETs)管理中的一项重大挑战。本研究的目的是验证一种血液分子基因组分析方法NETest®,用于预测个体患者的疾病进程,并与嗜铬粒蛋白A(CgA)进行比较。在152例GEP-NETs患者中测量了NETest®评分(正常≤20%)和CgA水平(正常<100μg/L)。中位随访时间为36(4 - 56)个月。采用盲法评估无进展生存期(实体瘤疗效评价标准[RECIST]1.1版)。计算预测疾病稳定(SD)和疾病进展(PD)的最佳截断值(受试者工作特征曲线下面积[AUC])、比值比以及阴性和阳性预测值(NPV/PPV)。在152例GEP-NETs患者中,86%的患者NETest®呈阳性,52%的患者CgA呈阳性。NETest®的AUC为0.78,而CgA为0.73(p = 无统计学意义)。预测SD/PD的最佳截断值,NETest®为33%,CgA为140μg/L。多因素分析确定,与CgA(比值比:3.0)、肿瘤分级(比值比:3.1)或肝转移(比值比:7.7)相比,NETest®是PD最强的预测指标(比值比:5.7[评分:34 - 79%];12.6[评分:≥80%])。NETest®对12个月时SD的NPV为87%。对PD的PPV分别为47%和64%(评分分别为34 - 79%和≥80%)。NETest®指标在观察等待、治疗和无疾病证据(NED)亚组中具有可比性。对于CgA(>140 ng/mL),NPV和PPV分别为83%和52%。CgA无法在观察等待或NED亚组中预测PD。NETest®能可靠地预测SD,是PD最强的预测指标。CgA的效用较低。NETest®能在影像学改变出现前长达1年预测RECIST定义的疾病状态。

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