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

Autor:	van Treijen MJC; Department of Endocrine Oncology, University Medical Center Utrecht, Utrecht, The Netherlands, m.j.c.vantreijen@umcutrecht.nl.; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands, m.j.c.vantreijen@umcutrecht.nl., van der Zee D; Department of Radiology, Bernhoven Hospital, Uden, The Netherlands., Heeres BC; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Staal FCR; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Vriens MR; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Endocrine Surgical Oncology, University Medical Center Utrecht, Utrecht, The Netherlands., Saveur LJ; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Gastroenterology, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Verbeek WHM; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Gastroenterology, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Korse CM; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Clinical Chemistry, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Maas M; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands., Valk GD; 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., Tesselaar MET; Center for Neuroendocrine Tumors, ENETS Center of Excellence, Netherlands Cancer Institute, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Medical Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Jazyk:	angličtina
Zdroj:	Neuroendocrinology [Neuroendocrinology] 2021; Vol. 111 (6), pp. 586-598. Date of Electronic Publication: 2020 Jun 03.
DOI:	10.1159/000509091
Abstrakt:	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. (© 2020 The Author(s) Published by S. Karger AG, Basel.)
Databáze:	MEDLINE
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