Literature DB >> 32492680

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

Mark J C van Treijen1,2, Dennis van der Zee3, Birthe C Heeres4,5, Femke C R Staal4,5, Menno R Vriens4,6, Lisette J Saveur4,7, Wieke H M Verbeek4,7, Catharina M Korse4,8, Monique Maas4,5, Gerlof D Valk9,4, Margot E T Tesselaar4,10.   

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.
© 2020 The Author(s) Published by S. Karger AG, Basel.

Entities:  

Keywords:  Biomarkers; Chromogranin A; Gastroenteropancreatic neuroendocrine tumors; Liquid biopsy; Survival

Mesh:

Substances:

Year:  2020        PMID: 32492680     DOI: 10.1159/000509091

Source DB:  PubMed          Journal:  Neuroendocrinology        ISSN: 0028-3835            Impact factor:   4.914


  6 in total

1.  Defining disease status in gastroenteropancreatic neuroendocrine tumors: Choi-criteria or RECIST?

Authors:  M J C van Treijen; J M H Schoevers; B C Heeres; D van der Zee; M Maas; G D Valk; M E T Tesselaar
Journal:  Abdom Radiol (NY)       Date:  2022-01-06

2.  A multigenomic liquid biopsy biomarker for neuroendocrine tumor disease outperforms CgA and has surgical and clinical utility.

Authors:  I M Modlin; M Kidd; M Falconi; P L Filosso; A Frilling; A Malczewska; C Toumpanakis; G Valk; K Pacak; L Bodei; K E Öberg
Journal:  Ann Oncol       Date:  2021-08-11       Impact factor: 51.769

3.  A novel liquid biopsy (NETest) identifies paragangliomas and pheochromocytomas with high accuracy.

Authors:  Karel Pacak; Mark Kidd; Leah Meuter; Irvin M Modlin
Journal:  Endocr Relat Cancer       Date:  2021-10-13       Impact factor: 5.900

Review 4.  Advances in the Diagnosis and Therapeutic Management of Gastroenteropancreatic Neuroendocrine Neoplasms (GEP-NENs).

Authors:  Krzysztof Kaliszewski; Maksymilian Ludwig; Maria Greniuk; Agnieszka Mikuła; Karol Zagórski; Jerzy Rudnicki
Journal:  Cancers (Basel)       Date:  2022-04-17       Impact factor: 6.575

5.  NETest is superior to chromogranin A in neuroendocrine neoplasia: a prospective ENETS CoE analysis.

Authors:  Anna Malczewska; Kjell Oberg; Beata Kos-Kudla
Journal:  Endocr Connect       Date:  2021-01       Impact factor: 3.335

6.  NETest: serial liquid biopsies in gastroenteropancreatic NET surveillance.

Authors:  Mark J C van Treijen; Catharina M Korse; Wieke H Verbeek; Margot E T Tesselaar; Gerlof D Valk
Journal:  Endocr Connect       Date:  2022-09-07       Impact factor: 3.221

  6 in total

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