Netest is superior to chromogranin a in neuroendocrine neoplasia: A prospective enets coe analysis

Abstract

Introduction: The absence of a reliable, universal biomarker is a significant limitation in neuroendocrine neoplasia (NEN) management. We prospectively evaluated two CgA assays, (NEOLISA, EuroDiagnostica) and (CgA ELISA, Demeditec Diagnostics (DD)) and compared the results to the NETest. Methods: NEN cohort (n = 258): pancreatic, n = 67; small intestine, n = 40; appendiceal, n = 10; rectal, n = 45; duodenal, n = 9; gastric, n = 44; lung, n = 43. Image-positive disease (IPD) (n = 123), image & histology-negative (IND) (n = 106), and image-negative and histology positive (n = 29). CgA metrics: NEOLISA, ULN: 108 ng/mL, DD: ULN: 99 ng/mL. Data mean ± s.e.m. NETest: qRT-PCR – multianalyte analyses, ULN: 20. All samples de-identified and assessed blinded. Statistics: Mann–Whitney U-test, Pearson correlation and McNemar-test. Results: CgA positive in 53/258 (NEOLISA), 32 (DD) and NETest-positive in 157/258. In image-positive disease (IPD, n = 123), NEOLISA-positive: 33% and DD: 19%. NETest-positive: 122/123 (99%; McNemar’s Chi2= 79–97, P < 0.0001). NEOLISA was more accurate than DD (P = 0.0003). In image-negative disease (IND), CgA was NEOLISA-positive (11%), DD (8%), P = NS, and NETest (33%). CgA assays could not distinguish progressive (PD) from stable disease (SD) or localized from metastatic disease (MD). NETest was significantly higher in PD (47 ± 5) than SD (29 ± 1, P = 0.0009). NETest levels in MD (35 ± 2) were elevated vs localized disease (24 ± 1.3, P = 0.008). Conclusions: NETest, a multigenomic mRNA biomarker, was ~99% accurate in the identification of NEN disease. The CgA assays detected NEN disease in 19–33%. Multigenomic blood analysis using NETest is more accurate than CgA and should be considered the biomarker standard of care.