Introduction: A key issue in GEP-NETs is early identification and prediction of disease progression. Clinical evaluation and imaging are limited due to the lack of sensitivity and disease indolence.
Aim(s): Assess the NETest as a predictive and prognostic marker of progression in a long-term follow-up study.
Materials and methods: GEP-NETs (n=34) followed for a median 4 yrs (2.2-5.4). WHO tumor grade/stage Grade I: n=15, Grade II: n=17; 31 (91%): stage IV. Baseline and longitudinal imaging and biomarkers were available and progression defined (RECIST 1.0). NETest: qPCR and multianalyte algorithmic analysis (disease activity scaled 0-100% with low <40% and high activity risk cutoffs >80%); CgA: RIA (normal <150µg/l); PFS: Kaplan-Meier analysis.
Conference: 13th Annual ENETS conference 2016 (2016)
Presenting Author: Professor Mark Kidd
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