Predicting Response to PRRT: Development and Validation of a Blood-Based Predictive Biomarker Abstract #2216

Introduction: We have developed a blood-based tool (gene expression analysis and tumor grade) for predicting PRRT efficacy.
Aim(s): Validate the clinical utility of the biomarker in two independent prospective cohorts and in two independent non-PRRT cohorts.
Materials and methods: Three 177Lu-PRRT treatment cohorts (n=158 [IRST Meldola; EMC-Rotterdam; ZKK-Bad Berka]) and 2 Comparator cohorts (GEPNETs (n=106, in a watch-and-wait program) and SSA-treated GEP-NETs (n=28). Baseline evaluations: Grade (Ki67) and NETest (qRT-PCR). A logistic regression model (PPQ) including genes regulating metabolism/growth factor signaling and grade. Two prediction outputs: Predicted Responder vs Predicted Non-Responder. Response was by RECIST 1.1 criteria [Responder (stable, partial and complete response) vs Non-Responder (disease progression)]. Statistics: Kaplan-Meier survival analysis.
Conference: 15th Annual ENETS conference (2018)
Category: Nuclear Medicine - Imaging and Therapy (PRRT)
Presenting Author: Professor Mark Kidd

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