Factors at time of diagnosis associated with progressive or stable disease in patients with Small Intestinal Neuroendocrine Tumors (SI-NETs)

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Introduction: EXPLAIN (NCT02630654) is evaluating a multi biomarker strategy for diagnosis, prognosis and response prediction in patients with SI-NET.

Aim(s): Interim analysis to identify via machine learning baseline clinical factors (CF) and novel plasma proteins (nPP) associated with either progressive (PD) or stable disease (SD) after 3 years of follow up.

Materials and methods: Patients with SI NET (G1 and G2) were included. Exclusion criteria: Other malignant disease, chronic inflammatory diseases, kidney or liver failure. Blood samples were obtained at time of diagnosis (first visit) before any tumor related therapy was initiated. Levels of 92 nPP and chromogranin A (CgA) were analysed centrally. SD or PD was determined according to current clinical practice by each investigator. Association rule mining was used to identify combinations of CF and nPP associated with either SD or PD. Rules were filtered using usual metrics of support, confidence and lift.

Conference:

Presenting Author: Schalin-Jäntti C

Authors: Schalin-Jäntti C, Kjellman M, Knigge U, Grønbæk H, Thiis-Evensen E,

Keywords: SI-NET, Biomarker, Progression, Data mining,