Use of Plasma Proteins to Predict Progressive Disease in Patients with Small Intestinal Neuroendocrine Tumours


Introduction: Prediction of progression in small intestinal neuroendocrine tumors (SI-NET).

Aim(s): To investigate if 93 circulating plasma protein biomarkers at time of diagnosis can predict which patients with G1/G2 SI-NET will progress (PD) or remain stable (SD) during 3-year follow-up.

Materials and methods: Non-interventional prospective study screened 175 patients with suspected SI-NET, 136 patients fulfilled the inclusion criteria. Exclusion criteria: other malignant disease, chronic inflammatory diseases, kidney or liver failure. Blood samples, histology and imaging were obtained at the time of diagnosis prior to initiation of any NET treatment. Relative levels of plasma proteins were analyzed with OLink Proseek method. Chromogranin A (CgA) was analyzed centrally. PD was determined in a real-life setting according to investigator judgement. The relative levels of plasma proteins (including CgA) were analyzed with machine learning with linear discriminant analysis (LDA).

Conference: 17th Annual ENETSConcerence (2020)

Presenting Author: Belusa R

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

Keywords: prediction, progression, machine learning, SI-NET, serum protein,

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