Identification of gastroenteropancreatic neuroendocrine tumor with high liver tumor burden based on clinicopathological features

#4038

Introduction: Liver tumor burden (LTB) is a key prognostic factor affecting survival and treatment response of GEP-NET patients. Currently available quantitative assessment of LTB relies on 68Ga-SSA PET/CT scan which is not accessible in some centers.

Aim(s): To develop a clinical model based on easily accessible clinicopathological markers to predict LTB in GEP-NET patients.

Materials and methods: We retrospectively enrolled 200 patients with well differentiated GEP-NETs. LTB was quantified based on 68Ga-DOTA-NOC PET/CT scan. The optimal cut-off value of high LTB was determined based on our previous study. Serum levels of liver enzymes and tumor biomarkers around the time of PET/CT scan were collected. The whole dataset was divided into training set and validation set. A LASSO regression method was applied to select predictors, and multivariate logistic regression was used to develop a clinical model which was further visualized by constructing a nomogram.

Conference:

Presenting Author: Chen L

Authors: Jumai N, Chen L, He Q, Liu M, Wen W,

Keywords: liver tumor burden, prediction, neuroendocrine tumor,