Association rule mining of clinical and biomarker data in neuroendocrine tumors: A prospective study on disease progression.

ABSTRACT: There is an unmet need for new methods to predict disease course in patients with neuroendocrine tumors (NET). We investigated 92 putative cancer-related plasma proteins including chromogranin A (CgA) and clinical parameters at the time of diagnosis to identify early factors associated with progressive (PD) or stable disease (SD). Patients with NET grade 1 and 2 of the small intestine (siNET) and pancreas (pNET) were included in this prospective study. Blood samples were obtained at the time of diagnosis before tumor-related therapy was initiated. During 3 years of follow-up, SD or PD was determined according to current clinical practice by each investigator. Association rule mining (ARM) was used to identify combinations of biomarkers and clinical parameters associated with SD or PD. Alto

SUBMITTER: Knigge UP 

PROVIDER: S-EPMC12488364 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature