Evidence map›Paper›PMID 40812788›Full record

ArticleJournal of neuroendocrinology2025

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

Ulrich Peter Knigge, Magnus Kjellman, Henning Grønbæk, Espen Thiis-Evensen, Camilla Schalin-Jäntti, Staffan Welin, Halfdan Sørbye, Maria Del Pilar Schneider, Roger Belusa, Nordic NET Biomarker Group

Abstract read
In one paragraph

Article in Journal of neuroendocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ulrich Peter KniggeDepartment of Surgery and Transplantation, ENETS Neuroendocrine Tumor Centre of Excellence, Copenhagen University Hospital, Copenhagen, Denmark.
Magnus KjellmanDepartment of Breast, Endocrine Tumors and Sarcoma, Karolinska University Hospital Solna, Stockholm, Sweden.
Henning GrønbækDepartment of Hepatology and Gastroenterology, Aarhus University Hospital, ENETS Center of Excellence, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-8998-7910
Espen Thiis-EvensenDepartment of Gastroenterology, Oslo University Hospital, Rikshospitalet, ENETS Center of Excellence, Oslo, Norway.ORCID https://orcid.org/0000-0003-0029-6481
Camilla Schalin-JänttiEndocrinology, Abdominal Center, Helsinki University Hospital and University of Helsinki, ENDO-ERN (European Reference Network on Rare Endocrine Conditions), Helsinki, Finland.ORCID https://orcid.org/0000-0002-2428-0161
Staffan WelinDepartment of Endocrine Oncology, Uppsala University Hospital, ENETS Center of Excellence, Uppsala, Sweden.
Halfdan SørbyeCancer Clinic, Haukeland University Hospital, Bergen, Norway.ORCID https://orcid.org/0000-0002-7132-6214
Maria Del Pilar SchneiderMedical Department, IPSEN Innovation, Paris, France.ORCID https://orcid.org/0009-0003-8633-9274
Roger BelusaGlobal Biometry Department, IPSEN, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-3776-7267
Nordic NET Biomarker Group

Funding

Ipsen
6 · The paper itself

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. Altogether, 115 patients with siNET and 30 with pNET with complete clinical and biomarker data were included in the analysis representing 3 years of follow-up. Several novel plasma proteins and clinical factors were associated with either PD or SD. In siNET, CgA (>4 upper limits of normal [ULN]) was the most frequent biomarker associated with PD. Females, in contrast to males, with CgA >4 ULN showed a high risk of progression (PPV 100%, NPV 63%). In the siNET cohort, Carboxypeptidase E (CPE) was a discriminating factor between SD and PD. CPE <3.03 was associated with SD, whereas CPE >3.14 was associated with PD (p = 0.003). In the pNET cohort, among clinical variables, only the presence of liver metastasis was associated with PD. CgA was not among the top biomarkers associated with PD. Several parameters, both clinical and biomarker data, as well as combinations of these, were associated with PD or SD 3 years after diagnosis. We identified novel biomarkers improving the association with PD or SD. [Correction added on 28 August 2025, after first online publication: Abstract has been updated.].

Indexed as

Biomarkers, TumorData MiningIntestinal NeoplasmsNeuroendocrine TumorsPancreatic NeoplasmsAdultAgedChromogranin ADisease ProgressionFemaleHumansMaleMiddle AgedProspective StudiesBiomarkers, TumorChromogranin Aassociation rulesdisease progressionneuroendocrine tumorplasma chromogranin Aproteins

Identifiers

PMID40812788
PMCPMC12488364

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.