Evidence map›Paper›PMID 42713095›Full record

ArticleFrontiers in endocrinology2026

Early prediction of metastatic insulinoma using tumor size and biochemical markers: a retrospective cohort study.

Annie Mathew, Ben Freudenberg, Marc Wichert, Frank Weber, Benedikt M Schaarschmidt, Johanna Braegelmann, David Kersting, Dagmar Fuhrer, Harald Lahner

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors.

Annie MathewDepartment of Endocrinology, Diabetes and Metabolism and Division of Laboratory Research, University Hospital Essen, Endocrine Tumor Center at WTZ/Comprehensive Cancer Center and ENETS Center of Excellence, University of Duisburg-Essen, Essen, Germany.
Ben FreudenbergDepartment of Endocrinology, Diabetes and Metabolism and Division of Laboratory Research, University Hospital Essen, Endocrine Tumor Center at WTZ/Comprehensive Cancer Center and ENETS Center of Excellence, University of Duisburg-Essen, Essen, Germany.
Marc WichertCenter of Endocrine Medicine, University of Duisburg-Essen, Essen, Germany.
Frank WeberCenter of Endocrine Medicine, University of Duisburg-Essen, Essen, Germany.
Benedikt M SchaarschmidtCenter of Endocrine Medicine, University of Duisburg-Essen, Essen, Germany.
Johanna BraegelmannDepartment of Endocrinology, Diabetes and Metabolism and Division of Laboratory Research, University Hospital Essen, Endocrine Tumor Center at WTZ/Comprehensive Cancer Center and ENETS Center of Excellence, University of Duisburg-Essen, Essen, Germany.
David KerstingCenter of Endocrine Medicine, University of Duisburg-Essen, Essen, Germany.
Dagmar FuhrerDepartment of Endocrinology, Diabetes and Metabolism and Division of Laboratory Research, University Hospital Essen, Endocrine Tumor Center at WTZ/Comprehensive Cancer Center and ENETS Center of Excellence, University of Duisburg-Essen, Essen, Germany.
Harald LahnerDepartment of Endocrinology, Diabetes and Metabolism and Division of Laboratory Research, University Hospital Essen, Endocrine Tumor Center at WTZ/Comprehensive Cancer Center and ENETS Center of Excellence, University of Duisburg-Essen, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Insulinomas are rare functional pancreatic neuroendocrine tumors. Metastasis is found in up to 15% of patients and is difficult to predict at diagnosis. Methods: We retrospectively analyzed 64 patients (56.2% female, median age 49 years) with biochemically confirmed insulinoma treated at a European Neuroendocrine Tumor Society Center of Excellence between 2010 and 2024, assessing clinical characteristics, tumor biology, diagnostics, treatments and survival (median follow-up 23 months) . Results: Metastasis was present in 27% of cases (17/64). Metastatic insulinomas had significantly larger primary tumors (median 32 vs. 15 mm, p < 0.001), higher Ki-67 indices (median 11% vs. 2%, p < 0.001), shorter overall survival (median 51 months vs. not reached, p < 0.001) and a shorter interval from symptom onset to diagnosis (median 2 vs. 8 months, p < 0.05). Surgery was performed in 79% of patients (39/45 non-metastatic vs. 10/17 metastatic insulinomas). All metastatic cases required further multimodal therapy, including pharmacological and local-ablative treatments. A logistic prediction model based on tumor size, fasting glucose and the insulin-to-C-peptide ratio was developed to predict metastasis in insulinoma patients and showed excellent performance (AUC 0.96, sensitivity 90.9%, specificity 93.8%) in the insulinoma cohort. ROC analysis identified clinically relevant size thresholds, with a tumor size cut-off at 19 mm capturing all metastatic insulinomas with available size data and a cut-off at 24 mm improving specificity for metastasis to 84.6%. Applied to 24 published insulinoma cases, the model achieved a classification accuracy of 75%. Stratification into three risk categories ("low," "medium," and "high") further enhanced clinical interpretability. In line with molecular studies, metastatic insulinomas in our cohort exhibited disproportionate proinsulin secretion in the available cases, supporting the concept of β-cell dedifferentiation with impaired prohormone processing as a feature of aggressive disease. Discussion: Our analysis highlights relevant clinical and biological distinctions between non-metastatic and metastatic insulinomas. Based on three diagnostic parameters, we propose a predictive model for early risk stratification to guide staging intensity and follow-up in insulinoma management.

Indexed as

Biomarkers, TumorInsulinomaPancreatic NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedNeoplasm MetastasisPrognosisRetrospective StudiesTumor BurdenBiomarkers, Tumorfunctioning pancreatic NEThypoglycemiametastatic insulinomaneuroendocrine tumorsrisk prediction model

Identifiers

PMID42713095
PMCPMC13551242

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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.