Multiparametric Machine Learning Model for Predicting Overall Survival in Patients with Small Intestinal Neuroendocrine Tumors under Somatostatin Analogs

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00037024

Enrollment

100

Registered

2025-10-14

Start date

2025-08-01

Completion date

Unknown

Last updated

2026-06-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

C17

Interventions

Group 1: Development and validation of an AI-based input model for the prognosis of overall survival of patients with histologically confirmed small intestinal NET who received treatment with somatost

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: Histologically confirmed small intestinal NET, treatment with somatostatin analogs, sufficient clinical follow-up data available.

Exclusion criteria

Exclusion criteria: Incomplete patient records, insufficient follow-up, other primary tumors.

Design outcomes

Primary

Measure	Time frame
Overall survival (OS) Observation period: 01.01.2012 - 01.05.2025	—

Secondary

Measure	Time frame
Progression-free survival (PFS), predictive accuracy of the machine learning model (e.g., C-index, ROC-AUC)	—

Countries

Germany

Contacts

Public ContactClemens Cyran

Klinikum der Universität München, Klinik und Poliklinik für Radiologie

Clemens.Cyran@med.uni-muenchen.de089 4400 73620

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Jun 11, 2026