ENETS has a long experience in neuroendocrine neoplasms (NENs) and has a high level of expertise and multi-center co-operation resulting from its networking with ENETS Centers of Excellence (CoE) for head and neck, thoracic gastroenteropancreatic (GEP), pelvic NENs in Europe as well as non-European countries, such as the USA and Australia.
ENETS has hosted a NEN registry since 2008: https://doi.org/10.1016/j.ejca.2022.03.007.
In 2020, ENETS made the decision to take the project to new academic levels with a new partner, the Coordinating Center for Clinical Trials at the Philipps-University of Marburg (KKS). KKS is an independent academic institution of the Faculty of Medicine of Philipps-Universität Marburg.
Research is crucial for ENETS.
The ENETS European NET Database (ENETS DB) structure is a compromise between best modality of NEN patient characterisation during their lifetime, regulatory and information constraints. It is an academic and evolving database.
ENETS DB is expected not only to be a pillar of ENETS research but also to help each NEN referral center to better structure its own activity research.
The ENETS European NET Database (ENETS DB) offers a unique opportunity to collect data by contributing to an innovative study model for rare diseases. This project aims to re-establish a platform for the retrospective and prospective collection of clinical information on patients with NENs.
The new ENETS database will:
- Collect basic clinical data on NENs at each Center of Excellence
- Provide a basis for robust clinical questions for ENETS studies where it is unlikely that the required number of patients can be recruited within an individual or even multi-center approach
- Identify patients eligible to lay the foundations of prospective ENETS trials
- To stimulate collaboration among ENETS CoEs
- Allow each participating center to evaluate its own data via the data reporter, which constitutes part of the database's technical set-up.
ENETS DB definitions and concepts
Inclusion and exclusion criteria
- Head and neck, thoracic, GEP and pelvic NEN patients seen in centers from the 1 January 2010 onwards are eligible to be enrolled.
- Medullary thyroid carcinoma, pheo-/paragangliomas, pituitary carcinoma, and small cell lung NEC are excluded.
- Other NET primary or patients seen prior 2010 may be discussed as part of specific level 3 studies.
Five propositions that are fundamental to the new database concept:
Concept 1: To make database capture compatible with real life
Solution: 3 levels of data capture
Level 1 - Minimal dataset – 100 items
- Designed so that all necessary data can be entered within 15 minutes
- Is best suited for new patients with prospective data collection
- Suitable to test the feasibility of studies
- Provides answers on the “epidemiology of experts centers”
Level 2 - Extended dataset – 140 items
- This dataset is designed to cover 80% of data needed for any kind of study
- Data is expected to be captured within a vast majority of (>80%) of level 3 studies
- Or on a routine basis based on local NEN referral center decision
- Ideally, the extended and minimum datasets should be captured at the same time
Level 2, in the DB section “additional” – approx. 60 items:
- This section will evolve over time
- Information (including comorbidities, adverse events, if tissue has been stored in a biobank) is expected to be captured within the majority (>50%) of level 3 studies
- Or on a routine basis based on the decision of the local NEN referral center.
Level 3 – A variety of specialised datasets that will be developed and are project driven.
- Level 3 datasets are based on levels 1 and 2.
- In each project, existing items (of levels 1 and 2) are used and new required items are programmed in addition.
Concept 2: Prospective collection ensures the highest completeness of data
Solution: Prospective or retrospective modality of data capture is inquired/possible
- Prospective collection is defined by first capture of data in the DB < 6 months for NET or 2 months for NEC diagnosis
- Retrospective collection is defined by first capture of data in the DB > 6 months for NET or > 2 months for NEC diagnosis
Concept 3: Center of Excellence (NEN referral centers) ensure the highest level of standardised characterisation
Solution: Officially acknowledged high-quality centers (NEN referral centers) are eligible to participate in the DB
The following accreditations/certifications are required to qualify as collaborating partners of the ENETS DB:
- ENETS certified NEN Center of Excellence (ENETS CoE) or other
- ERN-EURACAN (rare cancer network) accredited NEN referral centers
- NEN referral centers that are accredited by national authorities.
In order to apply to become an ENETS DB collaboration partner, please send an informal letter to firstname.lastname@example.org.
An information package including a template to draft the local research ethics committee application will be provided.
Concept 4: Longitudinal collection of data to capture the whole story of a rare, complex tumor with long-term survival, including baseline characteristic and major changes in characterisation
Solution: Different sections of data insertion are available reflecting the journey of each patient
- Baseline data: Data is collected (does not mean captured in the DB) in the center (NEN referral center or non-NEN referral center if the visit in the NEN referral center did not occur within the appropriate time frame) BEFORE 6 months from first NET or < 2 months from first NEC DIAGNOSIS as defined by:
- First choice: Date of pathology if available within the appropriate time frame or
- Second choice: Date of first positive imaging if pathology is not available within the appropriate time frame or
- Third choice: Date of first imaging work-up at the time of functioning syndrome diagnosis if positive imaging is not available within the appropriate time frame
- Major change data are defined by changes in WHO, TNM, functioning Sd, SRI categorisation during the course of the tumor as defined by AFTER 6 months from NET or 2 months from NEC diagnosis as defined above.
- Major changes are classified in 2 subgroups:
- True changes due to tumor progression or therapeutic pressure
- Optimisation, which means changes due to review of old exams or new exams not performed at baseline.
The major change section is also used to re-characterise patients for a level 3 study for which the baseline of the study is different from the BASELINE of the DB which is defined by the date of diagnosis.