The observational EURACAN prospective clinical registry dedicated to epithelioid hemangioendothelioma: The protocol of an international and collaborative effort on an ultra-rare entity
Authors: Frezza Anna Maria , Leonard Hugh , Aggerholm-Pedersen Ninna , Badalamenti Giuseppe , Baili Paolo , Baldi Giacomo G. , Bauer Sebastian , Bazzurri Serena , Benzonelli Irene , Bertuzzi Alexia , Blay Jean-Yves , Bianchi Giuseppe , Bonfarnuzzo Simone , Bouvier Christophe , Boye Kyetil , Martin Broto Javier , Brunello Antonella , Campanacci Domenico , Casali Paolo G. , Cicala Carlo , Crotti Elisa , D’Ambrosio Lorenzo , Dei Tos Angelo Paolo , Dieckmann Nils , Dufresne Armelle , Elston Stephanie , Ferraresi Virginia , Gabellini Stefano , Giani Claudia , Giannusa Vincenzo , Gil Sanjines Melissa , Grassani Teresa , Gronchi Alessandro , Lasalvia Paolo , Lindskog Stefan , Hindi Nadia , Ingrosso Matilde , Ivanescu Andrei , Jones Robin , Lugowska Iwona , Ketzer Julia , Mariuk-Jarema Anna , Mazzocca Alessandro , Monteleone Laura , Morosi Carlo , Napolitano Andrea , Nardozza Francesca , Neri Elisabetta , Nilsson Maria , Papakonstantinou Andri , Pasquali Sandro , Sbaraglia Marta , Scolari Federico , Szkandera Joanna , Valverde Claudia , Vincenzi Bruno , Vizzaccaro Salvatore , Zuccheri Federica , Stacchiotti Silvia , Trama Annalisa 
Published: August 2024

Introduction
Epithelioid hemangioendothelioma (EHE) is an ultra-rare sarcoma, marked by distinctive molecular and pathological features and with a variable clinical behavior. Its natural history is still partially understood, reliable prognostic and predictive factors are lacking and many questions are still open on the optimal management. In the context of EURACAN, a prospective registry specifically dedicated to EHE was developed and launched with the aim of providing, through high-quality prospective data collection, a better understanding of this disease.

Study design
Registry-based cohort study including only new cases of patients with a pathological and molecularly confirmed diagnosis of EHE

Objectives
To improve the understanding of EHE natural history, validate and identify new prognostic and predictive factors, clarify the activity and efficacy of currently available treatment options, describe treatment pattern.

Methods

Settings and participants
It is an hospital-based registry established in centers with expertise in EHE including adult patients with a new pathological and molecularly confirmed diagnosis of EHE starting from the 1st December 2023. The characteristics of each patient in the facility who meets the above-mentioned inclusion criteria will be collected prospectively and longitudinally with follow-up at cancer progression and / or cancer relapse or patient death. It is a secondary use of data which will be collected from the clinical records. The data collected for the registry will not entail further examinations or admissions to the facility and/or additional appointments to those normally provided for routine patient follow-up.

Variables
Full details on patients and disease features, treatment and outcome will be collected, according to common clinical practice guidelines developed and shared with all the contributing centers. In addition, data on potential confounders (e.g. comorbidity; functional status etc.) will also be collected.

Statistical methods
The data analyses will include descriptive statistics and analytical analyses. Multivariable Cox’s proportional hazards model and Hazard ratios (HR) for all-cause or cause-specific mortality will be used to determine independent predictors of overall survival, recurrence and progression.

Results
The registry has been joined by 21 sarcoma reference centers across EU and UK, covering 10 countries. Patients’ recruitment started in December 2023. The estimated completion date is December 2033 upon agreement on the achievement of all the registry objectives. The already established collaboration and participation of EHE patient’s associations involved in the project will help in promoting the registry and fostering accrual.