top of page
Screenshot 2022-05-02 at 06.39.21.png

study (MCS) office

Screenshot 2022-04-20 at 05.31.31.png

Introduction to ECISS

ECISS (Endometrial Cancer Individualized Scoring System) is a novel assessment tool for women diagnosed with endometrial cancer. The tool uses machine learning approaches to create a series of models that would predict overall and disease-free survival in these patients. These models would provide a prognostic value at initial diagnosis in the form of survival probability

However, an eventual objective of these models is to individualize management plan based on patient and disease characteristics by calculating survival probability against different management strategies prior to commencing treatment. The tool would be able to update probability of survival postoperatively based on intra-operative findings and postoperative events.

ECISS status

  • ECISS was first proposed in 2021. ECID (Endometrial Cancer International Database) is an international data collection project that was launched in 2021 by MOGGE foundation for the purpose of developing the first version of ECISS. Data collection was completed in March, 2022 and was contributed by 9 European centers.

  • ECID data collection was moderated by MOGGE MCS (multicenter studies) unit. Data were delivered to MOGGE AI (artificial intelligence) unit for development of ECISS models by the end of March, 2022.

  • Effective April 18th, 2022, preliminary results of ECISS have been revealed and 4 sets of models were created to predict 3-year, 5-year overall survival and disease-free survival. Each model consists of 3 submodels (baseline model, model including baseline score and treatment variables, model including previous score and postoperative findings).

  • A final manuscript submission is planned within the last half of 2022. 

AI logo.png

ECISS development project

  • ECISS development project is a multicenter international project that aims at supporting continuous development of ECISS  by expanding size of data and number of variables. This would facilitate re-analysis of data at regular basis to produce updated versions of the score over time. The ultimate goal is to increase ECISS accuracy in predicting cancer outcomes per management and thus, in determining patient-specific treatment that would yield the best outcomes. Such a tool can gradually replace staging and risk stratification systems and provide a single tool that would determine best management strategy.

  • Therefore, effective September 2022, we will accept requests from interested investigators to contribute to the upcoming version of ECISS. Interested investigators are expected to apply for IRB approval for the study before starting retrospective data collection.

Interested to partner or have questions? please contact us:

Original partners

Professor Juan Luis Alcázar
Gynecologic Oncologic Division
Clinica Universidad de Navarra
Navarra, Spain
Dr. Federico Ferrari
Department of Obstetrics and Gynecology
Spedali Civili
Brescia, Italy
Dr. Pluvio Coronado
Department of Obstetrics and Gynecology
Hospital clinico san carlos
Madrid, Spain
Rauf Melekoglu.jpg
Dr. Rauf Melekoglu
Department of Obstetrics and Gynecology
Inonu University
Malatya, Turkey
Dr. Luca Giannella
Azienda Ospedaliero-Universitaria
Ancona, Italy
Dr. Erbil Karaman
Department of obstetrics and gynecology
Van Yüzüncü Yıl Üniversitesi
Van, Turkey
Dr. Angel Yordanov
Department of Gynecologic Oncology
Medical University Pleven
Pleven, Bulgaria
Dr. Jure Knez
Clinic for Gynaecology
University Medical Centre Maribor
Maribor, Slovenia
Dr. Cem Önal
Department of Radiation Oncology
Baskent University
Ankara, Turkey

ECISS calculator v 1.0

ECISS calculator version 1.0 was created in May 2022. The current version is experimental and is intended for research purposes only and is available through this webpage free of charge


Not yet published

bottom of page