Research
To improve the ENDORISK model, our team is continually working on new research. Please take a look at our published articles to see already published research.
We are also working on ongoing projects to further improve the ENDORISK model.
PUBLISHED ARTICLES
December, 2022
Vrede, S. W. et al.
December, 2022
Vrede, S. W. et al.
December, 2022
Vrede, S. W. et al.
December, 2022
Vrede, S. W. et al.
December, 2022
Vrede, S. W. et al.
December, 2022
Vrede, S. W. et al.
December, 2022
Vrede, S. W. et al.
August, 2022
Grube, M. et al.
Improved preoperative risk stratification in endometrial carcinoma patients: external validation of the ENDORISK Bayesian network model in a large population-based case series
August, 2022
Muller-Sielaff, J. et al.
Augustus, 2022
Vinklerová, P. et al.
External validation study of endometrial cancer preoperative risk stratification model (ENDORISK)
Mei, 2020
Reijnen, C. et al.
Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study
ONGOING PROJECTS
Evaluation of endometrial cancer care study
Study in three oncological care regions in the Netherlands to gain insight in the standard care for endometrial cancer. Results of this study will function as a baseline to our upcoming implementation study of ENDORISK in to clinical practice.
ENDORISK Clinical Implementation Study (ENDORISK-I)
A study conducted in collaboration with hospitals from the gynecological oncology regions of Nijmegen (GOCN) and Eindhoven (GOCZ). We are investigating the impact of ENDORISK on clinical practice. The personalized risk score for lymph node metastases, the patient’s condition for additional therapy, and patients’ personal preferences are taken into account when developing the treatment plan. The results of this implementation study will be compared with the results of the Evaluation of Care in Endometrial Carcinoma study.
ENDORISK-SLN Model
A new version of the ENDORISK model is currently being developed, in which sentinel lymph node status will also be included in the model. This status provides valuable information about the volume of lymph node metastasis. This can support physicians in developing a treatment plan. Multiple external validations of this model will be performed.
ENDORISK Predict
This project investigates whether an AI model can help better predict which patients with endometrial carcinoma benefit from additional radiotherapy after surgery. The research builds on the existing ENDORISK model, which estimates the risk of lymph node metastases based on clinical, molecular, and pathological data. In this study, data from more than 1,100 patients will be analyzed, including women who did and did not receive radiotherapy. The study will examine which tumor characteristics, genetic factors, and patient characteristics are associated with the effect of radiotherapy. The aim is to develop a comprehensive prediction model that distinguishes between patients who benefit from additional treatment and patients for whom radiotherapy is unlikely to add value. The results should contribute to more targeted treatments and help prevent unnecessary side effects.
ENDORISK 2.0
Expanding the model with relevant variables to make it future-proof. This is being carried out in collaboration with Prof. Peter Lucas from the University of Twente and Dr. Arjen Hommersom from the Open University of the Netherlands.