Clinical Research Directory

Prospective Validation of an EHR-based Pancreatic Cancer Risk Model

The goal of this prospective observational cohort study is to validate a previously developed pancreatic cancer risk prediction algorith (the PRISM model) using electronic health records from the general population. The main questions it aims to answer are: * Will a pancreatic cancer risk model, developed on routine EHR data, reliably and accurately predict pancreatic cancer in real-time? * What is the average time from model deployment and risk prediction, to the date of pancreatic cancer development and what is the stage of pancreatic cancer at diagnosis? The risk model will be deployed on data from individuals eligible for the study. Each individual will be assigned a risk score and tracked over time to assess the model's discriminatory performance and calibration.

Dynamic Multi-omics Integration Model to Predict Neoadjuvant Therapy Response in Locally Advanced Rectal Cancer

The goal of this observational study is to establish a dynamic multi-omics integration model for predicting pathological complete response (pCR) after neoadjuvant treatment in locally advanced (T3-4NxM0) rectal cancer, providing support for subsequent patient selection for the watch-and-wait strategy. The main question it aims to answer is: What is the predictive value of this model to assess individual achievement of pathological complete response (pCR) after neoadjuvant treatment? Eligible patients will be prospectively enrolled, and the clinical features of their pre-neoadjuvant treatment, during-treatment, and post-treatment preoperative will be collected and annotated.

The Value of a Risk Prediction Tool (PERSARC) for Effective Treatment Decisions of Soft-tissue Sarcomas Patients

The goal of this clinical trial is to assess the (cost-)effectiveness of a personalised risk assessment tool (PERSARC) to increase patients' knowledge about risks and benefits of treatment options and to reduce decisional conflict in comparison with usual care in high-grade extremity Soft-Tissue Sarcoma-patients. High-grade (2-3) extremity Soft-Tissue Sarcoma patients (\>= 18 years) will either receive standard care (control group) or care with the use of PERSARC; i.e. PERSARC will be used in multidisciplinary tumour boards to guide treatment advice and in consultation in which the oncological/orthopaedic surgeon informs the patient about his/her diagnoses and discusses the benefits and harms of all relevant treatment options (intervention group)

Prospective Validation of Liver Cancer Risk Computation (LIRIC) Models

The goal of this prospective observational cohort study is to validate previously developed Hepatocellular Carcinoma (HCC) risk prediction algorithms, the Liver Risk Computation (LIRIC) models, which are based on electronic health records. The main questions it aims to answer are: * Will our retrospectively developed general population LIRIC models, developed on routine EHR data, perform similarly when prospectively validated, and reliably and accurately predict HCC in real-time? * What is the average time from model deployment and risk prediction, to the date of HCC development and what is the stage of HCC at diagnosis? The risk model will be deployed on data from individuals eligible for the study. Each individual will be assigned a risk score and tracked over time to assess the model's discriminatory performance and calibration.

Liquid Biopsy (ctDNA) Guided Treatment in Localized Pancreatic Cancer: Neoadjuvant CTX vs. Upfront Surgery

This study evaluates the clinical prognostic impact (on DFS and OS) of liquid biopsy guided treatment vs. standard of care (physicians choice) in localized pancreatic cancer (despite because of CA 19-9 levels and computed tomography, upfront surgery is recommended by tumor board). ctDNA positive patients will receive neoadjvuant chemotherapy at current gold standard physicians choice instead of upfront surgery, because of assumed high biological risk for early recurrence.

Predicting Tumor Metastasis by Employing a Target Organ/Primary Lesion Fusion Radiomics Model

A pre-metastatic target organ/primary lesion fusion radiomics model was developed based on the "soil-seed" theory to predict comman tumor metastasis in retrospective settings. To prospectively verify the performance of the target organ/primary lesion fusion radiomics model in predicting tumor metastasis patterns (brain metastasis in lung cancer, liver metastasis in colorectal cancer, lung metastasis in breast cancer), we designed this prospective observational trial.

Innovative Approach to Detect Recurrent Colorectal Lesions With Surveillance Via Mutation Analysis & Clinical Phenotype

It is known that the development of colorectal adenoma is dependent on the appearance of somatic mutations in protooncogenes and tumor suppressor genes. Based on our previous mutation analyses of 120 patients with high-risk adenoma removed by enbloc resection with subsequent colonoscopy after 1 year, there is a correlation between mutation in exon 7 of the TP53 gene and risk of early metachronous lesions development. The results also indicate that mutation phenotype (mutation profile and burden) of all lesions detected on index colonoscopy can determine risk of metachronous lesions. As not all synchronous lesions were analyzed and the surveillance colonoscopy interval was less than 3 years, this assumption could not be confirmed. In this study it is planned to perform mutation analysis of all synchronous lesions in 200 patients and correlate the data with appearance of metachronous lesions after 1, 3 and 5 years. Moreover, the mutation profile of all metachronous lesions developed during the 5 years of surveillance will be determinated and compared with mutation profile of index lesions from the same localization to verify their common biological origin. This all could help personalize the surveillance program in terms of reduction of the burden on the patient and endoscopic workplaces and risk of developing colorectal cancer in a particular patient.

COLO-COHORT (Colorectal Cancer Cohort) Study

This is a cross-sectional study aimed at identifying factors which best predicts patients at high risk of colorectal cancer or colorectal adenomas and to develop a risk prediction model.