Embedded Files
Explore the projects for details and their publications. Open-source code and resources, both from the listed oncology projects and other survival analysis work, are available on our new GitHub page.
Ongoing Projects
Ongoing Projects
The PACT-ES study
The PACT-ES study
This research project aims to employ advanced medical statistics methodology to develop a novel Personalised Approach to Chemotherapy Treatment for Ewing’s Sarcoma (PACT-ES). PACT-ES will investigate the longitudinal relationship between dose-reductions/delays in chemotherapy and multiple side effects, and their impact on survival outcomes.
The INDICATES study
The INDICATES study
This study aims to develop a user-friendly prediction tool to assist the multidisciplinary team in the decision-making process on INDIvidualized loCAl Therapy for patients with Ewing Sarcoma (INDICATES).
Prediction and validation using PERSARC (PERsonalized SARcoma Care)
Prediction and validation using PERSARC (PERsonalized SARcoma Care)
The PERSARC app represents an informative support tool for the dynamic prediction of overall survival (OS) and local recurrence (LR) in high-grade Soft-Tissue Sarcomas of the extremity (eSTS), using patient-, tumour- and treatment-related characteristics. It is currently used by many physicians in their daily practice to assess a more realistic prognosis of expected recurrence rates and life expectancy, improving their clinical-based predictive capability. Furthermore, given its established validity, it can serve as a tool for the validation and comparison of new models for OS and/or LR in eSTS.
Multistate cure analysis
Multistate cure analysis
The aim of this project is to develop a more generalized and user-friendly algorithm to fit a multistate cure model, on top of the current framework of multistate model and mixture cure model. The proposed algorithm will be applied on a study of childhood osteosarcoma as an example.
The PRIME-ROSE study
The PRIME-ROSE study
The aim of PRIME-ROSE is to enable cross-border data sharing by combining the data from DRUP-like trials in Europe. First, it builds synthetic randomized trials resembling a randomized control trial to evaluate clinical benefit. Second, the project plans to design and conduct pragmatic clinical trials, provide implementation data, effectively involve patients, focus on multi-stakeholder collaboration and continuous knowledge transfer and training of DRUP-like trials.
The SCOPES study
The SCOPES study
The aim of the KWF-funded study is to compare the wound healing complication rates and local control between the two different treatment schedules in soft tissue sarcomas, as well as the treatment-related burden for patients and the cost-effectiveness of the two regimens.
The DRUP (Drug Rediscovery Protocol) study
The DRUP (Drug Rediscovery Protocol) study
The aim of this project is to elaborate the use of statistical methods within the long-standing DRUP trial. First, the pooling of information across the different cohorts will be investigated to better analyze the effectiveness of targeted therapy in DRUP. Secondly, the absence of a control group shall be addressed by examining the application of survival models with historical data.
Pathological diagnosis of solid pediatric tumors
Pathological diagnosis of solid pediatric tumors
The aims of the this project are: (i) to evaluate the diagnostic value and accuracy of current pathological techniques in the diagnosis of solid pediatric tumors; (ii) to investigate the prognostic value of molecular aberrations in (non-high-risk) neuroblastoma to improve current risk-stratification and thereby improving outcome of neuroblastoma patients.
The epiMETA study
The epiMETA study
The aim of the epiMETA study is to investigate how effective different antiseizure medications are for patients with epilepsy due brain metastases. Using clinical data from patients across the Netherlands, we compare commonly used treatments and study how tumor-directed therapies relate to seizure outcomes.
Mathematical Institute, leiden university
Mathematical Institute, leiden university
Long term survival after childhood osteosarcoma: cure models
Long term survival after childhood osteosarcoma: cure models
Time-varying covariates for survival models
Time-varying covariates for survival models
Predicting cancer survival with machine learning
Predicting cancer survival with machine learning
Personalised Sarcoma Care (PERSARC)
Personalised Sarcoma Care (PERSARC)
Meta-analysis of individual patient data to investigate dose-intensity relation with survival outcome for osteosarcoma patients
Meta-analysis of individual patient data to investigate dose-intensity relation with survival outcome for osteosarcoma patients
Dose-intensity relation with survival outcomes in Acute Lymphoblastic Leukaemia
Dose-intensity relation with survival outcomes in Acute Lymphoblastic Leukaemia
Princess Máxima Center, utrecht & LEIDEN UNIVERSITY MEDICAL CENTER
Princess Máxima Center, utrecht & LEIDEN UNIVERSITY MEDICAL CENTER
Liquid biopsies in pediatric solid tumors
Liquid biopsies in pediatric solid tumors
Evaluating MUTARS® mega-endoprostheses
Evaluating MUTARS® mega-endoprostheses
The CATERPILLAR study
The CATERPILLAR study
Critically ill pediatric oncology patients
Critically ill pediatric oncology patients
Fluorescence Guided Surgery for Pediatric Oncology
Fluorescence Guided Surgery for Pediatric Oncology
Validating the Adjusted Clinical Groups (ACG) Risk Stratification Tool for Dutch Primary Care
Validating the Adjusted Clinical Groups (ACG) Risk Stratification Tool for Dutch Primary Care
Individual Clinical Advanced decision-making and Risk Evaluation for Ewing sarcoma (iCare 4 Ewing)
Individual Clinical Advanced decision-making and Risk Evaluation for Ewing sarcoma (iCare 4 Ewing)
Impact of Surgery for Neuroblastoma
Impact of Surgery for Neuroblastoma
The OPTIMAL study: Optimizing the treatment of patients with bone metastases
The OPTIMAL study: Optimizing the treatment of patients with bone metastases
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