Projects
Ongoing Projects
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
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.
Evaluating MUTARS® mega-endoprostheses
The aim of this project is to perform a qualitative evaluation of MUTARS® mega-endoprostheses survival in patients with extensive bone defects, describing failure types, mechanical/non-mechanical complications (according to the Henderson classification), and risk factors for complications.
Acute Kidney Injury in paediatric cancer patients
This project focuses on investigating (i) the applicability of non-invasive biomarkers to identify early Acute Kidney Injury (AKI) in paediatric cancer patients, and (ii) the impact of continuous renal replacement therapy on both short- and long-term outcomes among these children and factors that influence these outcomes.
The CATERPILLAR study
The aim of this project is to increase the quality of life of pediatric oncology patients by reducing the rate of central line-associated bloodstream infections with the use of TauroLock-Hep100, a lock solution with antimicrobial and anticoagulant properties.
Prediction models with survival data: Machine Learning vs Cox model
The aim of this project is on characterizing the model behaviour and measuring the model performance of various machine-learning methods in predicting osteosarcoma survival. In addition, various extensions of the traditional Cox proportional hazards model are investigated.
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.
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 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.
Past Projects
Critically ill pediatric oncology patients
Fluorescence Guided Surgery for Pediatric Oncology
Long term survival after childhood osteosarcoma: cure models
Time-varying covariates for survival models
Predicting cancer survival with machine learning
Personalised Sarcoma Care (PERSARC)
Validating the Adjusted Clinical Groups (ACG) Risk Stratification Tool for Dutch Primary Care
Meta-analysis of individual patient data to investigate dose-intensity relation with survival outcome for osteosarcoma patients
Individual Clinical Advanced decision-making and Risk Evaluation for Ewing sarcoma (iCare 4 Ewing)
Impact of Surgery for Neuroblastoma
The OPTIMAL study: Optimizing the treatment of patients with bone metastases
Dose-intensity relation with survival outcomes in Acute Lymphoblastic Leukaemia
