Multistate cure analysis

Background

A multistate cure model is a statistical framework used to analyze and represent the transitions that individuals undergo between different states over time, taking into account the possibility of being cured by initial treatment. This model is particularly useful in pediatric oncology where a fraction of the patient population achieves cure through treatment and therefore one or more of the states may never occur for them. It allows researchers to quantify the likelihood of transitions between states, examine the factors influencing these transitions while considering the probability of being cured and estimating the curative effect of a treatment. It can therefore provide a more comprehensive understanding of the disease progression or remission patterns being studied and aid in personalized treatment decisions and prognosis prediction.

Aims

The project aims at developing 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.

Relevance for cancer research

Besides its application to childhood osteosarcoma data from the EURAMOS-1 study, the new methodology developed can be employed to any kind of cancer data with cure possibility and sufficient follow-up information that involve transitions between different states.

Team

• Prof.dr. M. Fiocco, Mathematical Institute Leiden University, Department of Biomedical Data Sciences Leiden University Medical Center & Princess Máxima Center for Pediatric Oncology 

• Y. Jiang, PhD candidate at Mathematical Institute Leiden University & Princess Máxima Center for Pediatric Oncology 

• Prof.dr. H. Putter, Department of Biomedical Data Sciences Leiden University Medical Center & Mathematical Institute Leiden University

• Dr. ir. H. van Tinteren, Princess Máxima Center for Pediatric Oncology