Abstract
Follicular lymphoma is an incurable haematological cancer that tends to follow a remitting relapsing
course; with treatment options ranging from “watch and wait” (active monitoring), chemotherapy,
and radiotherapy. The treatment decision is typically dependent upon patient characteristics and
disease stage. Using routine data collected by the Haematological Malignancy Research Network
(www.hmrn.org), we are undertaking research into improving understanding of the treatment pathways
and the impact of these decisions not only on the patient, but also on the cost to the healthcare
provider. The aim is to facilitate informed decision making by providing a personalised prognostic tool
that identifies a suitable treatment option at each stage of the treatment pathway, as part of a shared
decision-making process between patient and clinician.
Multi-state modelling provides an appropriate toolkit for this work, owing to its ability to predict the
movement of a person through a discrete state-space captured by individual-level characteristics. This
work details implementation considerations of the modelling stage, including the design of the statediagram,
the fitting of transition-specific hazard functions, and the use of Discrete Event Simulation
to provide estimated transition probabilities. Other considerations include how to present the results
of a complex model into a deployable clinical tool.
course; with treatment options ranging from “watch and wait” (active monitoring), chemotherapy,
and radiotherapy. The treatment decision is typically dependent upon patient characteristics and
disease stage. Using routine data collected by the Haematological Malignancy Research Network
(www.hmrn.org), we are undertaking research into improving understanding of the treatment pathways
and the impact of these decisions not only on the patient, but also on the cost to the healthcare
provider. The aim is to facilitate informed decision making by providing a personalised prognostic tool
that identifies a suitable treatment option at each stage of the treatment pathway, as part of a shared
decision-making process between patient and clinician.
Multi-state modelling provides an appropriate toolkit for this work, owing to its ability to predict the
movement of a person through a discrete state-space captured by individual-level characteristics. This
work details implementation considerations of the modelling stage, including the design of the statediagram,
the fitting of transition-specific hazard functions, and the use of Discrete Event Simulation
to provide estimated transition probabilities. Other considerations include how to present the results
of a complex model into a deployable clinical tool.
| Original language | English |
|---|---|
| Publication status | Published - 24 Apr 2018 |
| Event | 7th Survival Analysis for Junior Researchers conference - Leiden, Netherlands Duration: 24 Apr 2018 → 26 Apr 2018 |
Conference
| Conference | 7th Survival Analysis for Junior Researchers conference |
|---|---|
| Country/Territory | Netherlands |
| City | Leiden |
| Period | 24/04/18 → 26/04/18 |