Data-driven shared decision making on cancer treatment

Helping cancer patients choose the best treatment: Data-driven shared decision making on cancer treatment for individual patients.

When someone is first diagnosed with cancer, patient and doctor jointly need to decide which treatment to opt for from the range of possible treatments. Decision tools have been developed to support this difficult process, but, unfortunately, these tend to be generic and population-based, focus exclusively on long-term survival and lack person- alised explanations. Moreover, they are ‘doctor driven’ and hence not easily understand- able and accessible for patients. As a result their usefulness is limited. In this project, we use data from millions of Dutch cancer patients to empower newly diagnosed patients during treatment decision making.

We do this by building new statistical models, determining the advantages and disadvantages of the relevant treatment options for individual patients. Based on the person and tumor characteristics, these models not only include predictions for (long term) survival, but also factors like side-effects of treatment and quality of life after treatment. Moreover, we develop a data-to-text system which automatically generates personalised explanations of the outcomes, using non-technical language and visualisations.

This system is enhanced with personalised explanations of un- certainties and risks associated with different treatments. End users (doctors and patients) are involved in all stages of the project, from the beginning, to gauge their wishes and needs, to the end, to evaluate the systems that were developed. We aim to show that our data-driven, personalised approach makes patients more knowledgeable about different treatment options and empowers them during shared decision making about treatments.

Progress

We succeeded in finding two good candidates for the respective PhD positions: one has just started (Felix Clouth), one will start in December. Additionally, we are nearly done with the consortium agreement and the datamanagement plan. We are ready to start for real.

Dissemination

We will be presenting a pitch at the Small Big Data Congress, a collaboration where Big Data meets Applied AI Congress.


Meer informatie
Titel project: Data-driven shared decision making on cancer treatment

Programma: Commit2Data-Programma

Organisatie: University of Tilburg

Looptijd: 01/09/2018 - 01/12/2002

Mede-projectleiders: Felix Clouth (aio) , Saar Hommes (aio)

Partners: IKNL

Projectmiddelen: 538.500

Nieuwsbrief

Schrijf u in voor onze nieuwsbrief en blijf op de hoogte van het laatste nieuws over Commit2data