Developing a Treatment Selection Approach to Inform Patients of the Impact of Treatment Options

With multiple treatments available for many mental health conditions, it’s vitally important we know which will work best for each individual.

The project

Faced with multiple treatment options – such as medication or cognitive behavioural therapy for depression – mental health professionals usually rely on a combination of clinical intuition and recent research.

But what if this process could be made more systematic? That’s the question that the team at the University of Pennsylvania is looking to answer.

The process

Using cutting-edge statistical modelling, our researchers are analysing:

• The wealth of data that exists on the effects of different treatments
• The ways that treatments interact
• The factors that affect how people respond to treatment

From this, they’ve developed an analytical model that produces a ‘Personalised Advantage Index’ (PAI) – listing the likely impact of treatment options for each patient.

To test and refine the PAI, they’re looking at existing largescale treatment studies – and comparing the treatments that actually worked best with the ones a PAI would have recommended. The next step is to test the PAI in new trials, to see just how effective it can really be.

The potential

It can take months or years for doctors to find a mental health treatment that works, with patients not only seeing little improvement but also having to deal with side effects.

The PAI could transform this situation – making individually tailored mental health care a reality, and enabling patients and doctors to choose the best treatments together.