Personalized Medicine: Predicting the Transition to Secondary Progressive Multiple Sclerosis
The postdoctoral researcher at Amsterdam University Medical Center introduces the DAAE score, a tool used to predict a patient's risk of transition to secondary progressive multiple sclerosis.
Tom A. Fuchs, MD PhD
When it comes to delivering personalized patient care, what tools do doctors need? To deliver patients personalized care, physicians and researchers like myself provide physicians with new and improved tools. These tools come in several forms. For instance, I may develop a disease-monitoring tool to answer the question, “How well is my treatment working right now?”1 I may also support personalized medicine by answering the question, “Who is most likely to benefit from this treatment?”2
To support personalized multiple sclerosis care, we recently developed the DAAE Score,3 a tool that addresses the question, “How likely is it that my patient’s disease will worsen in the years ahead?” This sort of predictive tool opens conversations between patients and their doctors about goals of care, wishes for the future, and desired path forward in balance with known risks.
Introducing the DAAE Score
This score a clinical tool for predicting the future. Because the transition to secondary progressive multiple sclerosis (SPMS) is associated with a worse prognosis, it is important for physicians to be able to predict this change. SPMS patients accumulate disability more quickly4 and they respond less to rehabilitation2 and medical therapy.5
With this in mind, we recently created the DAAE score (pronounced “day,” named from predictors used by the tool), a new clinical tool for estimating risk of transition to SPMS over 5 years.3
In the way a weather forecast helps us decide whether to pack an umbrella, the DAAE Score helps physicians make personalized care decisions to prevent problems for people with multiple sclerosis. For instance, to prevent decline, physicians may decide whether to start or stop certain medicines or whether rehabilitation is needed. The work describing the development and validation of the DAAE Score is published in Multiple Sclerosis and Related Disorders.
Using the DAAE Score
With this new clinical device, the DAAE Score, physicians can estimate risk of transition to SPMS in relapsing-remitting patient using clinical information. To do this, physicians input information about for key factors: Disease duration, Age, Age at disease onset, and physical disability measured using the Expanded Disability Status Scale. Using this information, a score from 0 to 12 is given, from which the DAAE Score provides a risk group and associated risk of deterioration (eg, low risk with 8.2% risk over 5 years). With this, the DAAE Score makes consistent risk estimates in clinical centers across the world and can be used in less than one minute.
To make the DAAE score available for patients and physicians, we created a free online web application and a paper-and-pencil form which can also be used when computers or smart phones are not available. Since its development, the DAAE score has been tested by physicians in over twenty countries, who rated it highly for usefulness and usability.
DAAE score on smartphone.
(Click to enlarge)
From Science to the Clinic
How was the DAAE score made? In recent years, more than 60 studies for predicting transition to SPMS have been published. We felt it was time to translate this scientific work to the clinic so that patients and physicians could benefit from the science. To do this, we used systematic review and advanced statistical methods to extract predictors from the previous research and create a reliable predictive clinical tool.
To accomplish our goal, we had to be careful to select the best predictors. Then, we had to rigorously test that each predictor adds value together in one algorithm. After that, we used machine-learning approaches to correctly weight each predictor in the final model. Finally, we tested the model to ensure it makes accurate predictions across research centers. In the end, the DAAE score made consistent predictions in centers across the world.
Equally important to the predictive performance of the DAAE score, we also wanted to be sure that it is accessible and easy to use in clinical environments. For this, we adapted our predictive algorithm into an online web application and paper-and-pencil reference table.
Future directions
The next steps are to improve the DAAE score so that it also considers the types of medicines patients are receiving and what is observed on MRI of the brain and spine. We are undertaking these important steps and are looking forward to providing improved versions of the DAAE score to physicians and their patients soon.
