Prediction Scores for Treatment Response in Liver Disease
Bettina Hansen is Associate Professor at the department of Gastroenterology and Hepatology, Erasmus MC University Medical Center, Rotterdam, the Netherlands. She graduated in 1991 as statistician at the Institute of Mathematical Statistics, University of Copenhagen, Denmark.
Abstract: A major challenge conducting studies in liver diseases is the slowly progressive nature of these chronic diseases. Patients need lifelong treatment or may be given a knockout treatment accompanied with numerous and sometime severe side effects. Identification of patients who benefit from treatment, who respond inadequate and could better stop treatment or need adjustment of treatment is of crucial importance. Even more important are the long‐term treatment effects on prevention of disease progression (decompensation and liver cancer), transplantation or death.
Development of prediction scores are an increasingly popular tool, but the statistical validation and dynamic improvement of these prediction scores as well as usability and impact needs more attention.
Other challenges we are facing in search of factors associated with treatment response in liver diseases are the relative low prevalence of the disease in combination with poor response to treatment and need of long‐term follow‐up before clinical endpoints are observed. For the purpose of designing robust prediction scores huge meta‐analysis of individual patient data are necessary and collaboration across centers and with pharmaceutical are essential. With collaboration between centers across the globe and pharmaceuticals we established International platforms and assembled huge databases to facilitate construction of new prediction scores for treatment in the field of viral hepatitis as well as in the area of primary biliary cholangitis. Current work involves a dynamic stopping rule of the 52 weeks interferon treatment of hepatitis B identifying patients at week 12 or 24 weeks who do not respond to treatment. For the lifelong treatment of primary biliary cholangitis a prognostic index was developed to early on identify patients at high risk for liver transplantation of death and therefore in need of additional therapy.
The prediction scores have had enormous impact on novel treatments and identification of patients at risk. Updates of the prediction scores are continuously being considered as well as exploring methods to make the scores more usable in daily clinical practice – bringing statistics to the patient and the specialists.
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