Biomarker-Based Prediction Models for Response to Treatment in Systemic Sclerosis-Related Interstitial Lung Disease
Technical Report,15 Sep 2016,14 Sep 2017
The University of Texas Health Science Center Houston United States
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Systemic sclerosis SSc-Scleroderma is associated with substantial morbidity and mortality. Interstitial lung disease ILD is the leading cause of disease-related mortality. Response to immunosuppression is highly variable in patients with SSc related ILD. The currently available clinical markers are inadequate for identifying patients who are more likely to respond to treatment. The utilized treatments are also associated with potentially serious adverse events, and their use should be reserved for highly responsive patients, further underscoring the critical need for development of reliable prediction tools. Our goal is to develop prediction tools using a combination of serum biomarkers and whole bloodskin gene expression data with potential clinical predictors. As the first step, key inflammatory serum proteins have been determined in the baseline samples of the Scleroderma Lung Study II SLS II. We are currently analyzing whether these serum proteins have predictive significance for response to treatment in SSc related ILD.
- Medicine and Medical Research
- Genetic Engineering and Molecular Biology