Accession Number:

AD1095189

Title:

Biomarker-Based Prediction Models for Response to Treatment in Systemic Sclerosis-Related Interstitial Lung Disease

Descriptive Note:

Technical Report,15 Sep 2017,14 Sep 2018

Corporate Author:

University of Texas Health Science Center at Houston Houston United States

Personal Author(s):

Report Date:

2018-10-01

Pagination or Media Count:

14.0

Abstract:

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 the likely responders. 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, the baseline serum samples of the Scleroderma Lung Study II SLS II were examined. The related analysis has been completed. We are currently confirming the candidate cytokine predictors in the GENISOS cohort. We are currently confirming our protein and transcript level data in an independent cohort.

Subject Categories:

  • Medicine and Medical Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE