Lead Investigator: Ari Rosenberg, University of Chicago
Title of Proposal Research: Developing predictive and prognostic Artificial Intelligent (AI) digital biomarkers for soft tissue sarcoma
Vivli Data Request: 6484
Funding Source: None
Potential Conflicts of Interest: None
Summary of the Proposed Research:
Soft tissue sarcoma (STS) is a rare group of cancers with over 13,000 new cases and over 5,000 deaths in the United States annually. Survival remains poor for patients with advanced STS with median survival of approximately 14-19 months and 2-year survival rates of 20-30%. For chemotherapy-sensitive subtypes of STS, a chemotherapy called doxorubicin remains the backbone of standard front-line treatment. Given the biologic and molecular heterogeneity of STS, an ability to predict patient benefit to doxorubicin in soft tissue sarcoma is urgently needed. To address the unmet need for rapid, accurate classification of STS subtypes and predict treatment response, we seek to identify the hidden information in a patient’s diagnostic pathology. The overall goal of this proposal is to use artificial intelligence in order to predict soft tissue sarcoma (STS) patient clinical treatment response to doxorubicin alone or in combination directly from digitized versions of their diagnostic slides.
A Randomized, Double-Blind, Placebo-Controlled, Phase 3 Trial of Doxorubicin Plus Olaratumab Versus Doxorubicin Plus Placebo in Patients With Advanced or Metastatic Soft Tissue Sarcoma
Data Contributor: Lilly
Study ID: NCT02451943
Sponsor ID: 15677
Update: This data request was withdrawn on 28-Apr-2022 by the researcher.