NCI Data Jamboree (Project Abstract Submission): Submission #22

Presenter Information
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First Name: Jacob
Middle Initial: {Empty}
Last Name: Krive
Degree(s): Ph.D. MS MBA FAMIA
Position/Title/Career Status: Clinical Associate Professor
Organization: University of Illinois at Chicago
Organization Address:
Chicago

Email: krive@uic.edu

Additional Authors
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List of Additional Authors:
{Empty}


Abstract Information
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Abstract Category: Building study cohorts (e.g., with visualization capabilities)
Abstract Keywords: cancer survivorship, cardiotoxicity, metabolic toxicity, CTR-CVT, cardio-oncology
Abstract Title: National real-world cancer regimens toxicity database and decision tools to support cancer survivorship 
Abstract:
Advances in oncology care have created a large patient population of cancer survivors. Survivorship is a rising challenge due to complexity and prolonged side-effects of the oncology regimens and lack of attention to toxicities frequently discovered in widespread community medical practice. These complexities produce complications observed in conventional chemotherapies and modern therapeutic regimens. Cardio-oncology fills the care gap in treating toxicities related to cardiovascular side effects of the oncology regimens, aimed at identification and management of the short- and long-term cancer therapy related cardiovascular toxicities (CTR-CVT). There are other toxicities, such as metabolic toxicity, affecting cancer survivorship.

Survivorship care suffers from a lack of standards, quality indicators, focus on toxicity during and after clinical trials, and comprehensive ways to identify and clinically manage patients at risk. Each medical practice is small to build true evidence of toxicity. I propose a partnership to utilize and extend the existing data sources to (1) store and analyze real-world toxicity, (2) translate analyses into community medical practice by building decision support tools aiding clinicians in the process of crafting the safest oncology care plans, and (3) support development of the cardio-oncology quality standards based on real data.

I would like to build a multi-institutional team and require additional members. Abeer Mohamed is UIC endocrinologist committed to the project. I need data engineering and machine learning expertise, specific language and tools agnostic – and welcome clinical and basic science researchers. I need access to large oncology datasets with discrete and (optionally) unstructured clinical and genomic data with at least diagnoses, procedures, labs, and medications useful for tracking toxicity. The aim of this initiative is unleashing the power of data to tell an oncology toxicity story while tracking real-world patient survivorship journeys to improve the quality of cancer survivorship care – immediately translatable into community practice.