Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Oct 27, 2019
Date Accepted: Dec 15, 2019
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Blockchain-Authenticated Sharing of Cancer Patient Genomic and Clinical Outcomes Data
ABSTRACT
Background:
Efficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of cancer patients to share their treatment experiences to fuel research, despite potential risks to privacy.
Objective:
The objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for dissemination of de-identified clinical and genomic data with a focus on late stage cancer.
Methods:
We created and piloted a blockchain-authenticated system to enable securely sharing de-identified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHR), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (n=18), which we uploaded to CGT. EHR data were extracted from both a hospital cancer registry and a common data model format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold-standard source documentation for patients with available data (n=17).
Results:
While the total completeness scores were greater for the registry reports than the common data model, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting common data model. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world cancer patient data in a more clinically useful timeframe. We also developed an open-source web application to allow users to seamlessly search, browse, explore, and download CGT data.
Conclusions:
Our pilot demonstrates the willingness of cancer patients to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required.
Citation
