MedicalResearch.com Interview with:
Kavita Sarin, M.D., Ph.D.
Assistant Professor of Dermatology
Stanford University Medical Center
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Drug reactions occur in the majority of patients undergoing cancer therapies. Half of serious drug reactions are detected after market approval which can result in painful complications and interruption in therapy. Post-market drug surveillance platforms such as FDA monitoring rely on medical publications and physician reporting and take time to identify trends. We sought to determine if we could identify trends in patient discussions in internet health forums to more rapidly identify chemotherapeutic drug reactions. We chose skin reactions as a proof-of-principle because patients can more easily describe what they see on their skin.
Julia Ransohoff, a medical student, and Azadeh Nikfarham, an informatics postdoctoral fellow trained a computer to recognize when a patient undergoing anti-cancer treatment with PD-1 antagonists or EGFR-inhibitors described a drug reaction in their internet forum posts.
MedicalResearch.com: What should readers take away from your report?
Response: We were surprised to find that we could detect specific skin drug reactions in internet health forums 6 to 9 months before any published reports and could even identify drug reactions that have not yet been published. This demonstrates the robust potential of internet health forums to provide useful information for doctors and medical researchers.
MedicalResearch.com: What recommendations do you have for future research as a result of this work?
Response: Moving forward, it will be important to show if this approach can be generalized to survey other types of skin and internal drug reactions.
MedicalResearch.com: Is there anything else you would like to add?
Response: We thank the Inspire team for allowing us access to their internet health forum for this study.
Ransohoff JD, Nikfarjam A, Jones E, Loew B, Kwong BY, Sarin KY, Shah NH. Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning. JAMA Oncol. Published online March 01, 2018. doi:10.1001/jamaoncol.2017.5688
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