Profiling off-label prescriptions in cancer treatment using social health networks. Issue 3 (22nd July 2019)

• Record Type: Journal Article
• Authors: Nikfarjam, Azadeh; Ransohoff, Julia D; Callahan, Alison; Polony, Vladimir; Shah, Nigam H
• Is Part Of: JAMIA open. Volume 2:Issue 3(2019)
• Page Start: 301
• Page End: 305
• Publication Date: 2019-07-22
• Subjects: social media -- data mining -- off-label drug use -- chemotherapy -- cancer; Medical informatics -- Periodicals; 610.285
• DOI: 10.1093/jamiaopen/ooz025
• Languages: English
• ISSNs: 2574-2531

Abstract

Abstract: Objectives: To investigate using patient posts in social media as a resource to profile off-label prescriptions of cancer drugs. Methods: We analyzed patient posts from the Inspire health forums (www.inspire.com ) and extracted mentions of cancer drugs from the 14 most active cancer-type specific support groups. To quantify drug-disease associations, we calculated information component scores from the frequency of posts in each cancer-specific group with mentions of a given drug. We evaluated the results against three sources: manual review, Wolters-Kluwer Medi-span, and Truven MarketScan insurance claims. Results: We identified 279 frequently discussed and therefore highly associated drug-disease pairs from Inspire posts. Of these, 96 are FDA approved, 9 are known off-label uses, and 174 do not have records of known usage (potentially novel off-label uses). We achieved a mean average precision of 74.9% in identifying drug-disease pairs with a true indication association from patient posts and found consistent evidence in medical claims records. We achieved a recall of 69.2% in identifying known off-label drug uses (based on Wolters-Kluwer Medi-span) from patient posts.