ArticleJAMIA open2019
Profiling off-label prescriptions in cancer treatment using social health networks.
Article in JAMIA open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Application of natural language processing techniques to identify off-label drug usage from various online health communities.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Strategies for Testing Intervention Matching Schemes in Cancer.Clinical pharmacology and therapeutics · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo investigate using patient posts in social media as a resource to profile off-label prescriptions of cancer drugs.
methodsWe 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.
resultsWe 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.
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