Validation of New Signal Detection Methods for Web Query Log Data Compared to Signal Detection Algorithms Used With FAERS.
Post-marketing drug surveillance is largely based on signals found in spontaneous reports from patients and healthcare providers. Rare adverse drug reactions and adverse events (AEs) that may develop after long-term exposure to a drug or from drug interactions may be missed. The US FDA and others have proposed that web-based data could be mined as a resource to detect latent signals associated with adverse drug reactions.



Recently, a web-based search query method called a query log reaction score (QLRS) was developed to detect whether AEs associated with certain drugs could be found from search engine query data. In this study, we compare the performance of two other algorithms, the proportional query ratio (PQR) and the proportional query rate ratio (Q-PRR) against that of two reference signal-detection algorithms (SDAs) commonly used with the FDA AE Reporting System (FAERS) database.



In summary, the web query methods have moderate sensitivity (80%) in detecting signals in web query data compared with reference SDAs in FAERS when the web query data are filtered, but the query metrics generate many false-positives and have low specificity compared with reference SDAs in FAERS.



Future research is needed to find better refinements of query data and/or the metrics to improve the specificity of these web query log algorithms.
Pharmacoepidemiology, Global Safety Sciences, Sanofi, 55 Corporate Dr., Bridgewater, NJ, 08807, USA. susan.colilla@sanofi.com.
Susan
S
Colilla
Microsoft Research, 13 Shenkar St., 4672513, Herzeliya, Israel.
Elad Yom
EY
Tov
Pharmacoepidemiology, Global Safety Sciences, Sanofi, 55 Corporate Dr., Bridgewater, NJ, 08807, USA.
Ling
L
Zhang
Pharmacoepidemiology & Signal Detection, Global Safety Sciences, Sanofi, 1 Avenue Pierre Brossolette, 91385, Chilly-Mazarin, France.
Marie-Laure
ML
Kurzinger
Pharmacoepidemiology & Signal Detection, Global Safety Sciences, Sanofi, 1 Avenue Pierre Brossolette, 91385, Chilly-Mazarin, France.
Stephanie
S
Tcherny-Lessenot
Pharmacoepidemiology & Signal Detection, Global Safety Sciences, Sanofi, 1 Avenue Pierre Brossolette, 91385, Chilly-Mazarin, France.
Catherine
C
Penfornis
Baxalta US, Inc., Global Drug Safety, 650 E. Kendall St., Cambridge, MA, 02142, USA.
Shang
S
Jen
US Food and Drug Administration, 10903 New Hampshire Ave., Silver Spring, MD, 20993, USA.
Danny S
DS
Gonzalez
Pfizer, Worldwide Safety, 235 E. 42nd St., New York, NY, 10017, USA.
Patrick
P
Caubel
Pharmacoepidemiology, Global Safety Sciences, Sanofi, 55 Corporate Dr., Bridgewater, NJ, 08807, USA.
Susan
S
Welsh
Pharmacoepidemiology, Global Safety Sciences, Sanofi, 55 Corporate Dr., Bridgewater, NJ, 08807, USA.
Juhaeri
J
Juhaeri
D016907:Adverse Drug Reaction Reporting Systems; D000465:Algorithms; D057225:Data Mining / Q000379:methods; D016208:Databases, Factual; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D006801:Humans; D020407:Internet; D011358:Product Surveillance, Postmarketing / Q000379:methods*; D013997:Time Factors; D014481:United States; D014486:United States Food and Drug Administration