PMID- 29677995
OWN - NLM
STAT- MEDLINE
DCOM- 20180611
LR  - 20181202
IS  - 1879-8365 (Electronic)
IS  - 0926-9630 (Linking)
VI  - 247
DP  - 2018
TI  - Signal Detection for Baclofen in Web Forums: A Preliminary Study.
PG  - 421-425
AB  - Web forums are proposed as a new complementary source of knowledge to spontaneous 
      reports by patients and healthcare professionals due to underreporting of adverse 
      drug reactions (ADRs). Some authors suggest that signal detection could be a 
      convenient method for gathering mentions of ADRs in patients' posts. Signal 
      detection methods were proposed to mine pharmacovigilance databases, but little 
      is known about their applicability to web forums. We describe a method 
      implementing several traditional decision rules on signal detection with baclofen 
      applied to a set of more than 6 million posts. We then cross-validated four 
      unexpected signals applying a logistic regression method. Most adverse effects 
      (AEs) described in the summary of product characteristics of baclofen were 
      detected by signal detection methods. Some unexpected AEs were too. Therefore, 
      web forums are confirmed as a complementary resource for improving current 
      knowledge in pharmacovigilance by detecting unexpected adverse drug reactions.
FAU - Karapetiantz, Pierre
AU  - Karapetiantz P
AD  - Sorbonne Universite, Inserm, universite Paris 13, Laboratoire d'informatique 
      medicale et d'ingenierie des connaissances en e-sante, LIMICS, F-75006 Paris, 
      France.
FAU - Audeh, Bissan
AU  - Audeh B
AD  - Sorbonne Universite, Inserm, universite Paris 13, Laboratoire d'informatique 
      medicale et d'ingenierie des connaissances en e-sante, LIMICS, F-75006 Paris, 
      France.
FAU - Lillo-Le Louet, Agnes
AU  - Lillo-Le Louet A
AD  - Centre regional de pharmacovigilance HEGP, AP-HP Paris, France.
FAU - Bousquet, Cedric
AU  - Bousquet C
AD  - Sorbonne Universite, Inserm, universite Paris 13, Laboratoire d'informatique 
      medicale et d'ingenierie des connaissances en e-sante, LIMICS, F-75006 Paris, 
      France.
LA  - eng
PT  - Journal Article
PL  - Netherlands
TA  - Stud Health Technol Inform
JT  - Studies in health technology and informatics
JID - 9214582
RN  - 0 (Muscle Relaxants, Central)
RN  - H789N3FKE8 (Baclofen)
MH  - Adverse Drug Reaction Reporting Systems
MH  - Baclofen/*adverse effects
MH  - Databases, Factual
MH  - *Drug-Related Side Effects and Adverse Reactions
MH  - Health Personnel
MH  - Humans
MH  - Muscle Relaxants, Central/*adverse effects
MH  - *Pharmacovigilance
OTO - NOTNLM
OT  - Adverse drug reaction
OT  - Baclofen
OT  - Forums
OT  - Logistic regression
OT  - Signal detection
OT  - Social media
EDAT- 2018/04/22 06:00
MHDA- 2018/06/12 06:00
CRDT- 2018/04/22 06:00
PHST- 2018/04/22 06:00 [entrez]
PHST- 2018/04/22 06:00 [pubmed]
PHST- 2018/06/12 06:00 [medline]
PST - ppublish
SO  - Stud Health Technol Inform. 2018;247:421-425.