PMID- 29098610
OWN - NLM
STAT- MEDLINE
DCOM- 20181004
LR  - 20181004
IS  - 1179-1942 (Electronic)
IS  - 0114-5916 (Linking)
VI  - 41
IP  - 3
DP  - 2018 Mar
TI  - Reported Adverse Events with Painkillers: Data Mining of the US Food and Drug 
      Administration Adverse Events Reporting System.
PG  - 313-320
LID - 10.1007/s40264-017-0611-5 [doi]
AB  - INTRODUCTION: One-third of adults in the USA experience chronic pain and use a 
      variety of painkillers, such as nonsteroidal anti-inflammatory drugs (NSAIDs), 
      acetaminophen, and opioids. However, some serious adverse events (AEs), such as 
      cardiovascular incidents, overdose, and death, have been found to be related to 
      painkillers. METHODS: We used 2015 and 2016 AE reports from the US FDA's Adverse 
      Events Reporting System (FAERS) to conduct exploratory analysis on the 
      demographics of those who reported painkiller-related AEs, examine the AEs most 
      commonly associated with different types of painkillers, and identify potential 
      safety signals. Summary descriptive statistics and proportional reporting ratios 
      (PRRs) were performed. RESULTS: Out of over 2 million reports submitted to FAERS 
      in 2015 and 2016, a total of 64,354 AE reports were associated with painkillers. 
      Reports of opioid-associated AEs were more likely to be from males or younger 
      patients (mean age 47.6 years). The highest numbers of AEs were reported for 
      NSAID and opioid use, and the most commonly found AEs were related to drug 
      ineffectiveness, administration issues, abuse, and overdose. Death was reported 
      in 20.0% of the reports, and serious adverse reactions, including death, were 
      reported in 67.0%; both adverse outcomes were highest among patients using 
      opioids or combinations of painkillers and were associated with PRRs of 2.12 and 
      1.87, respectively. CONCLUSIONS: This study examined the AEs most commonly 
      associated with varying classes of painkillers by mining the FAERS database. Our 
      results and methods are relevant for future secondary analyses of big data and 
      for understanding adverse outcomes related to painkillers.
FAU - Min, Jae
AU  - Min J
AD  - Department of Epidemiology, University of Florida, 2004 Mowry Rd, PO Box 100231, 
      Gainesville, FL, 32610, USA. jaemin@ufl.edu.
FAU - Osborne, Vicki
AU  - Osborne V
AD  - Department of Epidemiology, University of Florida, 2004 Mowry Rd, PO Box 100231, 
      Gainesville, FL, 32610, USA.
FAU - Kowalski, Allison
AU  - Kowalski A
AD  - Department of Epidemiology, University of Florida, 2004 Mowry Rd, PO Box 100231, 
      Gainesville, FL, 32610, USA.
FAU - Prosperi, Mattia
AU  - Prosperi M
AD  - Department of Epidemiology, University of Florida, 2004 Mowry Rd, PO Box 100231, 
      Gainesville, FL, 32610, USA.
LA  - eng
PT  - Journal Article
PL  - New Zealand
TA  - Drug Saf
JT  - Drug safety
JID - 9002928
RN  - 0 (Analgesics, Opioid)
SB  - IM
MH  - Adverse Drug Reaction Reporting Systems/*statistics & numerical data
MH  - Analgesics, Opioid/*adverse effects
MH  - Data Mining/statistics & numerical data
MH  - Databases, Factual
MH  - Drug-Related Side Effects and Adverse Reactions/etiology
MH  - Female
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - United States
MH  - United States Food and Drug Administration/statistics & numerical data
EDAT- 2017/11/04 06:00
MHDA- 2018/10/05 06:00
CRDT- 2017/11/04 06:00
PHST- 2017/11/04 06:00 [pubmed]
PHST- 2018/10/05 06:00 [medline]
PHST- 2017/11/04 06:00 [entrez]
AID - 10.1007/s40264-017-0611-5 [pii]
AID - 10.1007/s40264-017-0611-5 [doi]
PST - ppublish
SO  - Drug Saf. 2018 Mar;41(3):313-320. doi: 10.1007/s40264-017-0611-5.