Drug Safety

, Volume 41, Issue 3, pp 313–320 | Cite as

Reported Adverse Events with Painkillers: Data Mining of the US Food and Drug Administration Adverse Events Reporting System

  • Jae Min
  • Vicki Osborne
  • Allison Kowalski
  • Mattia Prosperi
Original Research Article



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.


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.


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.


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.



The authors thank the patients, healthcare providers, and others who contribute to the FAERS database and the FDA for making these data publicly available.

Compliance with ethical standards


No sources of funding were used to assist in the preparation of this study.

Conflicts of interest

Jae Min, Vicki Osborne, Allison Kowalski, and Mattia Prosperi have no conflicts of interest that are directly relevant to the content of this study.

Supplementary material

40264_2017_611_MOESM1_ESM.pdf (135 kb)
Supplementary material 1 (PDF 134 kb)


  1. 1.
    Institute of Medicine. Relieving pain in America: a blueprint for transforming prevention, care, education, and research. Washington, DC, National Academies Press; 2011. Accessed 13 Mar 2017.
  2. 2.
    Center for Health Statistics N. National hospital ambulatory medical care survey: 2013 Emergency Department Summary Tables. 2013. Accessed 13 Mar 2017.
  3. 3.
    Zhou Y, Boudreau DM, Freedman AN. Trends in the use of aspirin and nonsteroidal anti-inflammatory drugs in the general US population. Pharmacoepidemiol Drug Saf. 2014;23:43–50. Scholar
  4. 4.
    Gunter BR, Butler KA, Wallace RL, Smith SM, Harirforoosh S. Non-steroidal anti-inflammatory drug-induced cardiovascular adverse events: a meta-analysis. J Clin Pharm Ther. 2017;42:27–38.CrossRefPubMedGoogle Scholar
  5. 5.
    Varga Z, Rafay ali Sabzwari S, Vargova V. Cardiovascular risk of nonsteroidal anti-inflammatory drugs: an under-recognized public health issue. Cureus. 2017;9:e1144.PubMedPubMedCentralGoogle Scholar
  6. 6.
    Conaghan PG. A turbulent decade for NSAIDs: update on current concepts of classification, epidemiology, comparative efficacy, and toxicity. Rheumatol Int. 2012;32:1491–502.CrossRefPubMedGoogle Scholar
  7. 7.
    Næsdal J, Brown K. NSAID-associated adverse effects and acid control aids to prevent them: a review of current treatment options. Drug Saf. 2006;29:119–32.CrossRefPubMedGoogle Scholar
  8. 8.
    Hinz B, Cheremina O, Brune K. Acetaminophen (paracetamol) is a selective cyclooxygenase-2 inhibitor in man. FASEB J. 2008;22:383–90.CrossRefPubMedGoogle Scholar
  9. 9.
    Jozwiak-Bebenista M, Nowak JZ. Paracetamol: mechanism of action, applications and safety concern. Acta Pol Pharm Drug Res. 2014;71:11–23.Google Scholar
  10. 10.
    Nourjah P, Ahmad SR, Karwoski C, Willy M. Estimates of acetaminophen (paracetamol)-associated overdoses in the United States. Pharmacoepidemiol Drug Saf. 2006;15:398–405.CrossRefPubMedGoogle Scholar
  11. 11.
    Ghelardini C, Di Cesare Mannelli L, Bianchi E. The pharmacological basis of opioids. Clin Cases Miner Bone Metab. 2015;12:219–21.PubMedPubMedCentralGoogle Scholar
  12. 12.
    Fox LM, Hoffman RS, Vlahov D, Manini AF. Risk factors for severe respiratory depression from prescription opioid overdose. Addiction. 2017. Scholar
  13. 13.
    Garg RK, Fulton-kehoe D, Franklin GM. Patterns of opioid use and risk of opioid overdose death among medicaid patients. Med Care. 2017;55:661–8.CrossRefPubMedGoogle Scholar
  14. 14.
    Sun EC, Dixit A, Humphreys K, Darnall BD, Baker LC, Mackey S. Association between concurrent use of prescription opioids and benzodiazepines and overdose: retrospective analysis. BMJ. 2017;356:j760.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Boscarino JA, Kirchner HL, Pitcavage JM, Nadipelli VR, Ronquest NA, Fitzpatrick MH, et al. Factors associated with opioid overdose: a 10-year retrospective study of patients in a large integrated health care system. Subst Abuse Rehabil. 2016;7:131–41.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    US Food and Drug Administration. Reporting serious problems to FDA—what is a serious adverse event? Office of the Commissioner; 2016. Accessed 27 Jun 2017.
  17. 17.
    US Food and Drug Administration. FDA adverse events reporting system (FAERS)—Reports received and reports entered into FAERS by year. Center for Drug Evaluation and Research. 2014. Accessed 13 Mar 2017.
  18. 18.
    Bates DW, Spell N, Cullen DJ, Burdick E, Laird N, Petersen LA, et al. The costs of adverse drug events in hospitalized patients. Adverse Drug Events Prevention Study Group. JAMA. 1997;277:307–11.CrossRefPubMedGoogle Scholar
  19. 19.
    Bate A, Evans SJW. Quantitative signal detection using spontaneous ADR reporting. Pharmacoepidemiol Drug Saf. 2009;18:427–36. Scholar
  20. 20.
    Duggirala HJ, Tonning JM, Smith E, Bright R a., Baker JD, Ball R, et al. Data mining at FDA. 2015;1–24. Accessed 27 Jun 2017.
  21. 21.
    Wallenstein EJ, Fife D. Temporal patterns of NSAID the weber effect revisited. Drug Saf. 2001;24:233–7. Scholar
  22. 22.
    Hoffman KB, Dimbil M, Erdman CB, Tatonetti NP, Overstreet BM. The weber effect and the united states food and drug administration’s adverse event reporting system (FAERS): Analysis of sixty-two drugs approved from 2006 to 2010. Drug Saf. 2014;37:283–94. Scholar
  23. 23.
    Gereau RW, Sluka KA, Maixner W, Savage SR, Price TJ, Murinson BB, et al. A pain research agenda for the 21st century. J Pain. 2014;15:1203–14.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jae Min
    • 1
  • Vicki Osborne
    • 1
  • Allison Kowalski
    • 1
  • Mattia Prosperi
    • 1
  1. 1.Department of EpidemiologyUniversity of FloridaGainesvilleUSA

Personalised recommendations