title: Ranking adverse drug reactions with crowdsourcing.
abstract: BACKGROUND
  There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events.
  
  
  OBJECTIVE
  The intent of the study was to rank ADRs according to severity.
  
  
  METHODS
  We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs.
  
  
  RESULTS
  There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy.
  
  
  CONCLUSIONS
  ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.
authors: Department of Genetics, Stanford University, Stanford, CA, United States.
authors: Assaf
authors: http://orcid.org/0000-0003-4904-631X
authors: A
authors: Gottlieb
authors: Robert
authors: http://orcid.org/0000-0001-8149-5890
authors: R
authors: Hoehndorf
authors: Michel
authors: http://orcid.org/0000-0003-4727-9435
authors: M
authors: Dumontier
authors: Russ B
authors: http://orcid.org/0000-0003-3859-2905
authors: RB
authors: Altman
mesh_terms: D000328:Adult; D016907:Adverse Drug Reaction Reporting Systems / Q000592:standards*; D063045:Crowdsourcing / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions; D005260:Female; D006801:Humans; D020407:Internet; D008297:Male; D018802:Patient-Centered Care / Q000379:methods*; D060735:Pharmacovigilance; D018570:Risk Assessment
keywords: adverse drug reactions; alert fatigue; crowdsourcing; drug side effects; patient-centered care; pharmacovigilance