title: Summarizing the incidence of adverse events using volcano plots and time intervals.
abstract: BACKGROUND
  Adverse event incidence analyses are a critical component for describing the safety profile of any new intervention. The results typically are presented in lengthy summary tables. For therapeutic areas where patients have frequent adverse events, analysis and interpretation are made more difficult by the sheer number and variety of events that occur. Understanding the risk in these instances becomes even more crucial.
  
  
  OBJECTIVE
  We describe a space-saving graphical summary that overcomes the limitations of traditional presentations of adverse events and improves interpretability of the safety profile.
  
  
  METHODS
  We present incidence analyses of adverse events graphically using volcano plots to highlight treatment differences. Data from a clinical trial of patients experiencing an aneurysmal subarachnoid hemorrhage are used for illustration. Adjustments for multiplicity are illustrated.
  
  
  RESULTS
  Color is used to indicate the treatment with higher incidence; bubble size represents the total number of events that occur in the treatment arms combined. Adjustments for multiple comparisons are displayed in a manner to indicate clearly those events for which the difference between treatment arms is statistically significant. Furthermore, adverse events can be displayed by time intervals, with multiple volcano plots or animation to appreciate changes in adverse event risk over time. Such presentations can emphasize early differences across treatments that may resolve later or highlight events for which treatment differences may become more substantial with longer follow-up.
  
  
  CONCLUSIONS
  Treatment arms are compared in a pairwise fashion.
  
  
  CONCLUSIONS
  Volcano plots are space-saving tools that emphasize important differences between the adverse event profiles of two treatment arms. They can incorporate multiplicity adjustments in a manner that is straightforward to interpret and, by using time intervals, can illustrate how adverse event risk changes over the course of a clinical trial.
authors.affiliation: JMP Life Sciences, SAS Institute Inc., Cary, NC 27513, USA. richard.zink@jmp.com
authors.forename: Richard C
authors.initials: RC
authors.lastname: Zink
authors.forename: Russell D
authors.initials: RD
authors.lastname: Wolfinger
authors.forename: Geoffrey
authors.initials: G
authors.lastname: Mann
mesh_terms: D002986:Clinical Trials as Topic; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D006801:Humans; D015994:Incidence; D018570:Risk Assessment; D013345:Subarachnoid Hemorrhage / Q000628:therapy; D013812:Therapeutics / Q000009:adverse effects* / Q000706:statistics & numerical data