title: Illustration of the weibull shape parameter signal detection tool using electronic healthcare record data.
abstract: BACKGROUND
  The WSP tool has previously been proposed as a method to detect signals for adverse drug reactions utilising time-to-event data without the need for a reference population. The aim of this study was to assess the performance of the tool on two well-known and two suspected adverse drug reactions for bisphosphonates that varied in both frequency and accuracy of reporting time.
  
  
  METHODS
  The use of the WSP tool was investigated on data from a matched population cohort study involving data from UK primary care patients exposed to oral bisphosphonates. Four listed/suspected ADRs were selected for investigation: headache, musculoskeletal pain, alopecia and carpal tunnel syndrome. For each suspected ADR, a graphical exploratory analysis was performed and the WSP tool was applied for two censoring periods each.
  
  
  RESULTS
  Both of the well-known and common ADRs (headache and musculoskeletal pain) were detected using the WSP tool, and the signals were present regardless of the censoring intervals used. A signal was also detected when the event was uncommon and the timing was likely to be an accurate reflection of onset time (alopecia). This signal was only present for some of the censoring intervals. As anticipated, no signals were raised in the control groups for these events regardless of the censoring interval used. The suspected ADR, which was uncommon and where reporting times may not reflect onset time accurately (carpal tunnel syndrome), was not detected. A signal was raised in the control group but its false-positive nature was visible in the exploratory graphical analysis, which led to it (frequent but for only a limited number of consecutive dates).
  
  
  CONCLUSIONS
  This study illustrates the usability and examines the reliability of the WSP tool as a method for signal detection in electronic health records. When the events are uncommon the success of this method may depend on the reporting time accurately reflecting the true event onset time. The study has shown that further work is required to define the censoring periods. The addition of a control group is not required but may enhance causal inference by showing that other causes than the exposure may lead to a signal.
authors.affiliation: AG Epidemiologie and International Public Health, Universität Bielefeld, Pf 10 01 31, 33501, Bielefeld, Germany, odile.sauzet@uni-bielefeld.de.
authors.forename: Odile
authors.initials: O
authors.lastname: Sauzet
authors.forename: Alfonso
authors.initials: A
authors.lastname: Carvajal
authors.forename: Antonio
authors.initials: A
authors.lastname: Escudero
authors.forename: Mariam
authors.initials: M
authors.lastname: Molokhia
authors.forename: Victoria R
authors.initials: VR
authors.lastname: Cornelius
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D015331:Cohort Studies; D003198:Computer Simulation; D004164:Diphosphonates / Q000009:adverse effects; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology / Q000209:etiology; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D008962:Models, Theoretical; D013997:Time Factors; D006113:United Kingdom
chemical_list: D004164:Diphosphonates