title: Calculation of NNTs in RCTs with time-to-event outcomes: a literature review.
abstract: BACKGROUND
  The number needed to treat (NNT) is a well-known effect measure for reporting the results of clinical trials. In the case of time-to-event outcomes, the calculation of NNTs is more difficult than in the case of binary data. The frequency of using NNTs to report results of randomised controlled trials (RCT) investigating time-to-event outcomes and the adequacy of the applied calculation methods are unknown.
  
  
  METHODS
  We searched in PubMed for RCTs with parallel group design and individual randomisation, published in four frequently cited journals between 2003 and 2005. We evaluated the type of outcome, the frequency of reporting NNTs with corresponding confidence intervals, and assessed the adequacy of the methods used to calculate NNTs in the case of time-to-event outcomes.
  
  
  RESULTS
  The search resulted in 734 eligible RCTs. Of these, 373 RCTs investigated time-to-event outcomes and 361 analyzed binary data. In total, 62 articles reported NNTs (34 articles with time-to-event outcomes, 28 articles with binary outcomes). Of the 34 articles reporting NNTs derived from time-to-event outcomes, only 17 applied an appropriate calculation method. Of the 62 articles reporting NNTs, only 21 articles presented corresponding confidence intervals.
  
  
  CONCLUSIONS
  The NNT is used as effect measure to present the results from RCTs with binary and time-to-event outcomes in the current medical literature. In the case of time-to-event data incorrect methods were frequently applied. Confidence intervals for NNTs were given in one third of the NNT reporting articles only. In summary, there is much room for improvement in the application of NNTs to present results of RCTs, especially where the outcome is time to an event.
authors.affiliation: Institute for Quality and Efficiency in Health Care (IQWiG), Cologne, Germany. mandy.hildebrandt@iqwig.de
authors.forename: Mandy
authors.initials: M
authors.lastname: Hildebrandt
authors.forename: Elke
authors.initials: E
authors.lastname: Vervölgyi
authors.forename: Ralf
authors.initials: R
authors.lastname: Bender
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D018401:Sample Size