title: Choice of non-inferiority (NI) margins does not protect against degradation of treatment effects on an average--an observational study of registered and published NI trials.
abstract: OBJECTIVE
  NI margins have to be chosen appropriately to control the risk of degradation of treatment effects in non-inferiority (NI) trials. We aimed to study whether the current choice of NI margins protects sufficiently against a degradation of treatment effect on an average.
  
  
  METHODS
  NI trials reflecting current practice were assembled and for each trial, the NI margin was translated into a likelihood of degradation. The likelihood of degradation was calculated as the conditional probability of a treatment being harmful given that it is declared non-inferior in the trial, using simulation. Its distribution among the NI trials was then studied to assess the potential risk of degradation.
  
  
  RESULTS
  The median (lower/upper quartile) NI margin among 112 binary outcome NI trials corresponded to an odds ratio of 0.57(0.45, 0.66), while among 38 NI trials with continuous outcome, to a Cohen's d of -0.42(-0.54, -0.31) and a hazard ratio of 0.82(0.73, 0.86) among 24 survival outcome NI trials. Overall, the median likelihood of degradation was 56% (45%, 62%).
  
  
  CONCLUSIONS
  Only two fifths of the current NI trials had a likelihood of degradation lower than 50%, suggesting that, in majority of the NI trials, there is no sufficient protection against degradation on an average. We suggest a third hurdle for the choice of NI margins, thus contributing a sufficient degree of protection.
authors: Clinical Epidemiology Group, Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany.
authors: Beryl Primrose
authors: BP
authors: Gladstone
authors: Clinical Epidemiology Group, Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany.
authors: Werner
authors: W
authors: Vach
mesh_terms: D002986:Clinical Trials as Topic / Q000379:methods*; D003627:Data Interpretation, Statistical; D017277:Drug Approval; D006801:Humans; D016013:Likelihood Functions; D012107:Research Design; D016896:Treatment Outcome