title: Permutation criteria to evaluate multiple clinical endpoints in a proof-of-concept study: lessons from Pre-RELAX-AHF.
abstract: BACKGROUND
  Clinically relevant endpoints cannot be routinely targeted with reasonable power in a small study. Hence, proof-of-concept studies are often powered to a primary surrogate endpoint. However, in acute heart failure (AHF) effects on surrogates have not translated into clinical benefit in confirmatory studies. Although observing an effect on one of many endpoints due to chance is likely, observing concurrent positive trends across several outcomes by chance is usually unlikely.
  
  
  METHODS
  Pre-RELAX-AHF, which compared 4 relaxin doses with placebo in AHF, has shown favourable trends versus placebo (one-sided P < 0.10) on six of nine clinical endpoints in the 30 μg/kg/day group. To illustrate evaluation of multiple, correlated clinical endpoints for evidence of efficacy and for dose selection, a permutation method was applied retrospectively. By randomly re-assigning the treatment group to the actual data for each of the 229 subjects, 20,000 permutation samples were constructed.
  
  
  RESULTS
  The permutation P value for at least six favourable trends among nine endpoints in any dose groups was 0.0073 (99.9% CI 0.0053-0.0093). This is higher than would be expected if the endpoints were uncorrelated (0.00026), but much lower than the probability of observing one of nine comparisons significant at the traditional two-sided P < 0.05 (0.74). Thus, the result was unlikely due to correlated endpoints or to chance.
  
  
  CONCLUSIONS
  Examining consistency of effect across multiple clinical endpoints in a proof-of-concept study may identify efficacious therapies and enable dose selection for confirmatory trials. The merit of the approach described requires confirmation through prospective application in designing future studies.
authors.affiliation: Momentum Research, Inc., Durham, NC, USA. bethdavison@momentum-research.com
authors.forename: Beth A
authors.initials: BA
authors.lastname: Davison
authors.forename: Gad
authors.initials: G
authors.lastname: Cotter
authors.forename: Hengrui
authors.initials: H
authors.lastname: Sun
authors.forename: Li
authors.initials: L
authors.lastname: Chen
authors.forename: John R
authors.initials: JR
authors.lastname: Teerlink
authors.forename: Marco
authors.initials: M
authors.lastname: Metra
authors.forename: G Michael
authors.initials: GM
authors.lastname: Felker
authors.forename: Adriaan A
authors.initials: AA
authors.lastname: Voors
authors.forename: Piotr
authors.initials: P
authors.lastname: Ponikowski
authors.forename: Gerasimos
authors.initials: G
authors.lastname: Filippatos
authors.forename: Barry
authors.initials: B
authors.lastname: Greenberg
authors.forename: Sam L
authors.initials: SL
authors.lastname: Teichman
authors.forename: Elaine
authors.initials: E
authors.lastname: Unemori
authors.forename: Gary G
authors.initials: GG
authors.lastname: Koch
mesh_terms: D000208:Acute Disease; D004305:Dose-Response Relationship, Drug; D023381:Endpoint Determination / Q000379:methods*; D006333:Heart Failure / Q000188:drug therapy*; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012065:Relaxin / Q000008:administration & dosage / Q000627:therapeutic use*; D012189:Retrospective Studies; D016896:Treatment Outcome
chemical_list: D012065:Relaxin