title: Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema.
abstract: OBJECTIVE
  There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Our objective was to review the literature on biomarkers and surrogates to develop a hierarchical schema that systematically evaluates and ranks the surrogacy status of biomarkers and surrogates; and to obtain feedback from stakeholders.
  
  
  METHODS
  After a systematic search of Medline and Embase on biomarkers, surrogate (outcomes, endpoints, markers, indicators), intermediate endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop.
  
  
  RESULTS
  The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation level of evidence schema that evaluates biomarkers along 4 domains: Target, Study Design, Statistical Strength, and Penalties. Scores derived from 3 domains the Target that the marker is being substituted for, the Design of the (best) evidence, and the Statistical strength are additive. Penalties are then applied if there is serious counterevidence. A total score (0 to 15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. It was proposed that the term "surrogate" be restricted to markers attaining Levels 1 or 2 only. Most stakeholders agreed that this operationalization of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful.
  
  
  CONCLUSIONS
  Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery, development, and approval.
authors.affiliation: Department of Rheumatology, St. George Hospital, University of New South Wales, Sydney, Australia. marissa.lassere@sesiahs.health.nsw.gov.au
authors.forename: Marissa N
authors.initials: MN
authors.lastname: Lassere
authors.forename: Kent R
authors.initials: KR
authors.lastname: Johnson
authors.forename: Maarten
authors.initials: M
authors.lastname: Boers
authors.forename: Peter
authors.initials: P
authors.lastname: Tugwell
authors.forename: Peter
authors.initials: P
authors.lastname: Brooks
authors.forename: Lee
authors.initials: L
authors.lastname: Simon
authors.forename: Vibeke
authors.initials: V
authors.lastname: Strand
authors.forename: Philip G
authors.initials: PG
authors.lastname: Conaghan
authors.forename: Mikkel
authors.initials: M
authors.lastname: Ostergaard
authors.forename: Walter P
authors.initials: WP
authors.lastname: Maksymowych
authors.forename: Robert
authors.initials: R
authors.lastname: Landewe
authors.forename: Barry
authors.initials: B
authors.lastname: Bresnihan
authors.forename: Paul-Peter
authors.initials: PP
authors.lastname: Tak
authors.forename: Richard
authors.initials: R
authors.lastname: Wakefield
authors.forename: Philip
authors.initials: P
authors.lastname: Mease
authors.forename: Clifton O
authors.initials: CO
authors.lastname: Bingham
authors.forename: Michael
authors.initials: M
authors.lastname: Hughes
authors.forename: Doug
authors.initials: D
authors.lastname: Altman
authors.forename: Marc
authors.initials: M
authors.lastname: Buyse
authors.forename: Sally
authors.initials: S
authors.lastname: Galbraith
authors.forename: George
authors.initials: G
authors.lastname: Wells
mesh_terms: D015415:Biomarkers; D019317:Evidence-Based Medicine; D006801:Humans; D009316:National Institutes of Health (U.S.); D017063:Outcome Assessment, Health Care; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012216:Rheumatic Diseases / Q000628:therapy*; D009626:Terminology as Topic; D014481:United States
chemical_list: D015415:Biomarkers