title: Validation of intermediate end points in cancer research.
abstract: Investigations using intermediate end points as cancer surrogates are quicker, smaller, and less expensive than studies that use malignancy as the end point. We present a strategy for determining whether a given biomarker is a valid intermediate end point between an exposure and incidence of cancer. Candidate intermediate end points may be selected from case series, ecologic studies, and animal experiments. Prospective cohort and sometimes case-control studies may be used to quantify the intermediate end point-cancer association. The most appropriate measure of this association is the attributable proportion. The intermediate end point is a valid cancer surrogate if the attributable proportion is close to 1.0, but not if it is close to 0. Usually, the attributable proportion is close to neither 1.0 nor 0; in this case, valid surrogacy requires that the intermediate end point mediate an established exposure-cancer relation. This would in turn imply that the exposure effect would vanish if adjusted for the intermediate end point. We discuss the relative advantages of intervention and observational studies for the validation of intermediate end points. This validation strategy also may be applied to intermediate end points for adverse reproductive outcomes and chronic diseases other than cancer.
authors.affiliation: Division of Cancer Prevention and Control, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892.
authors.forename: A
authors.initials: A
authors.lastname: Schatzkin
authors.forename: L S
authors.initials: LS
authors.lastname: Freedman
authors.forename: M H
authors.initials: MH
authors.lastname: Schiffman
authors.forename: S M
authors.initials: SM
authors.lastname: Dawsey
mesh_terms: D014408:Biomarkers, Tumor; D016022:Case-Control Studies; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D006801:Humans; D015994:Incidence; D009369:Neoplasms / Q000453:epidemiology*; D015203:Reproducibility of Results; D012107:Research Design; D013223:Statistics as Topic / Q000379:methods
chemical_list: D014408:Biomarkers, Tumor