title: Changepoint statistics for assessing a treatment-covariate interaction.
abstract: We formulate a stochastic process approach, related to that of Miller and Siegmund (1982, Biometrics 38, 1001-1016), for comparing two treatments in the setting where a covariate might affect the difference between the treatments. We illustrate the approach with data from a recent clinical trial examining whether pretreating subjects scheduled for major elective surgery with erythropoietin reduces their subsequent requirement for blood transfusion. The approach is valuable in identifying a changepoint in baseline hemoglobin level below which subjects appear to be more responsive to the infusion of erythropoietin.
authors.affiliation: Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, California 92037, USA.
authors.forename: J A
authors.initials: JA
authors.lastname: Koziol
authors.forename: S C
authors.initials: SC
authors.lastname: Wu
mesh_terms: D000704:Analysis of Variance; D001699:Biometry; D001803:Blood Transfusion; D004311:Double-Blind Method; D004921:Erythropoietin / Q000627:therapeutic use; D006454:Hemoglobins / Q000378:metabolism; D006801:Humans; D009985:Orthopedics; D011300:Preoperative Care; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D011994:Recombinant Proteins
chemical_list: D006454:Hemoglobins; D011994:Recombinant Proteins; D004921:Erythropoietin