title: Estimating the ratio of multivariate recurrent event rates with application to a blood transfusion study.
abstract: In comparative effectiveness studies of multicomponent, sequential interventions like blood product transfusion (plasma, platelets, red blood cells) for trauma and critical care patients, the timing and dynamics of treatment relative to the fragility of a patient's condition is often overlooked and underappreciated. While many hospitals have established massive transfusion protocols to ensure that physiologically optimal combinations of blood products are rapidly available, the period of time required to achieve a specified massive transfusion standard (e.g. a 1:1 or 1:2 ratio of plasma or platelets:red blood cells) has been ignored. To account for the time-varying characteristics of transfusions, we use semiparametric rate models for multivariate recurrent events to estimate blood product ratios. We use latent variables to account for multiple sources of informative censoring (early surgical or endovascular hemorrhage control procedures or death). The major advantage is that the distributions of latent variables and the dependence structure between the multivariate recurrent events and informative censoring need not be specified. Thus, our approach is robust to complex model assumptions. We establish asymptotic properties and evaluate finite sample performance through simulations, and apply the method to data from the PRospective Observational Multicenter Major Trauma Transfusion study.
authors.affiliation: 1 Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Ning
authors.affiliation: 2 Division of Clinical and Translational Sciences, Department of Internal Medicine, The University of Texas Medical School at Houston, Houston, USA.|3 Division of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Sciences Center at Houston, Houston, USA.
authors.forename: Mohammad H
authors.initials: MH
authors.lastname: Rahbar
authors.affiliation: 2 Division of Clinical and Translational Sciences, Department of Internal Medicine, The University of Texas Medical School at Houston, Houston, USA.
authors.forename: Sangbum
authors.initials: S
authors.lastname: Choi
authors.affiliation: 4 Division of Biostatistics, School of Public Health, The University of Texas Health Sciences Center at Houston, Houston, USA.
authors.forename: Jin
authors.initials: J
authors.lastname: Piao
authors.affiliation: 4 Division of Biostatistics, School of Public Health, The University of Texas Health Sciences Center at Houston, Houston, USA.
authors.forename: Chuan
authors.initials: C
authors.lastname: Hong
authors.affiliation: 5 Center for Translational Injury Research, Division of Acute Care Surgery, Department of Surgery, The University of Texas Health Science Center at Houston, Houston, USA.
authors.forename: Deborah J
authors.initials: DJ
authors.lastname: Del Junco
authors.affiliation: 6 Department of Biomedical Engineering, Wake Forest University, Winston-Salem, USA.
authors.forename: Elaheh
authors.initials: E
authors.lastname: Rahbar
authors.affiliation: 5 Center for Translational Injury Research, Division of Acute Care Surgery, Department of Surgery, The University of Texas Health Science Center at Houston, Houston, USA.
authors.forename: Erin E
authors.initials: EE
authors.lastname: Fox
authors.affiliation: 5 Center for Translational Injury Research, Division of Acute Care Surgery, Department of Surgery, The University of Texas Health Science Center at Houston, Houston, USA.
authors.forename: John B
authors.initials: JB
authors.lastname: Holcomb
authors.affiliation: 7 Department of Biostatistics, School of Public Health, Johns Hopkins University, Baltimore, USA.
authors.forename: Mei-Cheng
authors.initials: MC
authors.lastname: Wang
mesh_terms: D001803:Blood Transfusion; D006470:Hemorrhage / Q000628:therapy; D006801:Humans; D009010:Monte Carlo Method; D015999:Multivariate Analysis; D064887:Observational Studies as Topic; D011446:Prospective Studies
keywords: Informative censoring; multivariate recurrent event; rate ratio; transfusion medicine