title: Accounting for dropout reason in longitudinal studies with nonignorable dropout.
abstract: Dropout is a common problem in longitudinal cohort studies and clinical trials, often raising concerns of nonignorable dropout. Selection, frailty, and mixture models have been proposed to account for potentially nonignorable missingness by relating the longitudinal outcome to time of dropout. In addition, many longitudinal studies encounter multiple types of missing data or reasons for dropout, such as loss to follow-up, disease progression, treatment modifications and death. When clinically distinct dropout reasons are present, it may be preferable to control for both dropout reason and time to gain additional clinical insights. This may be especially interesting when the dropout reason and dropout times differ by the primary exposure variable. We extend a semi-parametric varying-coefficient method for nonignorable dropout to accommodate dropout reason. We apply our method to untreated HIV-infected subjects recruited to the Acute Infection and Early Disease Research Program HIV cohort and compare longitudinal CD4+T cell count in injection drug users to nonusers with two dropout reasons: anti-retroviral treatment initiation and loss to follow-up.
authors.affiliation: 1 Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA.
authors.forename: Camille M
authors.initials: CM
authors.lastname: Moore
authors.affiliation: 1 Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA.
authors.forename: Samantha
authors.initials: S
authors.lastname: MaWhinney
authors.affiliation: 1 Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA.|2 Veterans Integrated Service Network 19, Mental Illness Research Education and Clinical Center, Denver VA Medical Center, Denver, CO, USA.
authors.forename: Jeri E
authors.initials: JE
authors.lastname: Forster
authors.affiliation: 1 Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA.
authors.forename: Nichole E
authors.initials: NE
authors.lastname: Carlson
authors.affiliation: 1 Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA.
authors.forename: Amanda
authors.initials: A
authors.lastname: Allshouse
authors.affiliation: 1 Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA.|3 Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA.
authors.forename: Xinshuo
authors.initials: X
authors.lastname: Wang
authors.affiliation: 4 Division of Hematology and Chronic Viral Illness Service, McGill University, Montreal, Quebec, Canada.
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Routy
authors.affiliation: 5 Vancouver Infectious Diseases Centre, Vancouver, British Columbia, Canada.
authors.forename: Brian
authors.initials: B
authors.lastname: Conway
authors.affiliation: 6 Division of Infectious Diseases, University of Colorado Denver, Aurora, CO, USA.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Connick
mesh_terms: D000328:Adult; D018791:CD4 Lymphocyte Count; D015496:CD4-Positive T-Lymphocytes / Q000166:cytology; D018450:Disease Progression; D055030:Drug Users / Q000706:statistics & numerical data; D005500:Follow-Up Studies; D015658:HIV Infections / Q000188:drug therapy / Q000276:immunology; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015233:Models, Statistical; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D015819:Substance Abuse, Intravenous; D013997:Time Factors
keywords: B-spline; HIV/AIDS; dropout; longitudinal data; nonignorable missing data; varying-coefficient model