Tae Hyun Jung1, Tassos Kyriakides2, Mark Holodniy3, Denise Esserman1, Peter Peduzzi4. 1. Yale Center for Analytical Sciences, Department of Biostatistics, Yale School of Public Health, 300 George Street, New Haven, CT 06520, USA. 2. Yale Center for Analytical Sciences, Department of Biostatistics, Yale School of Public Health, 300 George Street, New Haven, CT 06520, USA; VA Cooperative Studies Program Coordinating Center, VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT 06516, USA. 3. VA Palo Alto Health Care System, 3801 Miranda Ave, Palo Alto, CA 94304, USA; Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, USA. 4. Yale Center for Analytical Sciences, Department of Biostatistics, Yale School of Public Health, 300 George Street, New Haven, CT 06520, USA; VA Cooperative Studies Program Coordinating Center, VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT 06516, USA. Electronic address: peter.peduzzi@yale.edu.
Abstract
OBJECTIVES: To investigate the association between recurrent AIDS-defining events and a semicompeting risk of death in patients with advanced, multidrug-resistant human immunodeficiency virus infection and to identify individuals at increased risk for these events using a joint frailty model. STUDY DESIGN AND SETTING:Three hundred sixty-eight patients with antiretroviral treatment failure in the Options in Management of Antiretrovirals Trial randomized to two antiretroviral treatment strategies using a 2 × 2 factorial design, intensive vs. standard and interruption vs. continuation, and followed for development of AIDS-defining events and death. RESULTS: Participants were heterogeneous for risk of AIDS-defining events and death (P < 0.001), and AIDS-defining events were strongly associated with death (P < 0.001), irrespective of treatment. The frailty model was used to classify individuals into high- and low-risk groups based on unobserved heterogeneity. Low-risk individuals were unlikely to die (0%) or have an AIDS-defining event (<4%), whereas high-risk individuals had event rates approaching 70%. About one-third of high-risk individuals had accelerated mortality, all who died before experiencing an AIDS-defining event. High-risk was associated with being immunocompromised and higher predicted 5-year mortality. CONCLUSION: The joint frailty model permits classification of individuals into risk groups based on unobserved heterogeneity that may be identifiable based on observed covariates, providing advantages over the traditional Cox model.
RCT Entities:
OBJECTIVES: To investigate the association between recurrent AIDS-defining events and a semicompeting risk of death in patients with advanced, multidrug-resistant human immunodeficiency virus infection and to identify individuals at increased risk for these events using a joint frailty model. STUDY DESIGN AND SETTING: Three hundred sixty-eight patients with antiretroviral treatment failure in the Options in Management of Antiretrovirals Trial randomized to two antiretroviral treatment strategies using a 2 × 2 factorial design, intensive vs. standard and interruption vs. continuation, and followed for development of AIDS-defining events and death. RESULTS:Participants were heterogeneous for risk of AIDS-defining events and death (P < 0.001), and AIDS-defining events were strongly associated with death (P < 0.001), irrespective of treatment. The frailty model was used to classify individuals into high- and low-risk groups based on unobserved heterogeneity. Low-risk individuals were unlikely to die (0%) or have an AIDS-defining event (<4%), whereas high-risk individuals had event rates approaching 70%. About one-third of high-risk individuals had accelerated mortality, all who died before experiencing an AIDS-defining event. High-risk was associated with being immunocompromised and higher predicted 5-year mortality. CONCLUSION: The joint frailty model permits classification of individuals into risk groups based on unobserved heterogeneity that may be identifiable based on observed covariates, providing advantages over the traditional Cox model.
Authors: Amy C Justice; Sharada P Modur; Janet P Tate; Keri N Althoff; Lisa P Jacobson; Kelly A Gebo; Mari M Kitahata; Michael A Horberg; John T Brooks; Kate Buchacz; Sean B Rourke; Anita Rachlis; Sonia Napravnik; Joseph Eron; James H Willig; Richard Moore; Gregory D Kirk; Ronald Bosch; Benigno Rodriguez; Robert S Hogg; Jennifer Thorne; James J Goedert; Marina Klein; John Gill; Steven Deeks; Timothy R Sterling; Kathryn Anastos; Stephen J Gange Journal: J Acquir Immune Defic Syndr Date: 2013-02-01 Impact factor: 3.731
Authors: Jennifer K Rogers; Stuart J Pocock; John J V McMurray; Christopher B Granger; Eric L Michelson; Jan Östergren; Marc A Pfeffer; Scott D Solomon; Karl Swedberg; Salim Yusuf Journal: Eur J Heart Fail Date: 2013-12-18 Impact factor: 15.534