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2020-04-03
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EMULATING A TRIAL OF JOINT DYNAMIC STRATEGIES: AN APPLICATION TO MONITORING AND TREATMENT OF HIV-POSITIVE INDIVIDUALS
Dynamic regime
Joint treatment strategies
Marginal structural model
No direct effect
Ellen C. Caniglia1,2 James M. Robins1,3 Lauren E. Cain1 Caroline Sabin4 Roger Logan1 Sophie Abgrall5 Michael J. Mugavero6 Sonia Hernández-Díaz1 Laurence Meyer7 Remonie Seng7 Daniel R. Drozd8 George R. Seage III1 Fabrice Bonnet9 Fabien Le Marec9 Richard D. Moore10 Peter Reiss11 Ard van Sighem11 William C. Mathews12 Inma Jarrín13 Belén Alejos13 Steven G. Deeks14 Roberto Muga15 Stephen L. Boswell16 Elena Ferrer17 Joseph J. Eron18 John Gill19 Antonio Pacheco20 Beatriz Grinsztejn20 Sonia Napravnik18 Sophie Jose4 Andrew Phillips4 Amy Justice21 Janet Tate21 Heiner C. Bucher22 Matthias Egger23 Hansjakob Furrer24 Jose M. Miro25 Jordi Casabona26 Kholoud Porter4 Giota Touloumi27 Heidi Crane8 Dominique Costagliola28 Michael Saag29 Miguel A. Hernán1,3,30 1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 2Department of Population Health, School of Medicine, New York University, New York, New York 3Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 4University College London, London, UK 5APHP Hôpital Avicenne, Bobigny, France 6School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama 7Inserm, Université Paris Sud, Orsay, France 8University of Washington, Seattle, Washington 9Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France 10School of Medicine, The Johns Hopkins University, Baltimore, Maryland 11Academisch Medisch Centrum Geneeskunde, Amsterdam, The Netherlands 12Department of Medicine, University of California San Diego Health, San Diego, California 13National Center of Epidemiology, Instituto de Salud Carlos III, Madrid, Spain 14School of Medicine, University of California, San Francisco, San Francisco, California 15Germans Trias Hospital, Barcelona, Spain 16Fenway Health, Boston, Massachusetts 17Hospital Universitari de Bellvitge, Barcelona, Spain 18Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 19Southern Alberta HIV Program, Calgary, Canada 20Fundação Oswaldo Cruz, Rio de Janeiro, Brazil 21School of Public Health, Yale University, New Haven, Connecticut 22Universitätsspital Basel, Basel, Switzerland 23Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland 24Division of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland 25University of Barcelona, Barcelona, Spain 26Institut Català d'Oncologia, Barcelona, Spain 27Department of Hygiene, Epidemiology and Medical Statistics, Athens University Medical School, Athens, Greece 28University Pierre and Marie Curie, Paris, France 29University of Alabama at Birmingham, Birmingham, Alabama 30Harvard-MIT Division of Health Sciences and Technology, Boston, Massachusetts.
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Abstract
Decisions about when to start or switch a therapy often depend on the frequency with which individuals are monitored or tested. For example, the optimal time to switch antiretroviral therapy depends on the frequency with which HIV-positive individuals have HIV RNA measured. This paper describes an approach to use observational data for the comparison of joint monitoring and treatment strategies and applies the method to a clinically relevant question in HIV research: when can monitoring frequency be decreased and when should individuals switch from a first-line treatment regimen to a new regimen? We outline the target trial that would compare the dynamic strategies of interest and then describe how to emulate it using data from HIV-positive individuals included in the HIV-CAUSAL Collaboration and the Centers for AIDS Research Network of Integrated Clinical Systems. When, as in our example, few individuals follow the dynamic strategies of interest over long periods of follow-up, we describe how to leverage an additional assumption: no direct effect of monitoring on the outcome of interest. We compare our results with and without the "no direct effect" assumption. We found little differences on survival and AIDS-free survival between strategies where monitoring frequency was decreased at a CD4 threshold of 350 cells/μl compared with 500 cells/μl and where treatment was switched at an HIV-RNA threshold of 1000 copies/ml compared with 200 copies/ml. The "no direct effect" assumption resulted in efficiency improvements for the risk difference estimates ranging from an 7- to 53-fold increase in the effective sample size.
Keywords
Causal inferenceDynamic regime
Joint treatment strategies
Marginal structural model
No direct effect
Publisher
Wiley
Citation
CANIGLIA, Ellen C. et al. Emulating a trial of joint dynamic strategies: an application to monitoring and treatment of HIV-positive individuals. Statistics in Medicine, p. 1-19, 2019.DOI
10.1002/sim.8120ISSN
0277-6715Notes
Antonio Pacheco - Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas.Ellen C. Caniglia1,2 James M. Robins1,3 Lauren E. Cain1 Caroline Sabin4 Roger Logan1 Sophie Abgrall5 Michael J. Mugavero6 Sonia Hernández-Díaz1 Laurence Meyer7 Remonie Seng7 Daniel R. Drozd8 George R. Seage III1 Fabrice Bonnet9 Fabien Le Marec9 Richard D. Moore10 Peter Reiss11 Ard van Sighem11 William C. Mathews12 Inma Jarrín13 Belén Alejos13 Steven G. Deeks14 Roberto Muga15 Stephen L. Boswell16 Elena Ferrer17 Joseph J. Eron18 John Gill19 Antonio Pacheco20 Beatriz Grinsztejn20 Sonia Napravnik18 Sophie Jose4 Andrew Phillips4 Amy Justice21 Janet Tate21 Heiner C. Bucher22 Matthias Egger23 Hansjakob Furrer24 Jose M. Miro25 Jordi Casabona26 Kholoud Porter4 Giota Touloumi27 Heidi Crane8 Dominique Costagliola28 Michael Saag29 Miguel A. Hernán1,3,30 1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 2Department of Population Health, School of Medicine, New York University, New York, New York 3Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 4University College London, London, UK 5APHP Hôpital Avicenne, Bobigny, France 6School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama 7Inserm, Université Paris Sud, Orsay, France 8University of Washington, Seattle, Washington 9Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France 10School of Medicine, The Johns Hopkins University, Baltimore, Maryland 11Academisch Medisch Centrum Geneeskunde, Amsterdam, The Netherlands 12Department of Medicine, University of California San Diego Health, San Diego, California 13National Center of Epidemiology, Instituto de Salud Carlos III, Madrid, Spain 14School of Medicine, University of California, San Francisco, San Francisco, California 15Germans Trias Hospital, Barcelona, Spain 16Fenway Health, Boston, Massachusetts 17Hospital Universitari de Bellvitge, Barcelona, Spain 18Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 19Southern Alberta HIV Program, Calgary, Canada 20Fundação Oswaldo Cruz, Rio de Janeiro, Brazil 21School of Public Health, Yale University, New Haven, Connecticut 22Universitätsspital Basel, Basel, Switzerland 23Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland 24Division of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland 25University of Barcelona, Barcelona, Spain 26Institut Català d'Oncologia, Barcelona, Spain 27Department of Hygiene, Epidemiology and Medical Statistics, Athens University Medical School, Athens, Greece 28University Pierre and Marie Curie, Paris, France 29University of Alabama at Birmingham, Birmingham, Alabama 30Harvard-MIT Division of Health Sciences and Technology, Boston, Massachusetts.
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