Your browser doesn't support javascript.
loading
Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV-positive individuals.
Caniglia, Ellen C; Robins, James M; Cain, Lauren E; Sabin, Caroline; Logan, Roger; Abgrall, Sophie; Mugavero, Michael J; Hernández-Díaz, Sonia; Meyer, Laurence; Seng, Remonie; Drozd, Daniel R; Seage Iii, George R; Bonnet, Fabrice; Le Marec, Fabien; Moore, Richard D; Reiss, Peter; van Sighem, Ard; Mathews, William C; Jarrín, Inma; Alejos, Belén; Deeks, Steven G; Muga, Roberto; Boswell, Stephen L; Ferrer, Elena; Eron, Joseph J; Gill, John; Pacheco, Antonio; Grinsztejn, Beatriz; Napravnik, Sonia; Jose, Sophie; Phillips, Andrew; Justice, Amy; Tate, Janet; Bucher, Heiner C; Egger, Matthias; Furrer, Hansjakob; Miro, Jose M; Casabona, Jordi; Porter, Kholoud; Touloumi, Giota; Crane, Heidi; Costagliola, Dominique; Saag, Michael; Hernán, Miguel A.
Afiliación
  • Caniglia EC; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Robins JM; Department of Population Health, School of Medicine, New York University, New York, New York.
  • Cain LE; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Sabin C; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Logan R; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Abgrall S; University College London, London, UK.
  • Mugavero MJ; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Hernández-Díaz S; APHP Hôpital Avicenne, Bobigny, France.
  • Meyer L; School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.
  • Seng R; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Drozd DR; Inserm, Université Paris Sud, Orsay, France.
  • Seage Iii GR; Inserm, Université Paris Sud, Orsay, France.
  • Bonnet F; University of Washington, Seattle, Washington.
  • Le Marec F; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Moore RD; Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France.
  • Reiss P; Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France.
  • van Sighem A; School of Medicine, The Johns Hopkins University, Baltimore, Maryland.
  • Mathews WC; Academisch Medisch Centrum Geneeskunde, Amsterdam, The Netherlands.
  • Jarrín I; Academisch Medisch Centrum Geneeskunde, Amsterdam, The Netherlands.
  • Alejos B; Department of Medicine, University of California San Diego Health, San Diego, California.
  • Deeks SG; National Center of Epidemiology, Instituto de Salud Carlos III, Madrid, Spain.
  • Muga R; National Center of Epidemiology, Instituto de Salud Carlos III, Madrid, Spain.
  • Boswell SL; School of Medicine, University of California, San Francisco, San Francisco, California.
  • Ferrer E; Germans Trias Hospital, Barcelona, Spain.
  • Eron JJ; Fenway Health, Boston, Massachusetts.
  • Gill J; Hospital Universitari de Bellvitge, Barcelona, Spain.
  • Pacheco A; Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
  • Grinsztejn B; Southern Alberta HIV Program, Calgary, Canada.
  • Napravnik S; Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
  • Jose S; Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
  • Phillips A; Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
  • Justice A; University College London, London, UK.
  • Tate J; University College London, London, UK.
  • Bucher HC; School of Public Health, Yale University, New Haven, Connecticut.
  • Egger M; School of Public Health, Yale University, New Haven, Connecticut.
  • Furrer H; Universitätsspital Basel, Basel, Switzerland.
  • Miro JM; Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
  • Casabona J; Division of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Porter K; University of Barcelona, Barcelona, Spain.
  • Touloumi G; Institut Català d'Oncologia, Barcelona, Spain.
  • Crane H; University College London, London, UK.
  • Costagliola D; Department of Hygiene, Epidemiology and Medical Statistics, Athens University Medical School, Athens, Greece.
  • Saag M; University of Washington, Seattle, Washington.
  • Hernán MA; University Pierre and Marie Curie, Paris, France.
Stat Med ; 38(13): 2428-2446, 2019 06 15.
Article en En | MEDLINE | ID: mdl-30883859
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.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Infecciones por VIH / Monitoreo de Drogas / Fármacos Anti-VIH Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Stat Med Año: 2019 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Infecciones por VIH / Monitoreo de Drogas / Fármacos Anti-VIH Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Stat Med Año: 2019 Tipo del documento: Article