Using observational data to emulate a randomized trial of dynamic treatment-switching strategies: an application to antiretroviral therapy

Author:

Cain Lauren E1,Saag Michael S2,Petersen Maya3,May Margaret T4,Ingle Suzanne M4,Logan Roger1,Robins James M15,Abgrall Sophie67,Shepherd Bryan E8,Deeks Steven G9,John Gill M10,Touloumi Giota11,Vourli Georgia11,Dabis François12,Vandenhende Marie-Anne12,Reiss Peter1314,van Sighem Ard13,Samji Hasina15,Hogg Robert S1516,Rybniker Jan17,Sabin Caroline A18,Jose Sophie18,del Amo Julia1920,Moreno Santiago2122,Rodríguez Benigno23,Cozzi-Lepri Alessandro24,Boswell Stephen L25,Stephan Christoph26,Pérez-Hoyos Santiago27,Jarrin Inma1920,Guest Jodie L282930,D’Arminio Monforte Antonella31,Antinori Andrea32,Moore Richard33,Campbell Colin NJ2034,Casabona Jordi203435,Meyer Laurence36,Seng Rémonie36,Phillips Andrew N18,Bucher Heiner C37,Egger Matthias3839,Mugavero Michael J40,Haubrich Richard41,Geng Elvin H42,Olson Ashley43,Eron Joseph J44,Napravnik Sonia44,Kitahata Mari M45,Van Rompaey Stephen E45,Teira Ramón46,Justice Amy C4748,Tate Janet P4748,Costagliola Dominique6,Sterne Jonathan AC4,Hernán Miguel A1549,

Affiliation:

1. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

2. Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

3. Divisions of Biostatistics and Epidemiology, University of California, Berkeley, School of Public Health, Berkeley, CA, USA

4. School of Social and Community Medicine, University of Bristol, Bristol, UK

5. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

6. Sorbonne Universités, UPMC Univ Paris 06, INSERM, Institut Pierre Louis d’épidémiologie et de Santé Publique (IPLESP UMRS 1136), F75013, Paris, France

7. Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Antoine Béclère, Service de Médecine Interne, Clamart, France

8. Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA

9. Positive Health Program, San Francisco General Hospital, San Francisco, CA, USA

10. Division of Infectious Diseases, University of Calgary, Calgary, AB, Canada

11. Department of Hygiene, Epidemiology and Medical Statistics, Athens University Medical School, Athens, Greece

12. INSERM U897, Centre Inserm Epidémiologie et Biostatistique, Université de Bordeaux, and Bordeaux University Hospital, Department of Internal Medicine, Bordeaux, France

13. Stichting HIV Monitoring, Amsterdam, Netherlands

14. Academic Medical Center, Department of Global Health and Division of Infectious Diseases, University of Amsterdam, and Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands

15. Epidemiology and Population Health Program, BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada

16. Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada

17. 1st Department of Internal Medicine, University of Cologne, D-50937 Cologne, Germany

18. University College London, London, UK

19. National Centre of Epidemiology, Instituto de Salud Carlos III, Madrid, Spain

20. Consorcio de Investigación Biomédica de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain

21. Ramón y Cajal Hospital, IRYCIS, Madrid, Spain

22. University of Alcalá de Henares, Madrid, Spain

23. Division of Infectious Disease, Case Western Reserve University, Cleveland, OH, USA

24. Department of Infection and Population Health; Division of Population Health, University College London, London, UK

25. Fenway Health, Boston, MA, USA

26. HIV Center, Department of Infectious Diseases, University Hospital, Frankfurt, Germany

27. Vall d'Hebron Research Institute, Barcelona, Spain

28. Rollins School of Public Health at Emory University, Atlanta, GA, USA

29. Emory University School of Medicine, Atlanta, GA, USA

30. Atlanta Veterans Affairs Medical Center, Decatur, GA, USA

31. Clinic of Infectious Diseases and Tropical Medicine, Department of Health Sciences, San Paolo Hospital, University of Milan, Milan, Italy

32. Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani IRCCS, Rome, Italy

33. School of Medicine, Johns Hopkins University, Baltimore, MD, USA

34. Center for Epidemiological Studies on HIV/AIDS and STI of Catalonia (CEEISCAT), Agència Salut Pública de Catalunya (ASPC), Generalitat de Catalunya, Badalona, 08916 Catalonia, Spain

35. Department of Paediatrics, Obstetrics, Gynaecology and Preventive Medicine, Universitat Autònoma de Barcelona, Bellaterra, 08193 Catalonia, Spain

36. Université Paris Sud, INSERM CESP U1018, and AP-HP, Hôpital de Bicêtre, Service de Santé Publique, le Kremlin Bicêtre, France

37. Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, Basel, Switzerland

38. Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa

39. University of Bern, Institute for Social and Preventive Medicine, Bern, Switzerland

40. University of Alabama at Birmingham, Birmingham, AL, USA

41. University of California San Diego, CA, USA (Currently Gilead Sciences, Foster City, CA, USA)

42. Division of HIV/AIDS, Department of Medicine, University of California, San Francisco, CA, USA

43. Medical Research Council Clinical Trials Unit, University College London, London, UK

44. Division of Infectious Diseases, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

45. Department of Medicine, University of Washington, Seattle, WA, USA

46. Unit of Infectious Diseases, Hospital Sierrallana, Torrelavega, Spain

47. Yale School of Medicine, New Haven, CT, USA

48. VA Connecticut Healthcare System, West Haven, CT, USA

49. Harvard-MIT Division of Health Sciences and Technology, Boston, MA, USA

Abstract

Abstract Background: When a clinical treatment fails or shows suboptimal results, the question of when to switch to another treatment arises. Treatment switching strategies are often dynamic because the time of switching depends on the evolution of an individual’s time-varying covariates. Dynamic strategies can be directly compared in randomized trials. For example, HIV-infected individuals receiving antiretroviral therapy could be randomized to switching therapy within 90 days of HIV-1 RNA crossing above a threshold of either 400 copies/ml (tight-control strategy) or 1000 copies/ml (loose-control strategy). Methods: We review an approach to emulate a randomized trial of dynamic switching strategies using observational data from the Antiretroviral Therapy Cohort Collaboration, the Centers for AIDS Research Network of Integrated Clinical Systems and the HIV-CAUSAL Collaboration. We estimated the comparative effect of tight-control vs. loose-control strategies on death and AIDS or death via inverse-probability weighting. Results: Of 43 803 individuals who initiated an eligible antiretroviral therapy regimen in 2002 or later, 2001 met the baseline inclusion criteria for the mortality analysis and 1641 for the AIDS or death analysis. There were 21 deaths and 33 AIDS or death events in the tight-control group, and 28 deaths and 41 AIDS or death events in the loose-control group. Compared with tight control, the adjusted hazard ratios (95% confidence interval) for loose control were 1.10 (0.73, 1.66) for death, and 1.04 (0.86, 1.27) for AIDS or death. Conclusions: Although our effective sample sizes were small and our estimates imprecise, the described methodological approach can serve as an example for future analyses.

Funder

National Institutes of Health

National Institute of Allergy and Infectious Diseases

UK Medical Research Council

Department for International Development

National Heart, Lung and Blood Institute

National Institute for Health Research Senior Investigator

The UK CHIC

Medical Research Council (MRC) UK

Publisher

Oxford University Press (OUP)

Subject

General Medicine,Epidemiology

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