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; ... (2019). Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV-positive individuals. Statistics in medicine, 38(13), pp. 2428-2446. Wiley-Blackwell 10.1002/sim.8120

[img] Text
Caniglia_EmulatingATrialMonitoringTreatmentHIV_StatisticsMedicine2019 (002).pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (992kB) | Request a copy

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.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Infectiology
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine

UniBE Contributor:

Egger, Matthias and Furrer, Hansjakob

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

0277-6715

Publisher:

Wiley-Blackwell

Language:

English

Submitter:

Annelies Luginbühl

Date Deposited:

27 Mar 2019 11:32

Last Modified:

04 May 2019 01:32

Publisher DOI:

10.1002/sim.8120

PubMed ID:

30883859

Uncontrolled Keywords:

causal inference dynamic regime joint treatment strategies marginal structural model no direct effect

BORIS DOI:

10.7892/boris.128458

URI:

https://boris.unibe.ch/id/eprint/128458

Actions (login required)

Edit item Edit item
Provide Feedback