Emulating a trial of joint dynamic strategies: An application to monitoring and treatment of HIV‐positive individuals

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 2428

Reporting of Observational Studies Explicitly Aiming to Emulate Randomized Trials

“…We retrieved 3133 unique records, of which 200 were included in the review (Figure 1). All reasons for excluding records after full-text review are given in eAppendix 6 in Supplement 1.…”

“…One-hundred and fifteen studies (58%) completely reported how the target trial protocol was emulated. Eighty-seven studies (44%) provided both the protocol of the target trial and described how it was emulated (Table 2).…”

Aim for clinical utility, not just predictive accuracy

“…Other practical considerations, such as survivor and selection biases, which are inherent in retrospective studies, can be minimized by carefully planning studies with pre-specified protocols that mimic those used in randomized controlled trials [7,20]. This approach has been suggested and applied in comparative effectiveness research [21,8,9] and we advocate for a similar approach.…”

“…In the context of comparing the effectiveness of treatments, [7] has proposed and promoted the concept of emulating a target trial with observational data, and this concept has also been applied to assess the utility of screening [8], and in other clinical settings [9]. In this paper, we similarly propose to use observational data to emulate a target trial to assess the clinical utility of a prediction-based decision rule.…”

Reflection on modern methods: trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data

“…To date, the two papers introducing the concept of trial emulation have been cited over 160 times, but to our knowledge, only two articles reported the use of the cloning approach. 12 , 13 This tutorial provides a step-by-step description of the design, methodology and statistical analysis of emulated trials when immortal-time bias is a concern. This is illustrated using population-based cancer registrations, used to investigate the benefits of surgical treatment for older NSCLC patients.…”