Observational cohorts are, and will continue to be, indispensable for the evaluation of strategies for the clinical management of people living with HIV. The most clinically relevant strategies are dynamic strategies that incorporate the patients' time-varying clinical history in the clinical decision. Unfortunately, conventional statistical methods cannot appropriately compare dynamic strategies, so methods specifically designed to deal with dynamic strategies and time-varying confounders are needed. We propose to continue to develop analytical methods to enhance the validity of effect estimates from observational HIV cohorts. We also propose to answer key clinical questions about the management of HIV-positive patients by applying innovative analytic methods to complex observational data. These questions include 1) the optimal strategy for viral load monitoring of HIV-positive individuals, 2) the effects of ART simplification on clinical outcomes, and 3) the effects of ART on the incidence of, and mortality from, non-AIDS outcomes. Our primary data source will be the HIV-CAUSAL Collaboration, and we will establish collaborations with complementary HIV consortia in Europe, the U.S., and Africa. We will generate and maintain user-friendly, publicly-available software and detailed documentation to make these methods available to the HIV research community. Our work will implement and extend cutting-edge approaches to emulate randomized trials using observational data, including methods based on the parametric g-formula. One reason for the lack of widespread use of these methods is their perceived technical complexity, which has made them appear inaccessible to many practitioners. After more than two decades of methods and software development, our group is now applying innovative methods to large prospective HIV cohorts, and showing that these methods can be added to the standard arsenal of HIV researchers. This proposal will strengthen the international role of the HIV-CAUSAL Collaboration as an incubator for new methodologies in observational HIV research and beyond.
We will answer key clinical questions about the management of HIV-positive patients by applying innovative analytic methods to complex observational data. We will develop the methods, implement them, show that they work, and make them available to HIV researchers.