Dynamic models for estimating the effect of HAART on CD4 in observational studies: Application to the Aquitaine Cohort and the Swiss HIV Cohort Study. Biometrics
Prague et al. aimed to estimate the effect of HAART on CD4 count using four dynamic models and compared estimates with those from a naive regression model. In their work, they presented three discrete-time dynamic models based on linear increments models (LIM): the first one based on one difference equation for CD4 counts, the second with an equilibrium point, and the third based on a system of two difference equations, which allowed jointly modeling CD4 counts and viral load. The authors considered continuous-time models based on ordinary differential equations with non-linear mixed effects (ODE-NLME). They compared the different approaches in simulation and in illustration on the ANRS CO3 Aquitaine Cohort and the Swiss HIV Cohort Study.
The authors found that the proposed mechanistic models allowed incorporating biological knowledge when available, which lead to increased statistical evidence for detecting treatment effect. Because inference in ODE-NLME was numerically challenging and required specific methods and softwares, LIM were a valuable intermediary option in terms of consistency, precision, and complexity.