Optimal CD4 count for treatment initiation in HIV-infection: impact of CD4 observation frequency and grace periods, and performance of dynamic marginal structural models, in realistic scenarios

Background: In HIV infection, dynamic marginal structural models have estimated the optimal CD4 for treatment initiation to minimize AIDS/death. The impact of CD4 observation frequency and grace periods (permitted delay to initiation) on the optimal regimen has not been investigated nor has the performance of dynamic marginal structural models in moderately sized data sets—two issues that are relevant to many applications. Methods: To determine optimal regimens, we simulated 31,000,000 HIV-infected persons randomized at CD4 500–550 cells/mm3 to regimens “initiate treatment within a grace period following observed CD4 first regimens for the observation frequencies and grace periods were defined by highest 10-year AIDS-free survival. To evaluate the performance of dynamic marginal structural models, we simulated 1000 observational studies (n = 3,000) with CD4-dependent treatment initiation. Results: Decreasing the frequency of CD4 measurements from monthly to every 3, 6, and 12 months increased the optimal regimen from a CD4 level of 350 (10-year AIDS-free survival, 0.8657) to 410 (0.8650), 460 (0.8634), and 490 (0.8564), respectively. Under a regimen defined by x = 350 with annual CD4s, 10-year AIDS-free survival dropped to 0.8304. Extending the grace period from 1 to 3 or 6 months, with 3-monthly CD4s, maintained the optimal regimen at 410 for 3 months and increased it to 460 for 6 months. In observational studies with 3-monthly CD4s, the mean (SE) estimated optimal regimen was 402 (76), 424 (66), and 430 (63) with 1-, 3-, and 6-month grace periods; 24%, 15%, and 14% of estimated optimal regimens resulted in >0.5% lower AIDS-free survival compared with the true optimal regimen. Conclusions: The optimal regimen is strongly influenced by CD4 frequency and less by grace period length. Dynamic marginal structural models lack precision at moderate sample sizes.