Optimal CD4 count for initiating HIV treatment: impact of CD4 observation frequency and grace periods, and performance of dynamic marginal structural models.
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/mm to regimens "initiate treatment within a grace period following observed CD4 first <x cells/mm," x = 200, 210, …, 500. Natural history and treatment response were simulated using previous model estimates from CASCADE data. Optimal treatment 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.
From the aMedical Research Council Clinical Trials Unit at University College London, London, United Kingdom; bMRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine, London, United Kingdom; cMwanza Intervention Trials Unit, National Institute for Medical Research, Mwanza, Tanzania; and dLondon School of Hygiene and Tropical Medicine, London, United Kingdom.
Fiona M
FM
Ewings
Deborah
D
Ford
A Sarah
AS
Walker
James
J
Carpenter
Andrew
A
Copas
D019380:Anti-HIV Agents / Q000627:therapeutic use*; D018791:CD4 Lymphocyte Count / Q000379:methods*; D003198:Computer Simulation; D018572:Disease-Free Survival; D004333:Drug Administration Routes; D016903:Drug Monitoring / Q000379:methods*; D015658:HIV Infections / Q000188:drug therapy* / Q000276:immunology*; D006801:Humans; D016015:Logistic Models; D064887:Observational Studies as Topic / Q000379:methods; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000379:methods; D012107:Research Design; D018401:Sample Size; D016896:Treatment Outcome
D019380:Anti-HIV Agents