Associations between baseline characteristics, CD4 cell count response and virological failure on first-line efavirenz + tenofovir + emtricitabine for HIV.
Asboe D, Pozniak A, Cane P, Chadwick D, Churchill D, Clark D, Collins S, Delpech V, Douthwaite S, Dunn D, Fearnhill E, Porter K, Tostevin A, Stirrup O, Fraser C, Geretti AM, Gunson R, Hale A, Hué S, Lazarus L, Leigh-Brown A, Mbisa T, Mackie N, Orkin C, Nastouli E, Pillay D, Phillips A, Sabin C, Smit E, Templeton K, Tilston P, Volz E, Williams I, Zhang H, Fairbrother K, Dawkins J, O'Shea S, Mullen J, Cox A, Tandy R, Fawcett T, Hopkins M, Booth C, Renwick L, Renwick L, Schmid ML, Payne B, Hubb J, Dustan S, Kirk S, Bradley-Stewart A, Babiker A, Hill T, Jose S, Thornton A, Huntington S, Glabay A, Shidfar S, Lynch J, Hand J, de Souza C, Perry N, Tilbury S, Youssef E, Gazzard B, Nelson M, Mabika T, Mandalia S, Anderson J, Munshi S, Post F, Adefisan A, Taylor C, Gleisner Z, Ibrahim F, Campbell L, Baillie K, Gilson R, Brima N, Ainsworth J, Schwenk A, Miller S, Wood C, Johnson M, Youle M, Lampe F, Smith C, Tsintas R, Chaloner C, Hutchinson S, Walsh J, Mackie N, Winston A, Weber J, Ramzan F, Carder M, Leen C, Wilson A, Morris S, Gompels M, Allan S, Palfreeman A, Lewszuk A, Kegg S, Faleye A, Ogunbiyi V, Mitchell S, Hay P, Kemble C, Martin F, Russell-Sharpe S, Gravely J, Allan S, Harte A, Tariq A, Spencer H, Jones R, Pritchard J, Cumming S, Atkinson C, Mital D, Edgell V, Allen J, Ustianowski A, Murphy C, Gunder I, Trevelion R.
- 1
- Institute for Global Health, University College London, London, UK.
- 2
- Mortimer Market Centre, Central and North West London NHS Foundation Trust, London, UK.
- 3
- Lawson Unit, Royal Sussex County Hospital, Brighton, UK.
Abstract
Objectives:
The aim of this study was to investigate associations between baseline characteristics and CD4 cell count response on first-line antiretroviral therapy and risk of virological failure (VF) with or without drug resistance.
Methods:
We conducted an analysis of UK Collaborative HIV Cohort data linked to the UK HIV Drug Resistance Database. Inclusion criteria were viral sequence showing no resistance prior to initiation of first-line efavirenz + tenofovir disoproxil fumarate + emtricitabine and virological suppression within 6 months. Outcomes of VF (≥200 copies/mL) with or without drug resistance were assessed using a competing risks approach fitted jointly with a model for CD4 cell count recovery. Hazard ratios for each VF outcome were estimated for baseline CD4 cell count and viral load and characteristics of CD4 cell count response using latent variables on a standard normal scale.
Results:
A total of 3640 people were included with 338 VF events; corresponding viral sequences were available in 134 with ≥1 resistance mutation in 36. VF with resistance was associated with lower baseline CD4 (0.30, 0.09-0.62), lower CD4 recovery (0.04, 0.00-0.17) and higher CD4 variability (4.40, 1.22-12.68). A different pattern of associations was observed for VF without resistance, but the strength of these results was less consistent across sensitivity analyses. Cumulative incidence of VF with resistance was estimated to be <2% at 3 years for baseline CD4 ≥350 cells/μL.
Conclusion:
Lower baseline CD4 cell count and suboptimal CD4 recovery are associated with VF with drug resistance. People with low CD4 cell count before ART or with suboptimal CD4 recovery on treatment should be a priority for regimens with high genetic barrier to resistance.
© 2019 The Authors. Journal of Virus Eradication published by Mediscript Ltd.
KEYWORDS:
ART; HIV; NNRTI; NRTI; antiretroviral therapy; drug resistance; viral failure; viral suppression
Figure 1.
Plots of hypothetical individual-level data and model fit illustrating latent variables included in the post-treatment CD4 cell count submodel. In each plot, the ‘true’ baseline CD4 cell count (ui) is 225 cells/μL, and the long-term median CD4 cell count following the expected trajectory (solid black line) is 625 cells/μL, but recovery in the observed individual (dotted line) is below average conditional on their baseline (τi is negative with magnitude indicated by the blue arrow). Plots (a) and (b) show people living with HIV with low and high CD4 cell count variability, respectively, with observed CD4 counts shown in red
J Virus Erad. 2019 Nov;5(4):204-211.
Figure 2.
Plot of hazard ratios linking VL and CD4 cell count characteristics to risk of virological failure with and without the appearance of resistance mutations. Results are for people living with HIV on first-line efavirenz + tenofovir disoproxil fumarate + emtricitabine regimen from the fitted model without adjustment for demographic variables. Results are shown as posterior mean with 95% credibility interval. All predictive variables in this plot relate to modelled latent variables transformed to a standard normal scale, with the effect estimate reported for a difference of 1 SD from the mean (on square-root scale for CD4 cell count and log10 scale for VL). VL, viral load
J Virus Erad. 2019 Nov;5(4):204-211.
Figure 3.
Estimated cumulative incidence functions for virological failure with or without resistance (black line) and virological failure with resistance (blue line), derived within a competing risks framework. Ninety-five per cent credibility intervals are shown (dotted lines). Plots are shown for ‘true’ CD4 cell count at baseline set to (a) 100 cells/μL, (b) 200 cells/μL, (c) 350 cells/μL and (d) 500 cells/μL. The estimates presented are averaged over the expected distribution of individual-level CD4 cell count recovery and baseline viral load characteristics, with the distribution for baseline viral load adjusted conditional on the specified CD4 cell count level
J Virus Erad. 2019 Nov;5(4):204-211.
Publication type
Secondary source ID