Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter July 27, 2019

Ongoing Vaccine and Monoclonal Antibody HIV Prevention Efficacy Trials and Considerations for Sequel Efficacy Trial Designs

Peter B. Gilbert

Abstract

Four randomized placebo-controlled efficacy trials of a candidate vaccine or passively infused monoclonal antibody for prevention of HIV-1 infection are underway (HVTN 702 in South African men and women; HVTN 705 in sub-Saharan African women; HVTN 703/HPTN 081 in sub-Saharan African women; HVTN 704/HPTN 085 in U.S., Peruvian, Brazilian, and Swiss men or transgender persons who have sex with men). Several challenges are posed to the optimal design of the sequel efficacy trials, including: (1) how to account for the evolving mosaic of effective prevention interventions that may be part of the trial design or standard of prevention; (2) how to define viable and optimal sequel trial designs depending on the primary efficacy results and secondary “correlates of protection” results of each of the ongoing trials; and (3) how to define the primary objective of sequel efficacy trials if HIV-1 incidence is expected to be very low in all study arms such that a standard trial design has a steep opportunity cost. After summarizing the ongoing trials, I discuss statistical science considerations for sequel efficacy trial designs, both generally and specifically to each trial listed above. One conclusion is that the results of “correlates of protection” analyses, which ascertain how different host immunological markers and HIV-1 viral features impact HIV-1 risk and prevention efficacy, have an important influence on sequel trial design. This influence is especially relevant for the monoclonal antibody trials because of the focused pre-trial hypothesis that potency and coverage of serum neutralization constitutes a surrogate endpoint for HIV-1 infection. Another conclusion is that while assessing prevention efficacy against a counterfactual placebo group is fraught with risks for bias, such analysis is nonetheless important and study designs coupled with analysis methods should be developed to optimize such inferences. I draw a parallel with non-inferiority designs, which are fraught with risks given the necessity of making unverifiable assumptions for interpreting results, but nevertheless have been accepted when a superiority design is not possible and a rigorous/conservative non-inferiority margin is used. In a similar way, counterfactual placebo group efficacy analysis should use rigorous/conservative inference techniques that formally build in a rigorous/conservative margin to potential biases that could occur due to departures from unverifiable assumptions. Because reliability of this approach would require new techniques for verifying that the study cohort experienced substantial exposure to HIV-1, currently it may be appropriate as a secondary objective but not as a primary objective.

Acknowledgements

I would like to thank the protocol team of the HVTN 702, HVTN 705, HVTN 703/HPTN 081, and HVTN 704/HPTN 085 trials and the many groups and individuals dedicated to planning and conducting these trials, as well as the study participants. I also thank the organizers (Holly Janes, Deborah Donnell, and Martha Nason) and sponsors of the HIV Prevention Efficacy Trial Designs of the Future Symposium (NIH NIAID, Bill and Melinda Gates Foundation, HVTN, HPTN, MTN) as well as Lindsay Carpp for excellent scientific and technical writing assistance. In addition, I thank Glenda Gray, Steven Nijs, Roels Sanne, Carla Truyers, and An Vandebosch for critical review of the manuscript. Lastly, I thank the peer-reviewer Tom Fleming for his insightful comments that improved this work.

  1. Conflict of interest: The author has no potential conflicts of interest to declare.

  2. Funding sources: This work was supported by the National Institute of Allergy and Infectious Disease at the National Institutes of Health [2 R37 AI054165-11 and UM1 AI068635 (Funder Id: http://dx.doi.org/10.13039/100000060)]. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health.

  3. Meetings where this research was presented: P.B.G. presented this research at the HIV Prevention Efficacy Trial Designs of the Future Symposium in November 2018 in Seattle, with talk title “Ongoing Vaccine and Monoclonal Antibody Efficacy Trials in the HVTN and Considerations for Sequel Designs.”

References

AVERT. 2018. “HIV and AIDS in South Africa.” Last Modified 23 October 2018, Accessed November 29, 2018. https://www.avert.org/professionals/hiv-around-world/sub-saharan-africa/south-africa.Search in Google Scholar

Baeten, J. M., D. Donnell, P. Ndase, N. R. Mugo, J. D. Campbell, J. Wangisi, J. W. Tappero, et al. 2012. “Antiretroviral Prophylaxis for HIV Prevention in Heterosexual Men and Women.” The New England Journal of Medicine 367 (5): 399–410. https://doi.org/10.1056/NEJMoa1108524.22784037Search in Google Scholar

Barouch, D. H., K. L. O’Brien, N. L. Simmons, S. L. King, P. Abbink, L. F. Maxfield, Y. H. Sun, et al. 2010. “Mosaic HIV-1 Vaccines Expand the Breadth and Depth of Cellular Immune Responses in Rhesus Monkeys.” Nature Medicine 16 (3): 319–23. https://doi.org/10.1038/nm.2089.20173752Search in Google Scholar

Barouch, D. H., F. L. Tomaka, F. Wegmann, D. J. Stieh, G. Alter, M. L. Robb, N. L. Michael, et al. 2018. “Evaluation of a Mosaic HIV-1 Vaccine in a Multicentre, Randomised, Double-blind, Placebo-controlled, Phase 1/2a Clinical Trial (APPROACH) and in Rhesus Monkeys (NHP 13-19).” Lancet 392 (10143): 232–43. https://doi.org/10.1016/S0140-6736(18)31364-3.Search in Google Scholar

Bekker, L. G., C. Beyrer, and T. C. Quinn. 2012. “Behavioral and Biomedical Combination Strategies for HIV Prevention.” Cold Spring Harbor Perspectives in Medicine 2 (8). https://doi.org/10.1101/cshperspect.a007435.22908192Search in Google Scholar

Bekker, L. G., Z. Moodie, N. Grunenberg, F. Laher, G. D. Tomaras, K. W. Cohen, M. Allen, et al. 2018. “Subtype C ALVAC-HIV and Bivalent Subtype C gp120/MF59 HIV-1 Vaccine in Low-risk, HIV-uninfected, South African Adults: A Phase 1/2 Trial.” Lancet HIV 5 (7): e366–e378. https://doi.org/10.1016/S2352-3018(18)30071-7.Search in Google Scholar

Breslow, N. E., T. Lumley, C. M. Ballantyne, L. E. Chambless, and M. Kulich. 2009. “Using the Whole Cohort in the Analysis of Case-cohort Data.” American Journal of Epidemiology 169 (11): 1398–405. https://doi.org/10.1093/aje/kwp055.19357328Search in Google Scholar

Corey, L., P. B. Gilbert, G. D. Tomaras, B. F. Haynes, G. Pantaleo, and A. S. Fauci. 2015. “Immune Correlates of Vaccine Protection against HIV-1 Acquisition.” Science Translational Medicine 7 (310): 310rv7. https://doi.org/10.1126/scitranslmed.aac7732.26491081Search in Google Scholar

deCamp, A. C., M. Rolland, P. T. Edlefsen, E. Sanders-Buell, B. Hall, C. A. Magaret, A. J. Fiore-Gartland, et al. 2017. “Sieve Analysis of Breakthrough HIV-1 Sequences in HVTN 505 Identifies Vaccine Pressure Targeting the CD4 Binding Site of Env-gp120.” PloS One 12 (11): e0185959. https://doi.org/10.1371/journal.pone.0185959.29149197Search in Google Scholar

Dunn, D., and D. Glidden. in press. “The connection between the averted infections ratio and the rate ratio in active-control trials of pre-exposure prophylaxis agents.” Statistical Communications in Infectious Diseases. (this article is in this same journal issue).Search in Google Scholar

Dunn, D. T., D. V. Glidden, O. T. Stirrup, and S. McCormack. 2018. “The Averted Infections Ratio: A Novel Measure of Effectiveness of Experimental HIV Pre-exposure Prophylaxis Agents.” Lancet HIV 5 (6): e329–e334. https://doi.org/10.1016/S2352-3018(18)30045-6.Search in Google Scholar

Fauci, A. S., G. K. Folkers, and H. D. Marston. 2014. “Ending the Global HIV/AIDS Pandemic: The Critical Role of an HIV Vaccine.” Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America 59 (Suppl 2): S80–4. https://doi.org/10.1093/cid/ciu420.25151483Search in Google Scholar

Fleming, T. R. 2008. “Current Issues in Non-inferiority Trials.” Statistics in Medicine 27 (3): 317–32. https://doi.org/10.1002/sim.2855.17340597Search in Google Scholar

Fleming, T. R., and D. L. DeMets. 1996. “Surrogate End Points in Clinical Trials: Are We Being Misled?” Annals of Internal Medicine 125 (7): 605–13.10.7326/0003-4819-125-7-199610010-000118815760Search in Google Scholar

Fleming, T. R., K. Odem-Davis, M. D. Rothmann, and Y. Li Shen. 2011. “Some Essential Considerations in the Design and Conduct of Non-inferiority Trials.” Clinical Trials (london, England) 8 (4): 432–39. https://doi.org/10.1177/1740774511410994.21835862Search in Google Scholar

Fleming, T. R., and J. H. Powers. 2012. “Biomarkers and Surrogate Endpoints in Clinical Trials.” Statistics in Medicine 31 (25): 2973–84. https://doi.org/10.1002/sim.5403.22711298Search in Google Scholar

Fleming, T. R., and B. A. Richardson. 2004. “Some Design Issues in Trials of Microbicides for the Prevention of HIV Infection.” The Journal of Infectious Diseases 190 (4): 666–74. https://doi.org/10.1086/422603.15272392Search in Google Scholar

Gabriel, E. E., M. C. Sachs, and P. B. Gilbert. 2015. “Comparing and Combining Biomarkers as Principle Surrogates for Time-to-event Clinical Endpoints.” Statistics in Medicine 34 (3): 381–95. https://doi.org/10.1002/sim.6349.Search in Google Scholar

Gilbert, P. B. 2010. “Some Design Issues in Phase 2B Vs Phase 3 Prevention Trials for Testing Efficacy of Products or Concepts.” Statistics in Medicine 29 (10): 1061–71. https://doi.org/10.1002/sim.3676.20419758Search in Google Scholar

Gilbert, P. B., E. E. Gabriel, Y. Huang, and I. S. Chan. 2015. “Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition.” Journal of Causal Inference 3 (2): 157–75. https://doi.org/10.1515/jci-2014-0007.26722639Search in Google Scholar

Gilbert, P. B., and Y. Huang. 2016. “Predicting Overall Vaccine Efficacy in a New Setting by Re-Calibrating Baseline Covariate and Intermediate Response Endpoint Effect Modifiers of Type-Specific Vaccine Efficacy.” Epidemiol Methods 5 (1): 93–112. https://doi.org/10.1515/em-2015-0007.Search in Google Scholar

Gilbert, P. B., and M. G. Hudgens. 2008. “Evaluating Candidate Principal Surrogate Endpoints.” Biometrics 64 (4): 1146–54. https://doi.org/10.1111/j.1541-0420.2008.01014.x.18363776Search in Google Scholar

Gilbert, P. B., M. Juraska, A. C. deCamp, S. Karuna, S. Edupuganti, N. Mgodi, D. J. Donnell, et al. 2017. “Basis and Statistical Design of the Passive HIV-1 Antibody Mediated Prevention (AMP) Test-Of-Concept Efficacy Trials.” Statistical Communications in Infectious Diseases 9: 1. https://doi.org/10.1515/scid-2016-0001.Search in Google Scholar

Gilbert, P. B., and A. R. Luedtke. 2018. “Statistical Learning Methods to Determine Immune Correlates of Herpes Zoster in Vaccine Efficacy Trials.” The Journal of Infectious Diseases 218 (suppl_2): S99–S101. https://doi.org/10.1093/infdis/jiy421.Search in Google Scholar

Grant, R. M., J. R. Lama, P. L. Anderson, V. McMahan, A. Y. Liu, L. Vargas, P. Goicochea, et al. 2010. “Preexposure Chemoprophylaxis for HIV Prevention in Men Who Have Sex with Men.” The New England Journal of Medicine 363 (27): 2587–99. https://doi.org/10.1056/NEJMoa1011205.21091279Search in Google Scholar

Hanscom, B., H. E. Janes, P. D. Guarino, Y. Huang, E. R. Brown, Y. Q. Chen, S. M. Hammer, P. B. Gilbert, and D. J. Donnell. 2016. “Brief Report: Preventing HIV-1 Infection in Women Using Oral Preexposure Prophylaxis: A Meta-analysis of Current Evidence.” Journal of Acquired Immune Deficiency Syndromes 73 (5): 606–08. https://doi.org/10.1097/QAI.0000000000001160.Search in Google Scholar

Haynes, B. F., P. B. Gilbert, M. J. McElrath, S. Zolla-Pazner, G. D. Tomaras, S. M. Alam, D. T. Evans, et al. 2012. “Immune-correlates Analysis of an HIV-1 Vaccine Efficacy Trial.” The New England Journal of Medicine 366 (14): 1275–86. https://doi.org/10.1056/NEJMoa1113425.22475592Search in Google Scholar

Huang, Y., P. B. Gilbert, and H. Janes. 2012. “Assessing Treatment-selection Markers Using a Potential Outcomes Framework.” Biometrics 68 (3): 687–96. https://doi.org/10.1111/j.1541-0420.2011.01722.x.22299708Search in Google Scholar

Huang, Y., A. Pegu, Y. Huang, M. Pauthner, L. Corey, P. Gilbert, D. Burton, and J. Mascola. 2018. “A Meta-analysis to Evaluate the Relationship between Serum Antibody Neutralizing Titer and Protection against SHIV Challenge in Nonhuman Primates.” AIDS Research and Human Retroviruses 34: 39–39.Search in Google Scholar

IOM (Institute of Medicine). 2010. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Edited by John R Ball and Christine M Micheel. Washington, DC: National Academies Press.Search in Google Scholar

Janes, H. E., K. W. Cohen, N. Frahm, S. C. De Rosa, B. Sanchez, J. Hural, C. A. Magaret, et al. 2017. “Higher T-Cell Responses Induced by DNA/rAd5 HIV-1 Preventive Vaccine are Associated with Lower HIV-1 Infection Risk in an Efficacy Trial.” The Journal of Infectious Diseases 215 (9): 1376–85. https://doi.org/10.1093/infdis/jix086.Search in Google Scholar

Julg, B., P. T. Liu, K. Wagh, W. M. Fischer, P. Abbink, N. B. Mercado, J. B. Whitney, et al. 2017. “Protection against a Mixed SHIV Challenge by a Broadly Neutralizing Antibody Cocktail.” Science Translational Medicine 9: 408. https://doi.org/10.1126/scitranslmed.aao4235.Search in Google Scholar

Kobayashi, F., and M. Kuroki. 2014. “A New Proportion Measure of the Treatment Effect Captured by Candidate Surrogate Endpoints.” Statistics in Medicine 33 (19): 3338–53. https://doi.org/10.1002/sim.6180.24782344Search in Google Scholar

Krishnaratne, S., B. Hensen, J. Cordes, J. Enstone, and J. R. Hargreaves. 2016. “Interventions to Strengthen the HIV Prevention Cascade: A Systematic Review of Reviews.” Lancet HIV 3 (7): e307–17. https://doi.org/10.1016/S2352-3018(16)30038-8.27365205Search in Google Scholar

McCormack, S., D. T. Dunn, M. Desai, D. I. Dolling, M. Gafos, R. Gilson, A. K. Sullivan, et al. 2016. “Pre-exposure Prophylaxis to Prevent the Acquisition of HIV-1 Infection (PROUD): Effectiveness Results from the Pilot Phase of a Pragmatic Open-label Randomised Trial.” Lancet 387 (10013): 53–60. https://doi.org/10.1016/S0140-6736(15)00056-2.26364263Search in Google Scholar

Molina, J. M., C. Capitant, B. Spire, G. Pialoux, L. Cotte, I. Charreau, C. Tremblay, et al. 2015. “On-Demand Preexposure Prophylaxis in Men at High Risk for HIV-1 Infection.” The New England Journal of Medicine 373 (23): 2237–46. https://doi.org/10.1056/NEJMoa1506273.26624850Search in Google Scholar

Parast, L., T. Cai, and L. Tian. 2017. “Evaluating Surrogate Marker Information Using Censored Data.” Statistics in Medicine 36 (11): 1767–82. https://doi.org/10.1002/sim.7220.28088843Search in Google Scholar

Plotkin, S. A. 2010. “Correlates of Protection Induced by Vaccination.” Clinical and Vaccine Immunology : CVI 17 (7): 1055–65. https://doi.org/10.1128/CVI.00131-10.20463105Search in Google Scholar

Plotkin, S. A., W. A. Orenstein, P. A. Offit, and K. M. Edwards. 2018. Plotkin’s Vaccines, 7th ed. Philadelphia, PA: Elsevier.Search in Google Scholar

Prentice, R. L. 1989. “Surrogate Endpoints in Clinical Trials: Definition and Operational Criteria.” Statistics in Medicine 8 (4): 431–40.272746710.1002/sim.4780080407Search in Google Scholar

Price, B. L., P. B. Gilbert, and M. J. van der Laan. 2018. “Estimation of the Optimal Surrogate Based on a Randomized Trial.” Biometrics. https://doi.org/10.1111/biom.12879.29701875Search in Google Scholar

Rerks-Ngarm, S., P. Pitisuttithum, S. Nitayaphan, J. Kaewkungwal, J. Chiu, R. Paris, N. Premsri, et al. 2009. “Vaccination with ALVAC and AIDSVAX to Prevent HIV-1 Infection in Thailand.” The New England Journal of Medicine 361 (23): 2209–20. https://doi.org/10.1056/NEJMoa0908492.19843557Search in Google Scholar

Rid, A., A. Saxena, A. H. Baqui, A. Bhan, J. Bines, M. C. Bouesseau, A. Caplan, et al. 2014. “Placebo Use in Vaccine Trials: Recommendations of a WHO Expert Panel.” Vaccine 32 (37): 4708–12. https://doi.org/10.1016/j.vaccine.2014.04.022.Search in Google Scholar

Rida, W., P. Fast, R. Hoff, and T. Fleming. 1997. “Intermediate-size Trials for the Evaluation of HIV Vaccine Candidates: A Workshop Summary.” Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology : Official Publication of the International Retrovirology Association 16 (3): 195–203.939057210.1097/00042560-199711010-00009Search in Google Scholar

Robb, M. L., S. Rerks-Ngarm, S. Nitayaphan, P. Pitisuttithum, J. Kaewkungwal, P. Kunasol, C. Khamboonruang, et al. 2012. “Risk Behaviour and Time as Covariates for Efficacy of the HIV Vaccine Regimen ALVAC-HIV (vcp1521) and AIDSVAX B/E: A Post-hoc Analysis of the Thai Phase 3 Efficacy Trial RV 144.” The Lancet Infectious Diseases 12 (7): 531–37. https://doi.org/10.1016/S1473-3099(12)70088-9.22652344Search in Google Scholar

Schoenfeld, D. A. 1983. “Sample-size Formula for the Proportional-hazards Regression Model.” Biometrics 39 (2): 499–503.635429010.2307/2531021Search in Google Scholar

Stieh, D. J., K. Callewaert, M. Sarnecki, J. Hendriks, S. Nijs, Z. Euler, H. Schuitemaker, G. D. Tomaras, J. G. Kublin, and L. Corey. 2018. “Primary Analysis of TRAVERSE: A Phase 1/2a Study to Assess Safety/Tolerability and Immunogenicity of 2 Different Prime/Boost HIV Vaccine Regimens.” AIDS Research and Human Retroviruses 34: 18.Search in Google Scholar

Tomaras, G. D., and B. F. Haynes. 2014. “Advancing toward HIV-1 Vaccine Efficacy through the Intersections of Immune Correlates.” Vaccines (Basel) 2 (1): 15–35. https://doi.org/10.3390/vaccines2010015.24932411Search in Google Scholar

Tomaras, G. D., and S. A. Plotkin. 2017. “Complex Immune Correlates of Protection in HIV-1 Vaccine Efficacy Trials.” Immunological Reviews 275 (1): 245–61. https://doi.org/10.1111/imr.12514.28133811Search in Google Scholar

Uno, H., B. Claggett, L. Tian, E. Inoue, P. Gallo, T. Miyata, D. Schrag, et al. 2014. “Moving beyond the Hazard Ratio in Quantifying the Between-group Difference in Survival Analysis.” Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology 32 (22): 2380–85. https://doi.org/10.1200/JCO.2014.55.2208.24982461Search in Google Scholar

Uno, H., J. Wittes, H. Fu, S. D. Solomon, B. Claggett, L. Tian, T. Cai, M. A. Pfeffer, S. R. Evans, and L. J. Wei. 2015. “Alternatives to Hazard Ratios for Comparing the Efficacy or Safety of Therapies in Noninferiority Studies.” Annals of Internal Medicine 163 (2): 127–34. https://doi.org/10.7326/M14-1741.26054047Search in Google Scholar

US Food and Drug Administration. 1998. Providing Clinical Evidence of Effectiveness for Human Drug and Biological Products. Technical report.Search in Google Scholar

US Food and Drug Administration. 2012. “Food and Drug Administration Safety and Innovation Act (FDASIA).” https://www.gpo.gov/fdsys/pkg/PLAW-112publ144/pdf/PLAW-112publ144.pdf.Search in Google Scholar

VanderWeele, T. 2015. Explanation in Causal Inference: Methods for Mediation and Interaction. New York, NY: Oxford University Press.Search in Google Scholar

Vansteelandt, S., E. Goetghebeur, M. G. Kenward, and G. Molenberghs. 2006. “Ignorance and Uncertainty Regions as Inferential Tools in a Sensitivity Analysis.” Statistica Sinica 16 (3): 953–79.Search in Google Scholar

Wagh, K., M. S. Seaman, M. Zingg, T. Fitzsimons, D. H. Barouch, D. R. Burton, M. Connors, et al. 2018. “Potential of Conventional & Bispecific Broadly Neutralizing Antibodies for Prevention of HIV-1 Subtype A, C & D Infections.” PLoS Pathogens 14 (3): e1006860.Search in Google Scholar

Wagh, K., T. Bhattacharya, C. Williamson, A. Robles, M. Bayne , J. Garrity, M. Rist, et al. 2016. “Optimal Combinations of Broadly Neutralizing Antibodies for Prevention and Treatment of HIV-1 Clade C Infection.” PLoS Pathogens 12 (3): e1005520.Search in Google Scholar

World Health Organization. 2013. “Expert Consultation on the Use of Placebos in Vaccine Trials.” Accessed July 15, 2015. http://apps.who.int/iris/bitstream/10665/94056/1/9789241506250_eng.pdf?ua=1.Search in Google Scholar

World Health Organization. 2015. “WHO Expands Recommendation on Oral Pre-Exposure Prophylaxis of HIV Infection (prep).” http://apps.who.int/iris/bitstream/handle/10665/197906/WHO_HIV_2015.48_eng.pdf;jsessionid=8A9596B4EBCCB53C0F5A8F676B41F1BB?sequence=1.Search in Google Scholar

Wu, X., Z. Y. Yang, Y. Li, C. M. Hogerkorp, W. R. Schief, M. S. Seaman, T. Zhou, et al. 2010. “Rational Design of Envelope Identifies Broadly Neutralizing Human Monoclonal Antibodies to HIV-1.” Science 329 (5993): 856–61. https://doi.org/10.1126/science.1187659.20616233Search in Google Scholar

Xu, L., A. Pegu, E. Rao, N. Doria-Rose, J. Beninga, K. McKee, D. M. Lord, et al. 2017. “Trispecific Broadly Neutralizing HIV Antibodies Mediate Potent SHIV Protection in Macaques.” Science 358 (6359): 85–90. https://doi.org/10.1126/science.aan8630.28931639Search in Google Scholar

Supplementary Material

The online version of this article offers supplementary material (DOI:https://doi.org/10.1515/scid-2019-0003).

Received: 2019-02-05
Revised: 2019-04-30
Accepted: 2019-05-31
Published Online: 2019-07-27

© 2019 Walter de Gruyter GmbH, Berlin/Boston