Yunda Huang1, Lily Zhang2, Holly Janes3, Nicole Frahm4, Abby Isaacs5, Jerome H Kim6, David Montefiori7, M Julie McElrath8, Georgia D Tomaras9, Peter B Gilbert10. 1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Department of Global Health, University of Washington, 1510 San Juan Rd., Seattle, WA 98195, USA. Electronic address: yunda@scharp.org. 2. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA. Electronic address: yzhang2@scharp.org. 3. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Department of Biostatistics, University of Washington, 1705 NE Pacific St., Seattle, WA 98195, USA. Electronic address: hjanes@fredhutch.org. 4. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Department of Global Health, University of Washington, 1510 San Juan Rd., Seattle, WA 98195, USA. Electronic address: nfrahm@fredhutch.org. 5. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA. Electronic address: aisaacs@scharp.org. 6. U.S. Military HIV Research Program, Walter Reed Army Institute of Research, 503 Robert Grant Ave., Silver Spring, MD 20910, USA; International Vaccine Institute, 1 Gwanak-ro, Gwanak-gu, Seoul, South Korea. Electronic address: Jerome.Kim@ivi.int. 7. Duke Human Vaccine Institute, Genome Court, MSRB II, Durham, NC 27710, USA. Electronic address: david.montefiori@duke.edu. 8. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Department of Global Health, University of Washington, 1510 San Juan Rd., Seattle, WA 98195, USA; Department of Laboratory Medicine, University of Washington, 1959 NE Pacific St., Seattle, WA 98195, USA; Department of Medicine, University of Washington, 1959 NE Pacific St., Seattle, WA 98195, USA. Electronic address: jmcelrat@fredhutch.org. 9. Duke Human Vaccine Institute, Genome Court, MSRB II, Durham, NC 27710, USA. Electronic address: gdt@duke.edu. 10. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Seattle, WA 98109, USA; Department of Biostatistics, University of Washington, 1705 NE Pacific St., Seattle, WA 98195, USA. Electronic address: pgilbert@scharp.org.
Abstract
BACKGROUND: The evaluation of durable immune responses is important in HIV vaccine research and development. The efficiency of such evaluation could be increased by incorporating predictors of the responses in the statistical analysis. In this paper, we investigated whether and how baseline demographic variables and immune responses measured two weeks after vaccination predicted durable immune responses measured six months later. METHODS: We included data from seven preventive HIV vaccine regimens evaluated in three clinical trials: a Phase 1 study of four DNA, NYVAC and/or AIDSVAX vaccine regimens (HVTN096), a Phase 2 study of two DNA and/or MVA vaccine regimens (HVTN205), and a Phase 3 study of a single ALVAC/AIDSVAX regimen (RV144). Regularized random forests and linear regression models were used to identify and evaluate predictors of the positivity and magnitude of durable immune responses. RESULTS: We analyzed 201 vaccine recipients with data from 10 to 127 immune response biomarkers, and 3-5 demographic variables. The best prediction of participants' durable response positivity based on two-week responses rendered up to close-to-perfect accuracy; the best prediction of participants' durable response magnitude rendered correlation coefficients between the observed and predicted responses ranging up to 0.91. Though prediction performances differed among biomarkers, durable immune responses were best predicted by the two-week response level of the same biomarker. Adding demographic information and two-week response levels of different biomarkers provided little or no improvement in the predictions. CONCLUSIONS: For some biomarkers and for the vaccines we studied, two-week post-vaccination responses can well predict durable responses six months later. Therefore, if immune response durability is only assessed in a sub-sample of vaccine recipients, statistical analyses of durable responses will have increased efficiency by incorporating two-week response data. Further research is needed to generalize the findings to other vaccine regimens and biomarkers. Clinicaltrials.gov identifiers: NCT01799954, NCT00820846, NCT00223080.
RCT Entities:
BACKGROUND: The evaluation of durable immune responses is important in HIV vaccine research and development. The efficiency of such evaluation could be increased by incorporating predictors of the responses in the statistical analysis. In this paper, we investigated whether and how baseline demographic variables and immune responses measured two weeks after vaccination predicted durable immune responses measured six months later. METHODS: We included data from seven preventive HIV vaccine regimens evaluated in three clinical trials: a Phase 1 study of four DNA, NYVAC and/or AIDSVAX vaccine regimens (HVTN096), a Phase 2 study of two DNA and/or MVA vaccine regimens (HVTN205), and a Phase 3 study of a single ALVAC/AIDSVAX regimen (RV144). Regularized random forests and linear regression models were used to identify and evaluate predictors of the positivity and magnitude of durable immune responses. RESULTS: We analyzed 201 vaccine recipients with data from 10 to 127 immune response biomarkers, and 3-5 demographic variables. The best prediction of participants' durable response positivity based on two-week responses rendered up to close-to-perfect accuracy; the best prediction of participants' durable response magnitude rendered correlation coefficients between the observed and predicted responses ranging up to 0.91. Though prediction performances differed among biomarkers, durable immune responses were best predicted by the two-week response level of the same biomarker. Adding demographic information and two-week response levels of different biomarkers provided little or no improvement in the predictions. CONCLUSIONS: For some biomarkers and for the vaccines we studied, two-week post-vaccination responses can well predict durable responses six months later. Therefore, if immune response durability is only assessed in a sub-sample of vaccine recipients, statistical analyses of durable responses will have increased efficiency by incorporating two-week response data. Further research is needed to generalize the findings to other vaccine regimens and biomarkers. Clinicaltrials.gov identifiers: NCT01799954, NCT00820846, NCT00223080.
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