2
|
Gilbert PB, Fong Y, Hejazi NS, Kenny A, Huang Y, Carone M, Benkeser D, Follmann D. Four statistical frameworks for assessing an immune correlate of protection (surrogate endpoint) from a randomized, controlled, vaccine efficacy trial. Vaccine 2024; 42:2181-2190. [PMID: 38458870 PMCID: PMC10999339 DOI: 10.1016/j.vaccine.2024.02.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/22/2024] [Accepted: 02/23/2024] [Indexed: 03/10/2024]
Abstract
A central goal of vaccine research is to characterize and validate immune correlates of protection (CoPs). In addition to helping elucidate immunological mechanisms, a CoP can serve as a valid surrogate endpoint for an infectious disease clinical outcome and thus qualifies as a primary endpoint for vaccine authorization or approval without requiring resource-intensive randomized, controlled phase 3 trials. Yet, it is challenging to persuasively validate a CoP, because a prognostic immune marker can fail as a reliable basis for predicting/inferring the level of vaccine efficacy against a clinical outcome, and because the statistical analysis of phase 3 trials only has limited capacity to disentangle association from cause. Moreover, the multitude of statistical methods garnered for CoP evaluation in phase 3 trials renders the comparison, interpretation, and synthesis of CoP results challenging. Toward promoting broader harmonization and standardization of CoP evaluation, this article summarizes four complementary statistical frameworks for evaluating CoPs in a phase 3 trial, focusing on the frameworks' distinct scientific objectives as measured and communicated by distinct causal vaccine efficacy parameters. Advantages and disadvantages of the frameworks are considered, dependent on phase 3 trial context, and perspectives are offered on how the frameworks can be applied and their results synthesized.
Collapse
Affiliation(s)
- Peter B Gilbert
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA.
| | - Youyi Fong
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Nima S Hejazi
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Avi Kenny
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Ying Huang
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Marco Carone
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - David Benkeser
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Dean Follmann
- Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA
| |
Collapse
|
3
|
Huang Y, Hejazi NS, Blette B, Carpp LN, Benkeser D, Montefiori DC, McDermott AB, Fong Y, Janes HE, Deng W, Zhou H, Houchens CR, Martins K, Jayashankar L, Flach B, Lin BC, O’Connell S, McDanal C, Eaton A, Sarzotti-Kelsoe M, Lu Y, Yu C, Kenny A, Carone M, Huynh C, Miller J, El Sahly HM, Baden LR, Jackson LA, Campbell TB, Clark J, Andrasik MP, Kublin JG, Corey L, Neuzil KM, Pajon R, Follmann D, Donis RO, Koup RA, Gilbert PB. Stochastic Interventional Vaccine Efficacy and Principal Surrogate Analyses of Antibody Markers as Correlates of Protection against Symptomatic COVID-19 in the COVE mRNA-1273 Trial. Viruses 2023; 15:2029. [PMID: 37896806 PMCID: PMC10612023 DOI: 10.3390/v15102029] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 09/25/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023] Open
Abstract
The COVE trial randomized participants to receive two doses of mRNA-1273 vaccine or placebo on Days 1 and 29 (D1, D29). Anti-SARS-CoV-2 Spike IgG binding antibodies (bAbs), anti-receptor binding domain IgG bAbs, 50% inhibitory dilution neutralizing antibody (nAb) titers, and 80% inhibitory dilution nAb titers were measured at D29 and D57. We assessed these markers as correlates of protection (CoPs) against COVID-19 using stochastic interventional vaccine efficacy (SVE) analysis and principal surrogate (PS) analysis, frameworks not used in our previous COVE immune correlates analyses. By SVE analysis, hypothetical shifts of the D57 Spike IgG distribution from a geometric mean concentration (GMC) of 2737 binding antibody units (BAU)/mL (estimated vaccine efficacy (VE): 92.9% (95% CI: 91.7%, 93.9%)) to 274 BAU/mL or to 27,368 BAU/mL resulted in an overall estimated VE of 84.2% (79.0%, 88.1%) and 97.6% (97.4%, 97.7%), respectively. By binary marker PS analysis of Low and High subgroups (cut-point: 2094 BAU/mL), the ignorance interval (IGI) and estimated uncertainty interval (EUI) for VE were [85%, 90%] and (78%, 93%) for Low compared to [95%, 96%] and (92%, 97%) for High. By continuous marker PS analysis, the IGI and 95% EUI for VE at the 2.5th percentile (519.4 BAU/mL) vs. at the 97.5th percentile (9262.9 BAU/mL) of D57 Spike IgG concentration were [92.6%, 93.4%] and (89.2%, 95.7%) vs. [94.3%, 94.6%] and (89.7%, 97.0%). Results were similar for other D29 and D57 markers. Thus, the SVE and PS analyses additionally support all four markers at both time points as CoPs.
Collapse
Affiliation(s)
- Ying Huang
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; (A.K.); (M.C.)
| | - Nima S. Hejazi
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Bryan Blette
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Lindsay N. Carpp
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
| | - David Benkeser
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA;
| | - David C. Montefiori
- Department of Surgery, Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC 27710, USA; (D.C.M.); (C.M.); (A.E.); (M.S.-K.)
| | - Adrian B. McDermott
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA (B.F.); (B.C.L.); (R.A.K.)
| | - Youyi Fong
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Holly E. Janes
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Weiping Deng
- Moderna, Inc., Cambridge, MA 02139, USA; (W.D.); (H.Z.); (J.M.); (R.P.)
| | - Honghong Zhou
- Moderna, Inc., Cambridge, MA 02139, USA; (W.D.); (H.Z.); (J.M.); (R.P.)
| | - Christopher R. Houchens
- Biomedical Advanced Research and Development Authority, Washington, DC 20201, USA; (C.R.H.); (L.J.); (C.H.); (R.O.D.)
| | - Karen Martins
- Biomedical Advanced Research and Development Authority, Washington, DC 20201, USA; (C.R.H.); (L.J.); (C.H.); (R.O.D.)
| | - Lakshmi Jayashankar
- Biomedical Advanced Research and Development Authority, Washington, DC 20201, USA; (C.R.H.); (L.J.); (C.H.); (R.O.D.)
| | - Britta Flach
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA (B.F.); (B.C.L.); (R.A.K.)
| | - Bob C. Lin
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA (B.F.); (B.C.L.); (R.A.K.)
| | - Sarah O’Connell
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA (B.F.); (B.C.L.); (R.A.K.)
| | - Charlene McDanal
- Department of Surgery, Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC 27710, USA; (D.C.M.); (C.M.); (A.E.); (M.S.-K.)
| | - Amanda Eaton
- Department of Surgery, Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC 27710, USA; (D.C.M.); (C.M.); (A.E.); (M.S.-K.)
| | - Marcella Sarzotti-Kelsoe
- Department of Surgery, Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC 27710, USA; (D.C.M.); (C.M.); (A.E.); (M.S.-K.)
| | - Yiwen Lu
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
| | - Chenchen Yu
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
| | - Avi Kenny
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; (A.K.); (M.C.)
| | - Marco Carone
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; (A.K.); (M.C.)
| | - Chuong Huynh
- Biomedical Advanced Research and Development Authority, Washington, DC 20201, USA; (C.R.H.); (L.J.); (C.H.); (R.O.D.)
| | - Jacqueline Miller
- Moderna, Inc., Cambridge, MA 02139, USA; (W.D.); (H.Z.); (J.M.); (R.P.)
| | - Hana M. El Sahly
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA;
| | | | - Lisa A. Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA 98101, USA;
| | - Thomas B. Campbell
- Division of Infectious Diseases, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - Jesse Clark
- Department of Medicine, Division of Infectious Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA;
| | - Michele P. Andrasik
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
| | - James G. Kublin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
| | - Lawrence Corey
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Kathleen M. Neuzil
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA;
| | - Rolando Pajon
- Moderna, Inc., Cambridge, MA 02139, USA; (W.D.); (H.Z.); (J.M.); (R.P.)
| | - Dean Follmann
- Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA;
| | - Ruben O. Donis
- Biomedical Advanced Research and Development Authority, Washington, DC 20201, USA; (C.R.H.); (L.J.); (C.H.); (R.O.D.)
| | - Richard A. Koup
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA (B.F.); (B.C.L.); (R.A.K.)
| | - Peter B. Gilbert
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; (Y.H.); (N.S.H.); (L.N.C.); (Y.F.); (H.E.J.); (Y.L.); (C.Y.); (M.P.A.); (J.G.K.); (L.C.)
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; (A.K.); (M.C.)
| | | | | | | | | |
Collapse
|
4
|
De Vos E, Westreich D, Scott L, Voss de Lima Y, Stevens W, Hayes C, da Silva P, Van Rie A. Estimating the effect of a rifampicin resistant tuberculosis diagnosis by the Xpert MTB/RIF assay on two-year mortality. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001989. [PMID: 37656670 PMCID: PMC10473529 DOI: 10.1371/journal.pgph.0001989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 07/07/2023] [Indexed: 09/03/2023]
Abstract
Studies assessing patient-centred outcomes of novel rifampicin resistant tuberculosis (RR-TB) diagnostics are rare and mostly apply conventional methods which may not adequately address biases. Even though the Xpert MTB/RIF molecular assay was endorsed a decade ago for simultaneous diagnosis of tuberculosis and RR-TB, the impact of the assay on mortality among people with RR-TB has not yet been assessed. We analysed data of an observational prospective cohort study (EXIT-RIF) performed in South Africa. We applied a causal inference approach using inverse odds of sampling weights to rectify survivor bias and selection bias caused by differing screening guidelines. We also adjusted for confounding using a marginal structural model with inverse probability of treatment weights. We estimated the total effect of an RR-TB diagnosis made by the Xpert assay versus the pre-Xpert diagnostic algorithm (entailing a targeted Line Probe Assay (LPA) among TB-confirmed patients) on two-year mortality and we assessed mediation by RR-treatment initiation. Of the 749 patients diagnosed with RR-TB [247 (33%) by the pre-Xpert diagnostic algorithm and 502 (67%) by the Xpert assay], 42.7% died. Of these, 364 (48.6%) patients died in the pre-Xpert group and 200 (39.8%) in the Xpert group. People diagnosed with RR-TB by the Xpert assay had a higher odds of RR-TB treatment initiation compared to those diagnosed by the targeted LPA-based diagnostic process (OR 2.79; 95%CI 2.19-3.56). Receiving an RR-TB diagnosis by Xpert resulted in a 28% reduction in the odds of mortality within 2 years after presentation to the clinic (ORCI 0.72; 95%CI 0.53-0.99). Causal mediation analysis suggests that the higher rate of RR-TB treatment initiation in people diagnosed by the Xpert assay explains the effect of Xpert on 2-year mortality [natural indirect effect odds ratio 0.90 (95%CI 0.85-0.96). By using causal inference methods in combination with high quality observational data, we could demonstrate that the introduction of the Xpert assay caused a 28% reduction in 2-year odds of mortality of RR-TB. This finding highlights the need for advocacy for a worldwide roll-out of rapid molecular tests. Because the effect is mainly caused by increased RR-TB treatment initiation, health care systems should also ensure timely initiation of effective treatment upon an RR-TB diagnosis.
Collapse
Affiliation(s)
| | - Daniel Westreich
- University of North Carolina, Chapel Hill, NC, United States of America
| | - Lesley Scott
- University of the Witwatersrand, Johannesburg, South Africa
| | | | - Wendy Stevens
- University of the Witwatersrand, Johannesburg, South Africa
- National Health Laboratory Service, Johannesburg, South Africa
| | - Cindy Hayes
- National Health Laboratory Services, Port Elizabeth, South Africa
| | - Pedro da Silva
- National Health Laboratory Service, Johannesburg, South Africa
| | | |
Collapse
|