Assessing trends in vaccine efficacy by pathogen genetic distance

Benkeser, David; Juraska, Michal; Gilbert, Peter B.

Journal de la société française de statistique, Tome 161 (2020) no. 1, pp. 164-175.

Preventive vaccines are an effective public health intervention for reducing the burden of infectious diseases, but have yet to be developed for several major infectious diseases. Vaccine sieve analysis studies whether and how the efficacy of a vaccine varies with the genetics of the infectious pathogen, which may help guide future vaccine development and deployment. A standard statistical approach to sieve analysis compares the effect of the vaccine to prevent infection and disease caused by pathogen types defined dichotomously as genetically near or far from a reference pathogen strain inside the vaccine construct. For example, near may be defined by amino acid identity at all amino acid positions considered in a multiple alignment and far defined by at least one amino acid difference. An alternative approach is to study the efficacy of the vaccine as a function of genetic distance from a pathogen to a reference vaccine strain where the distance cumulates over the set of amino acid positions. We propose a nonparametric method for estimating and testing the trend in the effect of a vaccine across genetic distance. We illustrate the operating characteristics of the estimator via simulation and apply the method to a recent preventive malaria vaccine efficacy trial.

Classification : 62G10, 62N03, 62P10
Mots clés : vaccines, competing risks, causal inference, marginal structural model, Hamming distance

[1] Aitken, Alexander C On least squares and linear combination of observations, Proceedings of the Royal Society of Edinburgh, Volume 55 (1936), pp. 42-48 | DOI | Zbl

[2] Agnandji, ST; Lell, B; Fernandes, JF; Abossolo, BP; Methogo, BG; Kabwende, AL; Adegnika, AA; Mordmüller, B; Issifou, S A phase 3 trial of RTS,S/AS01 malaria vaccine in African infants., New England Journal of Medicine, Volume 367 (2012) no. 24, p. 2284-95 | DOI

[3] Benkeser, David; Carone, Marco; Gilbert, Peter B Improved estimation of the cumulative incidence of rare outcomes, Statistics in Medicine, Volume 37 (2018) no. 2, pp. 280-293 | DOI | MR

[4] Benkeser, David; Hejazi, Nima S survtmle: Targeted Minimum Loss-Based Estimation for Survival Analysis in R (2017) https://CRAN.R-project.org/package=survtmle | DOI

[5] Breiman, Leo Stacked regressions, Machine learning, Volume 24 (1996) no. 1, pp. 49-64 | DOI | Zbl

[6] Follmann, Dean; Proschan, Michael; Leifer, Eric Multiple outputation: Inference for complex clustered data, Biometrics, Volume 59 (2003), pp. 420-429 | DOI | MR | Zbl

[7] Gilbert, Peter B; McKeague, Ian W; Sun, Yanqing The two-sample problem for failure rates depending on a continuous mark: An application to vaccine efficacy, Biostatistics, Volume 9 (2008) no. 2, pp. 263-276 | DOI | Zbl

[8] Gilbert, Peter B; Self, Steven G; Ashby, Mark A Statistical methods for assessing differential vaccine protection against human immunodeficiency virus types, Biometrics, Volume 54 (1998) no. 3, pp. 799-814 | DOI | Zbl

[9] Gilbert, Peter B; Self, Steven G; Rao, Malla; Naficy, Abdollah; Clemens, John Sieve analysis: methods for assessing from vaccine trial data how vaccine efficacy varies with genotypic and phenotypic pathogen variation, Journal of Clinical Epidemiology, Volume 54 (2001) no. 1, pp. 68-85 | DOI

[10] Hampel, Frank R The influence curve and its role in robust estimation, Journal of the American Statistical Association, Volume 69 (1974) no. 346, pp. 383-393 | DOI | MR | Zbl

[11] Hudgens, Michael G; Halloran, M Elizabeth Toward causal inference with interference, Journal of the American Statistical Association, Volume 103 (2008) no. 482, pp. 832-842 | DOI | MR | Zbl

[12] Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J Statistical inference for data adaptive target parameters, The International Journal of Biostatistics, Volume 12 (2016) no. 1, pp. 3-19 | DOI | MR

[13] Juraska, Michal; Gilbert, Peter B Mark-Specific Hazard Ratio Model with Multivariate Continuous Marks: An Application to Vaccine Efficacy, Biometrics, Volume 69 (2013) no. 2, pp. 328-337 | DOI | MR | Zbl

[14] Juraska, Michal; Gilbert, Peter B Mark-specific hazard ratio model with missing multivariate marks, Lifetime Data Analysis, Volume 22 (2016) no. 4, pp. 606-625 | DOI | MR | Zbl

[15] Neafsey, Daniel E; Juraska, Michal; Bedford, Trevor; Benkeser, David; Valim, Clarissa; Griggs, Allison; Lievens, Marc; Abdulla, Salim; Adjei, Samuel; Agbenyega, Tsiri Genetic diversity and protective efficacy of the RTS,S/AS01 malaria vaccine, New England Journal of Medicine, Volume 373 (2015) no. 21, pp. 2025-2037 | DOI

[16] Pearl, Judea Causality: Models, Reasoning, and Inference, Cambridge University Press, New York, NY, 2009 | DOI | MR

[17] Petersen, Maya L; Porter, Kristin E; Gruber, Susan; Wang, Yue; van der Laan, Mark J Diagnosing and responding to violations in the positivity assumption, Statistical Methods in Medical Research, Volume 21 (2010) no. 1, pp. 31-54 | DOI | MR

[18] RTS,S Clinical Trials Partnership First Results of Phase 3 Trial of RTS,S/AS01 Malaria Vaccine in African Children, New England Journal of Medicine, Volume 365 (2011) no. 20, pp. 1863-1875 (PMID: 22007715) | arXiv | DOI

[19] Rolland, Morgane; Edlefsen, Paul T; Larsen, Brendan B; Tovanabutra, Sodsai; Sanders-Buell, Eric; Hertz, Tomer; Carrico, Chris; Menis, Sergey; Magaret, Craig A; Ahmed, Hasan Increased HIV-1 vaccine efficacy against viruses with genetic signatures in Env V2, Nature, Volume 490 (2012) no. 7420, pp. 417-420 | DOI

[20] Sun, Yanqing; Gilbert, Peter B; McKeague, Ian W Proportional hazards models with continuous marks, Annals of Statistics, Volume 37 (2009) no. 1, p. 394 | MR | Zbl

[21] Sun, Yanqing; Li, Mei; Gilbert, Peter B Mark-specific proportional hazards model with multivariate continuous marks and its application to HIV vaccine efficacy trials, Biostatistics, Volume 14 (2012) no. 1, pp. 60-74

[22] Stitelman, Ori M; Wester, C William; De Gruttola, Victor; van der Laan, Mark J Targeted maximum likelihood estimation of effect modification parameters in survival analysis, The International Journal of Biostatistics, Volume 7 (2011) no. 1, pp. 1-34 | DOI | MR

[23] van der Laan, Mark J; Dudoit, Sandrine; Keles, Sunduz Asymptotic optimality of likelihood-based cross-validation, Statistical Applications in Genetics and Molecular Biology, Volume 3 (2004) no. 1, pp. 1-23 | DOI | MR | Zbl

[24] van der Laan, Mark J; Polley, Eric C; Hubbard, Alan E Super learner, Statistical Applications in Genetics and Molecular Biology, Volume 6 (2007) no. 1, pp. 1-23 | DOI | MR | Zbl

[25] van der Laan, Mark; Rubin, Daniel Targeted maximum likelihood learning, The International Journal of Biostatistics, Volume 2 (2006) no. 1, pp. 1-40 | MR

[26] Wolpert, D Stacked generatlization, Neural Networks, Volume 5 (1992) no. 2, pp. 241-259 | DOI