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Mitigating bias in observational vaccine effectiveness studies using simulated comparator populations: Application to rotavirus vaccination in the UK

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Mitigating bias in observational vaccine effectiveness studies using simulated comparator populations : Application to rotavirus vaccination in the UK. / Hungerford, Daniel; Vivancos, Roberto; Read, Jonathan M; Bonnett, Laura J; Bar-Zeev, Naor; Iturriza-Gómara, Miren; Cunliffe, Nigel A; French, Neil.

In: Vaccine, Vol. 36, No. 45, 29.10.2018, p. 6674-6682.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Hungerford, D, Vivancos, R, Read, JM, Bonnett, LJ, Bar-Zeev, N, Iturriza-Gómara, M, Cunliffe, NA & French, N 2018, 'Mitigating bias in observational vaccine effectiveness studies using simulated comparator populations: Application to rotavirus vaccination in the UK', Vaccine, vol. 36, no. 45, pp. 6674-6682. https://doi.org/10.1016/j.vaccine.2018.09.051

APA

Hungerford, D., Vivancos, R., Read, J. M., Bonnett, L. J., Bar-Zeev, N., Iturriza-Gómara, M., Cunliffe, N. A., & French, N. (2018). Mitigating bias in observational vaccine effectiveness studies using simulated comparator populations: Application to rotavirus vaccination in the UK. Vaccine, 36(45), 6674-6682. https://doi.org/10.1016/j.vaccine.2018.09.051

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Hungerford, Daniel ; Vivancos, Roberto ; Read, Jonathan M ; Bonnett, Laura J ; Bar-Zeev, Naor ; Iturriza-Gómara, Miren ; Cunliffe, Nigel A ; French, Neil. / Mitigating bias in observational vaccine effectiveness studies using simulated comparator populations : Application to rotavirus vaccination in the UK. In: Vaccine. 2018 ; Vol. 36, No. 45. pp. 6674-6682.

Bibtex

@article{43ca298ced1b479d957b6312ff428375,
title = "Mitigating bias in observational vaccine effectiveness studies using simulated comparator populations: Application to rotavirus vaccination in the UK",
abstract = "BACKGROUND: Measuring vaccine effectiveness (VE) relies on the use of observational study designs. However, achieving robust estimates of direct and indirect VE is frequently compromised by bias, particularly when using syndromic diagnoses of low-specificity.METHODS: In order to mitigate confounding between the measured outcome and vaccine uptake, we developed a method to balance comparator populations using individual-level propensity scoring derived from the vaccine-exposed population, and applied it to the unexposed comparator population. Indirect VE was estimated by comparing the unvaccinated vaccine-exposed group with a propensity score-simulated unvaccinated, unexposed group. Direct VE was derived by removing indirect VE from the overall VE. We applied this method to an evaluation of the effectiveness of infant rotavirus vaccination in the UK. Using a general practice cohort of 45,259 live births between May 2010 and December 2015, we calculated indirect and direct VE against consultations for acute gastroenteritis using conventional and vaccination-propensity adjustment comparator populations.RESULTS: The overall VE during the rotavirus-season (January-May) calculated using mixed-effects Cox regression was 30% [95% confidence intervals (95% CI: 25,35%)]. Use of conventional comparator populations resulted in implausible VE estimates -14% (95% CI: -41,7%) for direct and 29% (95% CI: 14,42%) for indirect effects. Applying our alternative method, direct VE was 26% (95% CI: 1,45%) and indirect VE was 8% (95% CI: -19,29%).CONCLUSIONS: Estimating VE using propensity score simulated comparator populations, particularly for studies using routine health data with syndromic, low-specificity endpoints will aid accurate measurement of the broader public health impact of a vaccine programme.",
keywords = "Rotavirus vaccines, Gastroenteritis, Vaccine effectiveness, Epidemiologic methods, Bias, Propensity score",
author = "Daniel Hungerford and Roberto Vivancos and Read, {Jonathan M} and Bonnett, {Laura J} and Naor Bar-Zeev and Miren Iturriza-G{\'o}mara and Cunliffe, {Nigel A} and Neil French",
note = "Copyright {\textcopyright} 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.",
year = "2018",
month = oct,
day = "29",
doi = "10.1016/j.vaccine.2018.09.051",
language = "English",
volume = "36",
pages = "6674--6682",
journal = "Vaccine",
issn = "0264-410X",
publisher = "Elsevier BV",
number = "45",

}

RIS

TY - JOUR

T1 - Mitigating bias in observational vaccine effectiveness studies using simulated comparator populations

T2 - Application to rotavirus vaccination in the UK

AU - Hungerford, Daniel

AU - Vivancos, Roberto

AU - Read, Jonathan M

AU - Bonnett, Laura J

AU - Bar-Zeev, Naor

AU - Iturriza-Gómara, Miren

AU - Cunliffe, Nigel A

AU - French, Neil

N1 - Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

PY - 2018/10/29

Y1 - 2018/10/29

N2 - BACKGROUND: Measuring vaccine effectiveness (VE) relies on the use of observational study designs. However, achieving robust estimates of direct and indirect VE is frequently compromised by bias, particularly when using syndromic diagnoses of low-specificity.METHODS: In order to mitigate confounding between the measured outcome and vaccine uptake, we developed a method to balance comparator populations using individual-level propensity scoring derived from the vaccine-exposed population, and applied it to the unexposed comparator population. Indirect VE was estimated by comparing the unvaccinated vaccine-exposed group with a propensity score-simulated unvaccinated, unexposed group. Direct VE was derived by removing indirect VE from the overall VE. We applied this method to an evaluation of the effectiveness of infant rotavirus vaccination in the UK. Using a general practice cohort of 45,259 live births between May 2010 and December 2015, we calculated indirect and direct VE against consultations for acute gastroenteritis using conventional and vaccination-propensity adjustment comparator populations.RESULTS: The overall VE during the rotavirus-season (January-May) calculated using mixed-effects Cox regression was 30% [95% confidence intervals (95% CI: 25,35%)]. Use of conventional comparator populations resulted in implausible VE estimates -14% (95% CI: -41,7%) for direct and 29% (95% CI: 14,42%) for indirect effects. Applying our alternative method, direct VE was 26% (95% CI: 1,45%) and indirect VE was 8% (95% CI: -19,29%).CONCLUSIONS: Estimating VE using propensity score simulated comparator populations, particularly for studies using routine health data with syndromic, low-specificity endpoints will aid accurate measurement of the broader public health impact of a vaccine programme.

AB - BACKGROUND: Measuring vaccine effectiveness (VE) relies on the use of observational study designs. However, achieving robust estimates of direct and indirect VE is frequently compromised by bias, particularly when using syndromic diagnoses of low-specificity.METHODS: In order to mitigate confounding between the measured outcome and vaccine uptake, we developed a method to balance comparator populations using individual-level propensity scoring derived from the vaccine-exposed population, and applied it to the unexposed comparator population. Indirect VE was estimated by comparing the unvaccinated vaccine-exposed group with a propensity score-simulated unvaccinated, unexposed group. Direct VE was derived by removing indirect VE from the overall VE. We applied this method to an evaluation of the effectiveness of infant rotavirus vaccination in the UK. Using a general practice cohort of 45,259 live births between May 2010 and December 2015, we calculated indirect and direct VE against consultations for acute gastroenteritis using conventional and vaccination-propensity adjustment comparator populations.RESULTS: The overall VE during the rotavirus-season (January-May) calculated using mixed-effects Cox regression was 30% [95% confidence intervals (95% CI: 25,35%)]. Use of conventional comparator populations resulted in implausible VE estimates -14% (95% CI: -41,7%) for direct and 29% (95% CI: 14,42%) for indirect effects. Applying our alternative method, direct VE was 26% (95% CI: 1,45%) and indirect VE was 8% (95% CI: -19,29%).CONCLUSIONS: Estimating VE using propensity score simulated comparator populations, particularly for studies using routine health data with syndromic, low-specificity endpoints will aid accurate measurement of the broader public health impact of a vaccine programme.

KW - Rotavirus vaccines

KW - Gastroenteritis

KW - Vaccine effectiveness

KW - Epidemiologic methods

KW - Bias

KW - Propensity score

U2 - 10.1016/j.vaccine.2018.09.051

DO - 10.1016/j.vaccine.2018.09.051

M3 - Journal article

C2 - 30293764

VL - 36

SP - 6674

EP - 6682

JO - Vaccine

JF - Vaccine

SN - 0264-410X

IS - 45

ER -