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Challenges in Estimating the Effectiveness of COVID-19 Vaccination Using Observational Data.
Hulme, William J; Williamson, Elizabeth; Horne, Elsie M F; Green, Amelia; McDonald, Helen I; Walker, Alex J; Curtis, Helen J; Morton, Caroline E; MacKenna, Brian; Croker, Richard; Mehrkar, Amir; Bacon, Seb; Evans, David; Inglesby, Peter; Davy, Simon; Bhaskaran, Krishnan; Schultze, Anna; Rentsch, Christopher T; Tomlinson, Laurie; Douglas, Ian J; Evans, Stephen J W; Smeeth, Liam; Palmer, Tom; Goldacre, Ben; Hernán, Miguel A; Sterne, Jonathan A C.
  • Hulme WJ; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Williamson E; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Horne EMF; Population Health Sciences, University of Bristol, Bristol, United Kingdom (E.M.F.H., T.P.).
  • Green A; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • McDonald HI; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Walker AJ; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Curtis HJ; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Morton CE; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • MacKenna B; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Croker R; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Mehrkar A; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Bacon S; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Evans D; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Inglesby P; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Davy S; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Bhaskaran K; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Schultze A; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Rentsch CT; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Tomlinson L; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Douglas IJ; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Evans SJW; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Smeeth L; London School of Hygiene and Tropical Medicine, London, United Kingdom (E.W., H.I.M., K.B., A.S., C.T.R., L.T., I.J.D., S.J.W.E., L.S.).
  • Palmer T; Population Health Sciences, University of Bristol, Bristol, United Kingdom (E.M.F.H., T.P.).
  • Goldacre B; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom (W.J.H., A.G., A.J.W., H.J.C., C.E.M., B.M., R.C., A.M., S.B., D.E., P.I., S.D., B.G.).
  • Hernán MA; Department of Epidemiology, Department of Biostatistics, and CAUSALab, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (M.A.H.).
  • Sterne JAC; Population Health Sciences, University of Bristol; NIHR Bristol Biomedical Research Centre; and Health Data Research UK South West Better Care Partnership, Bristol, United Kingdom (J.A.C.S.).
Ann Intern Med ; 176(5): 685-693, 2023 05.
Article in English | MEDLINE | ID: covidwho-2315495
ABSTRACT
The COVID-19 vaccines were developed and rigorously evaluated in randomized trials during 2020. However, important questions, such as the magnitude and duration of protection, their effectiveness against new virus variants, and the effectiveness of booster vaccination, could not be answered by randomized trials and have therefore been addressed in observational studies. Analyses of observational data can be biased because of confounding and because of inadequate design that does not consider the evolution of the pandemic over time and the rapid uptake of vaccination. Emulating a hypothetical "target trial" using observational data assembled during vaccine rollouts can help manage such potential sources of bias. This article describes 2 approaches to target trial emulation. In the sequential approach, on each day, eligible persons who have not yet been vaccinated are matched to a vaccinated person. The single-trial approach sets a single baseline at the start of the rollout and considers vaccination as a time-varying variable. The nature of the confounding depends on the analysis strategy Estimating "per-protocol" effects (accounting for vaccination of initially unvaccinated persons after baseline) may require adjustment for both baseline and "time-varying" confounders. These issues are illustrated by using observational data from 2 780 931 persons in the United Kingdom aged 70 years or older to estimate the effect of a first dose of a COVID-19 vaccine. Addressing the issues discussed in this article should help authors of observational studies provide robust evidence to guide clinical and policy decisions.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines / Variants Limits: Humans Language: English Journal: Ann Intern Med Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines / Variants Limits: Humans Language: English Journal: Ann Intern Med Year: 2023 Document Type: Article