| Literature DB >> 35858680 |
William J Hulme1, Elizabeth J Williamson2, Amelia C A Green1, Krishnan Bhaskaran2, Helen I McDonald2, Christopher T Rentsch2, Anna Schultze2, John Tazare2, Helen J Curtis1, Alex J Walker1, Laurie A Tomlinson2, Tom Palmer3,4, Elsie M F Horne4,5, Brian MacKenna1, Caroline E Morton1, Amir Mehrkar1, Jessica Morley1, Louis Fisher1, Sebastian C J Bacon1, David Evans1, Peter Inglesby1, George Hickman1, Simon Davy1, Tom Ward1, Richard Croker1, Rosalind M Eggo2, Angel Y S Wong2, Rohini Mathur2, Kevin Wing2, Harriet Forbes2, Daniel J Grint2, Ian J Douglas2, Stephen J W Evans2, Liam Smeeth2, Chris Bates6, Jonathan Cockburn6, John Parry6, Frank Hester6, Sam Harper6, Jonathan A C Sterne4,5,7, Miguel A Hernán8,9, Ben Goldacre1.
Abstract
OBJECTIVE: To compare the effectiveness of the BNT162b2 mRNA (Pfizer-BioNTech) and the ChAdOx1 (Oxford-AstraZeneca) covid-19 vaccines against infection and covid-19 disease in health and social care workers.Entities:
Mesh:
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Year: 2022 PMID: 35858680 PMCID: PMC9295078 DOI: 10.1136/bmj-2021-068946
Source DB: PubMed Journal: BMJ ISSN: 0959-8138
Baseline characteristics of participants on day of covid-19 vaccination, by vaccine type. Values are numbers (percentages) of participants unless stated otherwise
| Characteristic | BNT162b2 (n=253 134) | ChAdOx1 (n=64 207) |
|---|---|---|
| Age (years): | ||
| 18-30 | 41 086 (16) | 10 464 (16) |
| 30s | 59 518 (24) | 14 724 (23) |
| 40s | 64 553 (26) | 16 286 (25) |
| 50s | 67 776 (27) | 17 543 (27) |
| 60-64 | 20 201 (8.0) | 5,190 (8.1) |
| Sex: | ||
| Female | 200 149 (79) | 49 331 (77) |
| Male | 52 985 (21) | 14 876 (23) |
| Ethnicity: | ||
| White | 211 463 (84) | 54 287 (85) |
| Black | 8 518 (3.4) | 3 161 (4.9) |
| South Asian | 23 140 (9.1) | 4 701 (7.3) |
| Mixed | 3 848 (1.5) | 1 007 (1.6) |
| Other | 6 165 (2.4) | 1 051 (1.6) |
| Index of Multiple Deprivation (IMD): | ||
| 1 (most deprived) | 36 850 (15) | 10 300 (16) |
| 2 | 47 279 (19) | 12 116 (19) |
| 3 | 55 832 (22) | 13 751 (21) |
| 4 | 57 499 (23) | 14 353 (22) |
| 5 (least deprived) | 55 674 (22) | 13 687 (21) |
| Region: | ||
| North East and Yorkshire | 53 522 (21) | 16 418 (26) |
| East of England | 62 377 (25) | 11 861 (18) |
| Midlands | 50 582 (20) | 17 224 (27) |
| South West | 35 948 (14) | 5 056 (7.9) |
| London | 10 405 (4.1) | 2 148 (3.3) |
| North West | 23 644 (9.3) | 7 875 (12) |
| South East | 16 656 (6.6) | 3 625 (5.6) |
| Rural/urban category: | ||
| Urban conurbation | 61 699 (24) | 19 295 (30) |
| Urban city or town | 144 222 (57) | 32 194 (50) |
| Rural town or village | 47 213 (19) | 12 718 (20) |
| Median (interquartile range) vaccination day (from 4 January 2021) | 12 (7-18) | 19 (13-33) |
| Body mass index >40 (kg/m2) | 9 789 (3.9) | 2 860 (4.5) |
| Chronic heart disease | 9 207 (3.6) | 2 527 (3.9) |
| Chronic kidney disease | 1 994 (0.8) | 551 (0.9) |
| Diabetes | 12 674 (5.0) | 3 339 (5.2) |
| Chronic liver disease | 3 854 (1.5) | 1 189 (1.9) |
| Chronic respiratory disease | 2 579 (1.0) | 731 (1.1) |
| Chronic neurological disease | 6 063 (2.4) | 1 620 (2.5) |
| Immunosuppressed | 2 527 (1.0) | 681 (1.1) |
| Asplenia or poor spleen function | 1 704 (0.7) | 481 (0.7) |
| Learning disabilities | 187 (<0.1) | 60 (<0.1) |
| Serious mental illness | 1 276 (0.5) | 434 (0.7) |
| Morbidity count: | ||
| 0 | 210 107 (83) | 52 455 (82) |
| 1 | 36 544 (14) | 9 835 (15) |
| ≥2 | 6 483 (2.6) | 1 917 (3.0) |
| Prior SARS-CoV-2 infection | 27 312 (11) | 9 085 (14) |
| No of SARS-CoV-2 tests in previous 3 months: | ||
| 0 | 160 576 (63) | 42 095 (66) |
| 1-3 | 73 611 (29) | 18 946 (30) |
| 4-6 | 10 696 (4.2) | 1 765 (2.7) |
| ≥7 | 8 251 (3.3) | 1 401 (2.2) |
Fig1Cumulative enrolment of study participants over time, by covid-19 vaccine type (ChAdOx1 and BNT162b2)
Fig 2Comparative effectiveness of covid-19 vaccine ChAdOx1 and BNT162b2. For each outcome based on the fully adjusted model, the marginal cumulative incidence for ChAdOx1 and BNT162b2, their difference, and the hazard ratio are shown. The models with less extensive confounder adjustment gave similar estimates (supplementary fig S2), suggesting that recipients of each vaccine were similar after accounting for differences in vaccine allocation over space and time (as did all models). Models that assumed piecewise-constant hazards gave similar effect estimates (supplementary fig S3).