| Literature DB >> 35322045 |
Eduardo Hermosilla1,2, Ermengol Coma1, Junqing Xie3, Shuo Feng4, Carmen Cabezas5, Leonardo Méndez-Boo1, Francesc Fina1, Elisabet Ballo1, Montserrat Martínez5, Manuel Medina-Peralta1, Josep Maria Argimon5, Daniel Prieto-Alhambra6,7.
Abstract
Small trials have suggested that heterologous vaccination with first-dose ChAdOx1 and second-dose BNT162b2 may generate a better immune response than homologous vaccination with two doses of ChAdOx1. In this cohort analysis, we use linked data from Catalonia (Spain), where those aged <60 who received a first dose of ChAdOx1 could choose between ChAdOx1 and BNT162b2 for their second dose. Comparable cohorts were obtained after exact-matching 14,325/17,849 (80.3%) people receiving heterologous vaccination to 14,325/149,386 (9.6%) receiving homologous vaccination by age, sex, region, and date of second dose. Of these, 464 (3.2%) in the heterologous and 694 (4.8%) in the homologous groups developed COVID-19 between 1st June 2021 and 5th December 2021. The resulting hazard ratio (95% confidence interval) is 0.66 [0.59-0.74], favouring heterologous vaccination. The two groups had similar testing rates and safety outcomes. Sensitivity and negative control outcome analyses confirm these findings. In conclusion, we demonstrate that a heterologous vaccination schedule with ChAdOx1 followed by BNT162b2 was more efficacious than and similarly safe to homologous vaccination with two doses of ChAdOx1. Most of the infections in our study occurred when Delta was the predominant SARS-CoV-2 variant in Spain. These data agree with previous phase 2 randomised trials.Entities:
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Year: 2022 PMID: 35322045 PMCID: PMC8943099 DOI: 10.1038/s41467-022-29301-9
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919
Fig. 1Population flowchart.
Baseline characteristics of study participants according to vaccination schedule.
| Variable | Heterologous | Homologous |
|---|---|---|
| N | 14,325 | 14,325 |
| Mean (SD) age, years | 42.20 (9.60) | 42.21 (9.57) |
| Female sex | 8959 (62.5%) | 8959 (62.5%) |
| Socio-economic status: first quartile (least deprived) | 2725 (19.02%) | 2745 (19.16%) |
| Socio-economic status: second quartile | 4403 (30.74%) | 4363 (30.46%) |
| Socio-economic status: third quartile | 2162 (15.09%) | 2145 (14.97%) |
| Socio-economic status: fourth quartile (most deprived) | 2260 (15.78%) | 2276 (15.89%) |
| Residence in a rural area | 2775 (19.37%) | 2796 (19.52%) |
| Analgesics | 654 (4.57%) | 533 (3.72%) |
| Sedatives/hypnotics | 1049 (7.32%) | 948 (6.62%) |
| Anticoagulants | 201 (1.40%) | 116 (0.81%) |
| Antidepressants | 1228 (8.57%) | 1077 (7.52%) |
| Antiepileptics | 449 (3.13%) | 353 (2.46%) |
| Antipsychotics | 281 (1.96%) | 157 (1.10%) |
| Antacids | 618 (4.31%) | 533 (3.72%) |
| Systemic corticosteroids | 101 (0.71%) | 82 (0.57%) |
| Oral antidiabetics | 187 (1.31%) | 150 (1.05%) |
| Insulin | 105 (0.73%) | 73 (0.51%) |
| Lipid modifying agents | 453 (3.16%) | 410 (2.86%) |
| Alpha blockers | 5 (0.03%) | 2 (0.01%) |
| Other antihypertensives | 4 (0.03%) | 1 (0.01%) |
| Beta blockers | 202 (1.41%) | 193 (1.35%) |
| Calcium channel blockers | 135 (0.94%) | 101 (0.71%) |
| Combination antihypertensives | 209 (1.46%) | 176 (1.23%) |
| Diuretics | 103 (0.72%) | 108 (0.75%) |
| ACE inhibitors/ARBs | 423 (2.95%) | 424 (2.96%) |
| Chronic obstructive pulmonary disease/asthma inhalers | 579 (4.04%) | 528 (3.69%) |
| Atrial fibrillation | 23 (0.16%) | 19 (0.13%) |
| Osteoarthritis | 513 (3.58%) | 533 (3.72%) |
| Asthma | 935 (6.53%) | 910 (6.35%) |
| Ischaemic heart disease | 48 (0.34%) | 38 (0.27%) |
| Diabetes mellitus | 266 (1.86%) | 209 (1.46%) |
| Liver disease | 289 (2.02%) | 278 (1.94%) |
| Hypertension | 826 (5.77%) | 814 (5.68%) |
| Heart failure | 5 (0.03%) | 2 (0.01%) |
| Cerebrovascular disease | 41 (0.29%) | 26 (0.18%) |
| Chronic obstructive pulmonary disease | 46 (0.32%) | 37 (0.26%) |
| Chronic kidney disease | 44 (0.31%) | 54 (0.38%) |
| Cancer (all except non-melanoma skin cancer) | 344 (2.40%) | 325 (2.27%) |
| Obesity | 1539 (10.74%) | 1391 (9.71%) |
| Valvular disease | 73 (0.51%) | 64 (0.45%) |
| Hepatitis B | 20 (0.14%) | 15 (0.10%) |
| Hepatitis C | 49 (0.34%) | 34 (0.24%) |
| HIV infection | 49 (0.34%) | 47 (0.33%) |
Number and incidence rate (per 1000 person-years) of tests and SARS-CoV-2 infection (positive test) following second-dose vaccination according to vaccination schedule.
| Heterologous | Homologous | HR/IRR | |||
|---|---|---|---|---|---|
| N / Mean | IR / SD | N / Mean | IR / SD | [95% CI] | |
| Tested | 4874 | 2.21/1000 py | 5134 | 2.35/1000 py | n/a |
| Number of tests (overall) | 0.82 | 1.65 | 0.87 | 1.68 | 1.01 [0.96–1.06] |
| N of tests among the tested | 2.42 | 2.04 | 2.44 | 2.03 | n/a |
| N of PCR tests (overall) | 0.37 | 1.15 | 0.38 | 1.20 | 1.02 [0.96–1.08] |
| N of PCR tests among the tested | 1.86 | 1.98 | 1.87 | 2.08 | n/a |
| N of LFT tests overall | 0.45 | 1.03 | 0.50 | 1.05 | 1.00 [0.96–1.04] |
| N of LFT tests among the tested | 2.18 | 1.17 | 2.17 | 1.07 | n/a |
| SARS-CoV-2 infection | 464 | 0.18/1000 py | 694 | 0.27/1000 py | 0.66 [0.59–0.74] |
CI confidence interval, HR hazard ratio, IR incidence rate, IRR incidence rate ratio, N number, py person-years of follow-up, SD standard deviation.
Fig. 2Vaccine uptake and testing rates according to vaccination schedule.
Fig. 3Kaplan–Meier plot of COVID-19 infection (primary outcome) after second-dose vaccination according to vaccination schedule.
Number (%) of safety events in the 21 days following second dose, according to vaccination schedule.
| Heterologous | Homologous | |||||
|---|---|---|---|---|---|---|
| 1:1 matching | 1:2 matching | 1:5 matching | 1:1 matching | 1:2 matching | 1:5 matching | |
| N participants | 14,325 | 12,512 | 8569 | 14,325 | 25,024 | 42,845 |
| N (%) of venous thromboembolism events | 1 | 1 | 1 | 0 | 0 | 0 |
| N (%) of venous thromboembolism with thrombocytopenia | 1 | 1 | 1 | 0 | 0 | 0 |
| N (%) of myopericarditis | 0 | 0 | 0 | 0 | 0 | 1 |