| Literature DB >> 35915081 |
Nina Breinholt Stærke1,2, Joanne Reekie3, Henrik Nielsen4,5, Thomas Benfield6,7, Lothar Wiese8, Lene Surland Knudsen8, Mette Brouw Iversen8, Kasper Iversen9, Kamille Fogh9, Jacob Bodilsen4,5, Maria Ruwald Juhl4, Susan Olaf Lindvig10, Anne Øvrehus10, Lone Wulff Madsen10,11, Vibeke Klastrup12, Sidsel Dahl Andersen12, Anna Karina Juhl12, Signe Rode Andreasen12, Sisse Rye Ostrowski7,13, Christian Erikstrup14,15, Thea K Fischer7,16, Martin Tolstrup12,14, Lars Østergaard12,14, Isik Somuncu Johansen10,11, Jens Lundgren3,7, Ole Schmeltz Søgaard12,14.
Abstract
SARS-CoV-2 variants of concern have continuously evolved and may erode vaccine induced immunity. In this observational cohort study, we determine the risk of breakthrough infection in a fully vaccinated cohort. SARS-CoV-2 anti-spike IgG levels were measured before first SARS-CoV-2 vaccination and at day 21-28, 90 and 180, as well as after booster vaccination. Breakthrough infections were captured through the Danish National Microbiology database. incidence rate ratio (IRR) for breakthrough infection at time-updated anti-spike IgG levels was determined using Poisson regression. Among 6076 participants, 127 and 364 breakthrough infections due to Delta and Omicron variants were observed. IRR was 0.29 (95% CI 0.15-0.56) for breakthrough infection with the Delta variant, comparing the highest and lowest quintiles of anti-spike IgG. For Omicron, no significant differences in IRR were observed. These results suggest that quantitative level of anti-spike IgG have limited impact on the risk of breakthrough infection with Omicron.Entities:
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Year: 2022 PMID: 35915081 PMCID: PMC9342834 DOI: 10.1038/s41467-022-32254-8
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 17.694
Participant demographics at baseline (14 days after second SARS-CoV-2 vaccination)
| Breakthrough infection during follow-up | Variant | ||||
|---|---|---|---|---|---|
| Total ( | No ( | Yes ( | Delta ( | Omicron ( | |
| Age at enrolment (median, IQR) | 64 (54, 75) | 64 (55, 75) | 56 (47, 68) | 58 (48, 69) | 55 (46, 68) |
| <55 | 1615 (26.6) | 1380 (24.8) | 235 (46.6) | 51 (40.2) | 177 (48.6) |
| 55–64 | 1543 (25.4) | 1425 (25.6) | 118 (23.4) | 34 (26.8) | 79 (21.7) |
| ≥65 | 2918 (48.0) | 2767 (49.7) | 151 (30.0) | 42 (33.1) | 108 (29.7) |
| Male | 2675 (44.0) | 2474 (44.4) | 201 (39.9) | 62 (48.8) | 132 (36.3) |
| Female | 3401 (56.0) | 3098 (55.6) | 303 (60.1) | 65 (51.2) | 232 (63.7) |
| Pfizer-BioNTech | 3369 (55.4) | 3113 (55.9) | 256 (50.8) | 72 (56.7) | 179 (49.2) |
| Moderna | 2363 (38.9) | 2168 (38.9) | 195 (38.7) | 54 (42.5) | 135 (37.1) |
| AstraZeneca/mRNA | 344 (5.7) | 291 (5.2) | 53 (10.5) | 1 (0.8) | 50 (13.7) |
| Individuals at increased riska | 1434 (23.6) | 1322 (23.7) | 112 (22.2) | 28 (22.0) | 83 (22.8) |
| Healthcare worker | 432 (7.1) | 371 (6.7) | 61 (12.1) | 2 (1.6) | 55 (15.1) |
| General population | 4210 (69.3) | 3879 (69.6) | 331 (65.7) | 97 (76.4) | 226 (62.1) |
The Delta variant analysis includes 6063 participants, and the Omicron variant analysis includes 5050 participants.
aIndividuals at increased risk includes cancer patients in active treatment, patients with immunodeficiencies (acquired or inherent), organ transplant recipients, hemodialysis patients, and patients with severe hematological, pulmonary or rheumatological diseases.
Fig. 1Main analysis adjusted and unadjusted incidence rate ratios for breakthrough infection.
A Schematic overview of the analysis design. The syringe icon represents vaccinations, the blood sample icons represent blood draws and the shaded area represents the censored time period. Participants were censored at the time of third SARS-CoV-2 vaccination and re-entered the analysis at the time of the post-booster blood draw. B Forest plot of the adjusted incidence rate ratios (aIRR) for breakthrough infections. Incidence rate ratios (IRR) and adjusted incidence rate ratios (aIRR) for breakthrough infections calculated using a Poisson regression analysis for each quintile of SARS-CoV-2 anti-spike IgG log10 BAU, stratified by viral variant. The multivariable models were adjusted for age at enrolment (per year later), gender (male vs female), being healthcare worker (no vs yes) and transmission level with two-sided chi-squared tests for each variable in the model. The multivariable model for the Omicron variant did not include transmission level as all Omicron breakthrough infections occurred during the very high transmission period. All variants analysis: n = 6076, Delta analysis: n = 6063, Omicron analysis: n = 5050. The forest plot presents the aIRR and 95% confidence intervals from the multivariable models. *Person-days of follow-up.
Fig. 2Sensitivity analysis adjusted and unadjusted incidence rate ratios for breakthrough infection.
A Schematic overview of the analysis design. The syringe icon represents vaccinations, the blood sample icon represents blood draws, and the shaded areas represents the censored time periods. The analysis includes the first thirty days following each study visit blood draw. B Forest plot of the adjusted incidence rate ratios (aIRR) for breakthrough infections Incidence rate ratios (IRR) and adjusted incidence rate ratios (aIRR) for breakthrough infections calculated using a Poisson regression analysis for each quintile of SARS-CoV-2 anti-spike IgG log10 BAU, stratified by viral variant. Multivariable models were adjusted for age at enrolment (per year later), gender (male vs female), being healthcare worker (no vs yes) and transmission level with two-sided chi-squared tests for each variable in the model. The multivariable model for the Omicron variant did not include transmission level as all infections occurred during the very high transmission period. The multivariable model for the Delta variant did not include healthcare worker, as there were no delta infections in this group in the sensitivity analysis. All variants analysis: n = 6073, Delta analysis: n = 6034, Omicron analysis: n = 4388. The forest plot presents the aIRR and 95% confidence intervals from the multivariable models. *Person days of follow-up.
Factors associated with breakthrough infection (n = 6076)
| Breakthrough infections | PDFUa | Univariable | Multivariable | |||
|---|---|---|---|---|---|---|
| IRR (95% CI) | aIRR (95% CI) | |||||
| ≤1.77 | 44 | 242,045 | 1.00 | 1.00 | ||
| 1.77–2.29 | 45 | 242,074 | 1.02 (0.68–1.54) | 0.91 | 0.68 (0.45–1.02) | 0.06 |
| 2.29–2.69 | 78 | 241,982 | 1.77 (1.23–2.56) | 0.002 | 0.75 (0.52–1.09) | 0.13 |
| 2.69–3.02 | 114 | 242,134 | 2.59 (1.84–3.65) | <0.0001 | 0.79 (0.56–1.11) | 0.17 |
| >3.02 | 223 | 241,968 | 5.07(3.68–6.98) | <0.0001 | 0.71 (0.51–0.98) | 0.03 |
| 0.97 (0.96–0.97) | <0.0001 | 0.97 (0.97–0.98) | <0.0001 | |||
| Male | 201 | 543,681 | 1.00 | 1.00 | ||
| Female | 303 | 666,522 | 1.23 (1.03–1.46) | 0.02 | 0.98 (0.82–1.17) | 0.78 |
| No | 443 | 1,124,364 | 1.00 | 1.00 | ||
| Yes | 61 | 85,839 | 1.80 (1.40–2.32) | <0.0001 | 1.18 (0.89–1.55) | 0.24 |
| Low | 7 | 310,364 | 1.00 | 1.00 | ||
| Intermediate | 36 | 569,908 | 2.60 (1.25–6.29) | 0.01 | 2.80 (1.25–6.30) | 0.01 |
| High | 51 | 134,818 | 16.77 (7.61–36.95) | <0.0001 | 16.56 (7.49–36.64) | <0.0001 |
| Very high | 410 | 195,113 | 93.17 (44.15–196.62) | <0.0001 | 94.49 (44.58–200.30) | <0.0001 |
Incidence rate ratios (IRR) and adjusted incidence rate ratios (aIRR) for breakthrough infections modelled in a univariable and multivariable poisson logistic regression model, with two-sided chi-squared tests for each variable in the model.
aPerson-days of follow-up.
bLow: <10 cases/100,000 population/day, moderate: 10–40 cases/100,000 population/day, high: 41–85 cases/100,000 population/day and very high: >85 cases/100,000 population/day.