Determinants of anti-S immune response at 6 months after COVID-19 vaccination in a multicentric European cohort of healthcare workers – ORCHESTRA project

Collatuzzo, Giulia; Visci, Giovanni; Violante, Francesco Saverio; Porru, Stefano; Spiteri, Gianluca; Monaco, Maria Grazia Lourdes; Fillon, Francesca Larese; Negro, Corrado; Janke, Christian; Castelletti, Noemi; Palma, Giuseppe De; Sansone, Emanuele; Mateș, Dana; Teodorescu, Silvia; Fabiánovà, Eleonóra; Vimercati, Luigi; Tafuri, Silvio; Abedini, Mahsa; Ditano, Giorgia; Asafo, Shuffield Seyram; Boffetta, Paolo

doi:10.3389/fimmu.2022.986085

Cited by 19 publications

(43 citation statements)

References 44 publications

(69 reference statements)

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“…Several studies have demonstrated the lower levels of immunological responsiveness of older subjects ( 16 ). This is consistent with our previous study that showed age as a determinant of lower level of serologic response in HCW ( 11 ). When focusing on gender differences, a 2% smaller probability of undergoing a one standard error decrease in antibody level was suggested for women, consistent with previous literature ( 17 – 19 ).…”

Section: Discussionsupporting

confidence: 94%

“…Previous studies focused on HCW as a job category rather than distinguishing potential association with COVID-19 infection and vaccination outcomes. For example, in a previous analysis we once again found no relationship between job title and immunological response ( 11 ). Moreover, a previous study based on the Italian cohort of the ORCHESTRA project found no difference in the risk of HCW contracting COVID-19, even when considering HCW in departments dedicated to COVID-19 ( 22 ).…”

Section: Discussionmentioning

confidence: 69%

“…However, as mentioned above, we addressed this issue by using the standardized log value and calculating RR per one SD increase, thus generating harmonized results on measurements of antibody levels. The same method was used in our previous analysis ( 11 ). This approach is particularly valuable given the global connotation of COVID-19 infection, because it allows us to overcome potential heterogeneity in data collection methods and to compare data from different populations.…”

Section: Discussionmentioning

confidence: 99%

“…We therefore log transformed the results and then we divided them by the standard errors (SE) of each cohort-specific mean. We used the same approach in previous analyses within ORCHESTRA ( 10 , 11 ).…”

Section: Methodsmentioning

confidence: 99%

“…Previous analyses in this cohort described the determinants of 3- and 6-months serology following COVID-19 vaccination ( 10 , 11 ). The objective of the present study is to delineate the trends of serologic levels in the first 13 months post vaccination, both overall and by month, in a population of approximately 20,000 HCW based on nine European study populations (five from Italy, two from Spain, one multicentric from Romania, and one multicentric from Slovakia) included in ORCHESTRA.…”

Section: Introductionmentioning

confidence: 99%

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Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: An individual-level analysis within 13 months in the ORCHESTRA cohort

et al. 2023

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Short summaryWe investigated changes in serologic measurements after COVID-19 vaccination in 19,422 subjects. An individual-level analysis was performed on standardized measurements. Age, infection, vaccine doses, time between doses and serologies, and vaccine type were associated with changes in serologic levels within 13 months.BackgroundPersistence of vaccine immunization is key for COVID-19 prevention.MethodsWe investigated the difference between two serologic measurements of anti-COVID-19 S1 antibodies in an individual-level analysis on 19,422 vaccinated healthcare workers (HCW) from Italy, Spain, Romania, and Slovakia, tested within 13 months from first dose. Differences in serologic levels were divided by the standard error of the cohort-specific distribution, obtaining standardized measurements. We fitted multivariate linear regression models to identify predictors of difference between two measurements.ResultsWe observed a progressively decreasing difference in serologic levels from <30 days to 210–240 days. Age was associated with an increased difference in serologic levels. There was a greater difference between the two serologic measurements in infected HCW than in HCW who had never been infected; before the first measurement, infected HCW had a relative risk (RR) of 0.81 for one standard deviation in the difference [95% confidence interval (CI) 0.78–0.85]. The RRs for a 30-day increase in time between first dose and first serology, and between the two serologies, were 1.08 (95% CI 1.07–1.10) and 1.04 (95% CI 1.03–1.05), respectively. The first measurement was a strong predictor of subsequent antibody decrease (RR 1.60; 95% CI 1.56–1.64). Compared with Comirnaty, Spikevax (RR 0.83, 95% CI 0.75–0.92) and mixed vaccines (RR 0.61, 95% CI 0.51–0.74) were smaller decrease in serological level (RR 0.46; 95% CI 0.40–0.54).ConclusionsAge, COVID-19 infection, number of doses, time between first dose and first serology, time between serologies, and type of vaccine were associated with differences between the two serologic measurements within a 13-month period.

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Section: Discussionsupporting

confidence: 94%

Section: Discussionmentioning

confidence: 69%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: An individual-level analysis within 13 months in the ORCHESTRA cohort

et al. 2023

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Accounting for time dependency in meta‐analyses of concordance probability estimates

Schmid

Friede

Klein

et al. 2023

Research Synthesis Methods

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Recent years have seen the development of many novel scoring tools for disease prognosis and prediction. To become accepted for use in clinical applications, these tools have to be validated on external data. In practice, validation is often hampered by logistical issues, resulting in multiple small‐sized validation studies. It is therefore necessary to synthesize the results of these studies using techniques for meta‐analysis. Here we consider strategies for meta analyzing the concordance probability for time‐to‐event data (“C‐index”), which has become a popular tool to evaluate the discriminatory power of prediction models with a right‐censored outcome. We show that standard meta‐analysis of the C‐index may lead to biased results, as the magnitude of the concordance probability depends on the length of the time interval used for evaluation (defined e.g., by the follow‐up time, which might differ considerably between studies). To address this issue, we propose a set of methods for random‐effects meta‐regression that incorporate time directly as covariate in the model equation. In addition to analyzing nonlinear time trends via fractional polynomial, spline, and exponential decay models, we provide recommendations on suitable transformations of the C‐index before meta‐regression. Our results suggest that the C‐index is best meta‐analyzed using fractional polynomial meta‐regression with logit‐transformed C‐index values. Classical random‐effects meta‐analysis (not considering time as covariate) is demonstrated to be a suitable alternative when follow‐up times are small. Our findings have implications for the reporting of C‐index values in future studies, which should include information on the length of the time interval underlying the calculations.

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Sex-Differential and Non-specific Effects of Vaccines Over the Life Course

St. Clair,

Chaulagain,

Klein

et al. 2023

Current Topics in Microbiology and Immunology

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Determinants of anti-S immune response at 6 months after COVID-19 vaccination in a multicentric European cohort of healthcare workers – ORCHESTRA project

Cited by 19 publications

References 44 publications

Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: An individual-level analysis within 13 months in the ORCHESTRA cohort

Temporal trends of COVID-19 antibodies in vaccinated healthcare workers undergoing repeated serological sampling: An individual-level analysis within 13 months in the ORCHESTRA cohort

Accounting for time dependency in meta‐analyses of concordance probability estimates

Sex-Differential and Non-specific Effects of Vaccines Over the Life Course

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