key: cord-0778132-v7annrym
authors: Mehew, Jennifer; Johnson, Rachel; Roberts, David; Griffiths, Alex; Harvala, Heli
title: Convalescent plasma for COVID‐19: Donor demographic factors associated high neutralising antibody titres
date: 2022-04-17
journal: Transfus Med
DOI: 10.1111/tme.12868
sha: 93db7b1b751f1ce3c9c8262cfc058938a74199ce
doc_id: 778132
cord_uid: v7annrym

BACKGROUND: Convalescent plasma containing high levels of SARS‐CoV‐2 antibodies has been studied as a possible treatment for COVID‐19. Better understanding of predictors of high antibody levels is needed for improving supply of high‐quality therapeutic plasma. AIMS: We have evaluated demographic and clinical factors associated with the probability of a convalescent plasma donor having high SARS‐CoV‐2 IgG antibody levels. METHODS: A total of 29,585 convalescent plasma donors employed during the first and second waves of the COVID‐19 pandemic in England were included in this study. All had been tested for SARS‐CoV‐2 IgG antibodies by EUROimmun ELISA. A multivariable logistic regression model was used to quantify the association of the demographic and clinical factors with high (EUROimmun S/Co>6.0) SARS‐CoV‐2 IgG antibody level. RESULTS: Most of the donors were male (23,024; 78%), with white ethnic background (24,598;83%) and had not been tested for SARS‐CoV‐2 (15,266; 52%).Overall, less than 20% of convalescent plasma donors with confirmed or suspected SARS‐CoV‐2 infection harboured high SARS‐CoV‐2 antibody levels (n = 4,978). We found that older male donors who had been hospitalised with COVID‐19 were most likely to harbour high levels of antibodies. White donors were less likely to have high SARS‐CoV‐2 antibody levels than donors with Asian orblack ethnic backgrounds residing in affluent areas likely reflecting ethnic inequality previously associated with SARS‐CoV‐2 infection. DISCUSSION: In a time of great uncertainty, and predicted new waves associated with newly emerging SARS‐CoV‐2 variants, these results will help us to target future convalescent plasma collections.

treatment did not decrease all-cause mortality, 2,3 it may be beneficial if given in early stages of infection [4] [5] [6] [7] or used to treat those unable to mount an effective immune response. 3, [8] [9] [10] Although immunisations programmes are advancing very fast, rapid spread of new SARS-CoV-2 variants with several mutations in the spike (S) glycoprotein that may show increased resistance to neutralisation have raised concerns [11] [12] [13] and might support future use for convalescent plasma.

We have previously demonstrated a correlation between virus neutralising antibody titres and antibody reactivity in commercial EUROimmun ELISA IgG tests in convalescent plasma collected from individuals with confirmed or suspected SARS-CoV-2 infection at least 28 days after the resolution of their symptoms. 14, 15 Based on that, we adopted a strategy where all donations with a signal to cut-off (S/CO) ratio of 6.0 or higher in the EUROimmun assay were released for clinical use without further virus neutralisation testing. 14 

This study includes 29 585 convalescent plasma donors with a confirmed or suspected SARS-CoV-2 infection, all at least 28 days post the resolution of their symptoms at the time of donation between 22 April and 16 December 2020. All had been tested for SARS-CoV-2 IgG antibodies by EUROimmun ELISA. 14, 15 Many of these donors donated more than once during the study period but only data from their first donation or sample were included in the analysis. To optimise use of available session time, some donors (including female donor and those without a confirmed SARS-CoV-2 infection) were invited for a medical assessment and sample-only collection before a full donation was collected.

SARS-CoV-2 IgG antibody level was defined as high if Euroimmun s/co ratio was 6.0 or higher. Donor demographic factors including sex, age, ethnic origin, blood group, geographic region based on donor centre details, social deprivation score based on donor's home postcode and using Acorn classification, 16 

Sociodemographic and clinical characteristics were summarised using descriptive statistics, stratified by SARS-CoV-2 IgG antibody level.

A multivariable logistic regression model was developed on the development dataset based on 70% of randomly selected donors to test and quantify the association of the 10 aforementioned factors with high (EUROimmun S/Co >6.0) SARS-CoV-2 IgG antibody level.

A stepwise variable selection method was used; candidate explanatory variables were retained in the model if they reduced the model deviance significantly (p < 0.1) according to the likelihood ratio test.

Donors with missing data for any of the significant variables were excluded from the model. The logistic regression model is commonly interpreted through the odds ratio. The probability that a donor will exhibit high SARS-CoV-2 antibody levels is linked to the odds through the following equation:

Therefore, the higher the odds, the higher the probability and the smaller p is, the closer the odds and the probability become.

Two-way variable interactions were considered between all the variables that were found to be significant as main effects, with the exception of donor centre region and timing of their donation (calculated as days since project began) as any interactions involving these two variables were not considered clinically meaningful. Two continuous variables (timing of the donation calculated as days since project began and the time between SARS-CoV-2 detection and donation)

were tested once as a linear variable and once as a non-linear variable.

Natural cubic splines were used to represent non-linearity, enabling cubic expressions between 'knots' at the 5%, 35%, 65% and 95% percentiles. A model containing the spline terms would be considered more appropriate than a model containing just the linear term if it reduced the model deviance significantly (p < 0.1) according to the likelihood ratio test. Because the time between SARS-CoV-2 detection and donation could not be calculated for donors without a SARS-CoV-2 test, this variable was tested at the end of the modelling process on a subset of donors with an available SARS-CoV-2 positive result.

The Hosmer and Lemeshow C statistic (equivalent to the area under the ROC curve) was calculated to assess predictive ability.

A value of 0.5 indicates that the model predicts no better than adopting a 50/50 guess and a value of 1 indicates perfect prediction, whereas values between 0.7 and 0.8 show acceptable predictive ability. Deviance residuals were assessed to identify any outlying observations. Cooks D statistic was plotted for each observation to identify any values that were highly influential in the calculation of the set of parameter estimates (referred to as influential observations). The Delta-betas were also plotted against each observation for each parameter in the model to identify any observations that highly influenced particular parameter estimates. 

The parameter estimates from the developed model were used to cal- was fitted to the validation dataset in order to assess odds ratio differences between these four groups of donors. The distribution of estimated probabilities was also compared between the donors with low and high SARS-CoV-2 antibody levels in the validation dataset. Ethnic group x social Interaction term Table 2 ).

The influences of age, gender, and test group on the probability that a donor would have high SARS-CoV-2 antibody levels were interpreted collectively due to significant interactions identified between these variables (Table 2) . Male donors who had tested positive for SARS-CoV-2 but had not been hospitalised were more likely to have high antibody levels than those without a SARS-CoV-2 positive test across all age groups ( Figure 3 ). Male donors with a laboratory confirmed SARS-CoV-2 diagnosis who were hospitalised were even more likely to have high antibody levels than those who had not been tested or hospitalised, and this impact was pronounced by age: those male donors who were 65 years of age or over, were tested positive for SARS-CoV-2 and hospitalised were most likely to harbour high antibody levels (OR 37.07, 95% CI 8.58-160.14). A similar relationship between age, gender, laboratory diagnosis and hospitalisation status were found for females, but the odds of high SARS-CoV-2 antibody levels were generally lower than for males ( Figure 4 ). However, it is important to note that some of these differences were based on very Similarly, the effects of donor ethnicity and social deprivation indicator were assessed together due to a significant interaction identified between these two factors ( We also assessed the significant (p < 0.0001) non-linear effect of timing of donation (days since the project began) on the probability of high SARS-CoV-2 antibody levels ( Figure 6 ). The odds of donors having high antibody levels appears to have decreased over time since the beginning of the project. However, the rate of decrease slowed down around mid-October (day 170) co-inciding with the increase in reported SARS-CoV-2 cases in the United Kingdom.

As the Hosmer and Lemeshow C statistic was >0.7, the model was considered to exhibit acceptable predictive ability. Residual analysis highlighted one donor that influenced the age and test group interaction parameter estimate however this donor was kept in the dataset

The interdependent effect of Ethnic Group and Social Deprivation Indicator on probability of high SARS-CoV-2 antibody levels F I G U R E 6 Odds ratios illustrating the non-linear effect of days since project began for high SARS-CoV-2 antibody levels as it was a genuine observation that led to more conservative results.

Some variables with smaller numbers of observations were, by definition, slightly more susceptible to influential values but there were no observations that posed a particular concern.

The estimated probability of high SARS-CoV-2 antibody level was calculated for 8511 donors in the validation dataset using the parameter estimates from the developed model ( Figure S1 ). The donors were categorised into four groups defined by the quartile values of the equivalent estimated probabilities from the development dataset; and a logistic regression model was used to assess difference in the probability of high antibody levels between these four groups ( Table S1 ).

The resulting C statistic of 0.720 indicated good predictive ability of this model. Furthermore, the median estimated probabilities for donors with high SARS-CoV-2 antibody levels was 0.22 compared to 0.10 for donors with low antibody levels ( Figure S2 ). Overall, model validation therefore suggested that our model was able to adequately identify donors with a higher chance of high SARS-CoV-2 antibody levels.

This is a large convalescent plasma donor cohort study to date reflecting a commitment of time, resources and generosity from NHS staff and almost 30 000 donors who took part in the convalescent plasma programme in England. To investigate the trends in demographic and clinical factors that influence the probability of individuals with previous SARS-CoV-2 infection to produce a good antibody response in such a large dataset has allowed us to draw robust conclusions from these data.

We showed that older donors, male donors, and donors previously hospitalised with SARS-CoV-2 infection were generally much more likely to have high levels of antibodies. This was consistent with previous findings, based on neutralising antibody testing of a smaller set of donors. 16 It should be noted that during the course of the study, there was a substantial drive to recruit male donors because the preliminary analysis suggested a greater probability of high antibody levels compared to females. 16 Overall, 78% of donors were male.

Female donors were generally only recruited if they had confirmed SARS-CoV-2 and thus thought to have increased probability of high antibody levels. Sex differences in COVID-19 severity were first noted in China; hospital admissions and mortality were higher among males than females. [18] [19] [20] Further male bias in COVID-19 mortality has been reported by 37 of the 38 countries providing sex -disaggregated data. 21 It has been proposed that these differences observed between males and females in response to SARS-CoV-2 infection are likely due to differences in their innate and adaptive immune responses driven by biological sex, including sex chromosomes and sex steroids (reviewed by Scully et al). 21 Similarly, differences in mortality between males and females were previously investigated in animal models of SARS-CoV infection, and these were attributed to steroid hormones. 22 With this dataset we were also able to demonstrate that donors from an Asian background had higher likelihood of having high SARS-CoV-2 antibody levels compared to white donors; although this disparity was enhanced in affluent areas, it was also seen in deprived areas. In contrast, the likelihood of having high SARS-CoV-2 antibody levels was increased only among those black donors residing in affluent areas. Data on the disproportionate effect of SARS-CoV-2 infection on black, Asian, and other minority ethnic people and possible reasons underlying that has been recently reviewed. 23 The results

suggest that people of black and Asian ethnic groups are more likely to be diagnosed with COVID-19. People from Asian and black ethnic groups have also been shown to be more likely hospitalised with SARS-CoV-2 infection when compared to those with white ethnicity (threefold and twofold, respectively). Furthermore, the evidence emerging from the United Kingdom suggests that those of black or

Asian ethnicity are around twice as likely to die from SARS-CoV-2 infection than those of white British ethnicity. 24 It has been proposed that black and Asian people are more likely to work in occupations with a higher risk of SARS-CoV-2 exposure or due to overcrowded housing, and might also delay seeking medical care when needed due to their negative past experiences with healthcare. 23 Although these cultural differences may impact the disease risk, it has also been shown recently that poverty is another independent risk factor for COVID-19 related mortality. 25 Reassuringly for the convalescent plasma programmes and those having been infected with SARS-CoV-2, the interval between a laboratory confirmed SARS-CoV-2 diagnosis and plasma donation was not found to be significantly associated with the likelihood of them having high antibody levels for the range of durations in our cohort (up to 327 days), indicating that in some donors high SARS-CoV-2 antibody levels remain over time. Decreases in SARS-CoV-2 neutralising antibody levels have been demonstrated in some [34] [35] [36] [37] but not all previous studies. 38 One of these studies demonstrated a trend towards lower antibody levels with increased time between symptoms and blood sampling, and a decline of neutralising antibody titres over time based on repeat testing of the same donors. 37 The difference between our results and their findings cannot be explained by methodology as 

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SUPPORTING INFORMATION Additional supporting information may be found in the online version of the article at the publisher's website. How to cite this article

The authors declare no conflict of interest.

All authors discussed and planned the study, Jennifer Mehew performed the multivariable analysis and drafted the first version of manuscript together with Heli Harvala. All authors critically reviewed the manuscript and accepted the last version of it.

https://orcid.org/0000-0001-9154-4190