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Renal medicine
Original research
Humoral response to SARS-CoV-2 vaccination in haemodialysis patients and a matched cohort
  1. Tianchen Zhao1,
  2. Takamitsu Nishi-uchi2,
  3. Fumiya Omata3,
  4. Morihito Takita1,
  5. Moe Kawashima1,
  6. Yoshitaka Nishikawa2,3,
  7. Chika Yamamoto1,
  8. Yurie Kobashi1,3,
  9. Takeshi Kawamura4,
  10. Kenji Shibuya5,
  11. Junichiro Kazama6,
  12. Ryuzaburo Shineha2,
  13. Masaharu Tsubokura1,2,3,5
  1. 1Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan
  2. 2Soma Central Hospital, Fukushima, Japan
  3. 3Department of General Internal Medicine, Hirata Central Hospital, Fukushima, Japan
  4. 4Proteomics Laboratory, Isotope Science Center, The University of Tokyo, Tokyo, Japan
  5. 5Tokyo Foundation for Policy Research, Tokyo, Japan
  6. 6Department of Nephrology and Hypertension, Fukushima Medical University School of Medicine, Fukushima, Japan
  1. Correspondence to Dr Masaharu Tsubokura; tsubo-m{at}fmu.ac.jp

Abstract

Objectives SARS-CoV-2 vaccination is a crucial intervention for infection control; however, the immune response to vaccination in dialysis patients has been reported to be moderate compared with healthy adults. There are few studies available on humoral response in immunised dialysis patients compared with well-matched control group, we conducted a prospective cohort study measuring SARS-CoV-2 antibody titres in Fukushima Prefecture, Japan since September 2021.

Participants We compared the titres of both anti-SARS-CoV-2 S1 IgG and neutralising antibodies of 65 haemodialysis patients (dialysis group) with 500 residents in Soma, Fukushima (control group).

Methods Coarsened exact matching was used to balance sex, age and days from the second dose between dialysis and control groups.

Results Significant differences in the titres of anti-SARS-CoV-2 S1 IgG and neutralising antibodies were observed between the dialysis and control groups; anti-SARS-CoV-2 S1 IgG: 168.35 (4.48–1074.29) AU/mL and 269.81 (4.72–945.96) AU/mL in dialysis and control groups, p=0.02, neutralising antibodies: 35.77 (2.94–826.06) AU/mL and 62.22 (0.00–535.57) AU/mL, p=0.007, respectively).

Conclusions We observed significantly reduced anti-SARS-CoV-2 S1 antibody and neutralising antibodies in haemodialysis patients compared with cohorts matched for duration after vaccination. Patients receiving haemodialysis should be carefully monitored for immunological responses to the vaccination and COVID-19 infection.

  • IMMUNOLOGY
  • End stage renal failure
  • INFECTIOUS DISEASES

Data availability statement

All data relevant to the study are included in the article or uploaded as online supplemental information.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2022-065741

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    STRENGTHS AND LIMITATIONS OF THIS STUDY

    • We compared the anti-SARS-CoV-2 S1 IgG and neutralising antibodies titres of the dialysis group with the control group.

    • Coarsened exact matching method was used to balance sex, age and days from second dose between dialysis and control groups.

    • We evaluated the initial measurement of anti-SARS-CoV-2 antibodies as a preliminary study and did not assess longitudinal changes in antibody titres over time.

    • Detailed characteristics of dialysis patients such as duration of dialysis and their epidemiology were not available in this study.

    Introduction

    Patients receiving haemodialysis are at high risk of SARS-CoV-2 infection and mortality.1 2 Patients with end-stage renal disease are susceptible to infection due to their immunocompromised state, and infection has been the second most common cause of mortality. Regular visits to the dialysis centre could increase the risk of SARS-CoV-2 infection due to limited capacity for air ventilation, close proximity and limited ability to physically distance.3 In Japan, 5471 dialysis patients were infected with SARS-CoV-2, and 519 died, accounting for 9.5% of mortality, as of 18 March 2022.4 The COVID-19 mortality in dialysis patients was higher than in the general population in Japan (0.44% as of 24 March 2022). Thus, preventative measures for the SARS-CoV-2 outbreak should be taken for dialysis patients.

    SARS-CoV-2 vaccination is a crucial element for infection control; however, the immune response to vaccination in dialysis patients was reported to be moderate to less than healthy adults.5 Significant decreases in the titre of anti-spike protein and neutralising antibodies of SARS-CoV-2 were observed in dialysis patients compared with healthy individuals.6–9 However, few studies on humoral response in immunised dialysis patients compared with the well-matched control group. Age, sex and the postvaccination period were reported to be dependent variables of anti-SARS-CoV-2 antibody titres.10 11 We conducted a prospective cohort study measuring SARS-CoV-2 antibodies in Fukushima Prefecture, Japan, since September 2021.12–14 We present the preliminary results of the humoral response in dialysis patients, along with a comparison with volunteer residents obtained by coarsened exact matching (CEM).

    Methods

    Study design and population

    This study was part of prospective cohort study. The public health office of Soma City (Fukushima Prefecture, Japan) broadly informed the residents of this study to understand their immunisation status as an infection control measurement. Five hundred residents voluntarily participated in the study. Sixty-five patients treated with haemodialysis in a hospital in Soma were also recruited in this study. All dialysis patients were outpatients receiving treatment at a hospital-associated clinic. All participants received a survey asking their age, sex, dates of vaccination with SARS-CoV-2, adverse reaction after vaccination, prescribed medication and history of the disease. The inclusion criteria for this study were the completion of the primary administration of the SARS-CoV-2 vaccine.

    Serological assay

    IgG antibody levels against the SARS-CoV-2 spike protein (S1) and neutralising activity were measured as secondary immune status outcome after second dose vaccination. IgG antibody titres against the SARS-CoV-2 N-protein were used to determine the previous status of COVID-19 infection. Collection of blood samples from all the participants was performed between 14 September and 25 September 2021. After serum isolation at blood collection sites, all frozen serum (−20°C) was shipped and evaluated in a central laboratory at the University of Tokyo.

    All serological assays were performed using the CLIA assay with iFlash 3000 (YHLO Biotech, Shenzhen, China) and iFlash-2019-nCoV series (YHLO Biotech, Shenzhen, China) as reagents. The measurement was performed according to the manufacturer’s instructions between 22 September 2021 and 28 October 2021. The validation process for quality control was conducted daily before measurement. The cut-off values of the anti-S1 and N antibodies and the neutralising activity were 10 AU/mL, which were the official cut-off values of the manufacturer. For neutralising activity, AU/mL×2.4 was used to convert to International Units (IU/mL). For IgG, AU/mL×1.0 was used to convert to binding antibody units (BAU/mL). The neutralising activity was set to 500 AU/mL if the activity was above 500 AU/mL due to the upper limit of the measurement. The results of similar antibody tests performed in this region can be found elsewhere.15–17

    Statistical analysis

    The CEM method was used to balance sex, age and days from second dose between dialysis and control groups.18 CEM was performed using the MatchIt package.19 Sex, age and days passed since the second dose were binned by Sturge’s method if the variable were continuous. Thirteen subclasses were obtained with both haemodialysis patients and healthy controls. Weights were assigned to each subclass of haemodialysis patients or healthy controls to ensure the same ratio of haemodialysis patients and healthy controls is maintained within each subclass to the overall matched cohort. These weights were also applied when performing linear regression. The standardised mean differences were less than 0.1 on all matched variables. We compared the characteristics of the haemodynamic patients (dialysis group) with the residents of Soma (control group). The two-group comparison was performed with the Mann-Whitney U and Fisher’s exact tests for continuous and categorical variables, respectively. The missing data were excluded from the individual analysis. Multivariable linear regression models were employed to predict log 10 of anti-SARS-CoV-2 S1 IgG and neutralising antibodies with participant characteristics of the participant group, such as sex, age and days between blood collection and second vaccination for the matched cohort. Linearity and heteroscedasticity were confirmed by plotting the residual against the fitted values. Normality on residuals were confirmed by QQ plot. Cook’s distance was less than 0.5 for all points. All analyses were performed using STATA IC (V.15) except for the CEM obtained by R package MatchIt package (V.4.3.2) of R (V.4.1.1).20 Violin and dot plots were constructed using the R package ggplot2 (V.3.3.2). Statistical significance was considered if the two-sided p values were less than 0.05.

    Patient and public involvement

    Patients or the public were not involved in the design, conduct, reporting or dissemination plans of our research.

    Results

    A total of 65 patients receiving haemodialysis and 500 residents were included in this study (table 1) (online supplemental table S1 for missing data). Although all participants in this study received two doses of vaccination (most patients received BNT162b2), no participants received third doses at blood collection.

    View this table:
    Table 1

    Participant characteristics

    In the entire cohort, dialysis patients were older (median age 69 and 47 years in the dialysis and control groups, respectively) and had a lower proportion of females (30.8% and 51.4%) when compared with controls. The time between the second vaccination and the blood collection for antibody measurement overlapped between dialysis patients and the control (105 and 117 days). The dialysis group exhibited a lower proportion of postvaccination adverse events of pain, malaise, fever ≥37.5℃ when compared with controls (table 2).

    View this table:
    Table 2

    Postvaccination adverse events

    After matching the CME for age, sex and time after the second administration of primary vaccination, we obtained 49 dialysis patients and 89 participants for further analysis (table 1 and figure 1). In the matched cohort, significantly higher proportions of hypertension, diabetes and cardiovascular disease were observed in the dialysis group compared with the control (p<0.001, <0.001 and<0.01). The dialysis group exhibited a significantly lower proportion of postvaccination adverse events of pain, malaise compared with the control (p<0.001 and <0.01)

    Figure 1
    Figure 1

    Distribution of age, sex and days postprimary vaccination in the matched cohort. Days postsecond vaccination (x axis) and age (y axis) are shown.

    Titres of SARS-CoV-2 antibodies

    None and two study participants showed the SARS-CoV-2 N-IgG antibody above the cut-off value in the dialysis and control groups, respectively. In the entire cohort, the significantly lower titres of SARS-CoV-2 S1-IgG were observed in dialysis patients compared with the control (median (range); 168.35 (4.48–1074.29) AU/mL and 286.66 (4.72–3556.17) AU/mL in dialysis and control groups, respectively, p<0.001) (figure 2). The levels of neutralising antibodies in dialysis patients were also significantly lower than those of the control (36.94 (2.94–36.94) AU/mL and 79.97 (0.00–2826.06) AU/mL, p<0.001).

    Figure 2
    Figure 2

    Histograms of SARS-CoV-2 antibody titres. The violin and dot plots of anti-SARS-CoV-2 S1 IgG titres (A and C for the overall and matched cohorts) and the neutralising antibodies (B and D for overall and matched cohorts) are shown. Solid and dashed lines in the violin plot indicate median and the IQR, respectively.

    After CME matching, significant differences in the titres of both anti-SARS-CoV-2 S1 IgG and neutralising antibodies were observed between the dialysis and control groups in the matched cohort (figure 2); anti-SARS-CoV-2 S1 IgG: 168.35 (4.48–1074.29) AU/mL and 269.81 (4.72–945.96) AU/mL in dialysis and control groups, p=0.02, neutralising antibodies: 35.77 (2.94–826.06) AU/mL and 62.22 (0.00–535.57) AU/mL, p=0.007, respectively). Participants with SARS-CoV-2 N-IgG antibody above the cut-off value were not included in the matched cohort of the dialysis and control groups.

    Predictors of anti-SARS-CoV-2 antibodies in the matched cohort

    Multivariate linear regression was performed to predict the log10 of SARS-CoV-2 antibody titres with the participant group, sex, age and duration of postvaccination using the matched cohort. In the models for both anti-SARS-CoV-2 S1 IgG and neutralising antibodies, dialysis and age were identified as independent predictors (a model for the log10 SARS-CoV-2 S1 IgG titre: p<0.05 and <0.001 for the dialysis group and age, respectively, a model for the Log10 neutralising antibodies titre: p<0.01 and <0.001 for the dialysis group and age) (table 3). The dialysis group showed negative values of β coefficients in both two models (β coefficient (95% CI): −0.187 (–0.334 to –0.039) and −0.237 (−0.400 to −0.075) for the models of Log10 SARS-CoV-2 S1 IgG and neutralising antibodies titres, respectively).

    View this table:
    Table 3

    Multiple linear regression to predict antibody titres in matched cohorts

    Variables to predict the log10 titres of anti-SARS-CoV-2 S1 IgG and neutralising antibodie are shown by multiple linear regression models. The anti-SARS-CoV-2 S1 IgG models and neutralising antibodies exhibited a weak fit of 0.258 (p<0.001) and 0.291 (p<0.001) for adjusted R2 values, respectively. When analysing the neutralising antibody titre of log10, a participant in the control group was excluded because he had a neutralising antibody of 0. The day range between the first and second vaccination was not included in the regression variable, since most participants in both the matched cohort of dialysis patients and the control group had 21 days between the first and second vaccination, and the variation in values was small.

    Discussion

    In this study, we demonstrated that patients undergoing haemodialysis had significantly lower titres of anti-SARS-CoV-2 S1 IgG and neutralising antibodies after the vaccination after matching for age, sex and postvaccination duration. The findings suggest that haemodialysis patients should be carefully monitored for their immunisation status.

    Our findings showing significantly lower anti-SARS-CoV-2 antibody titres in dialysis patients were consistent with previous studies.9 We performed CME matching to correct the influence of age, sex and period after the completion of primary vaccination on anti-SARS-CoV-2 antibody titres. The dialysis showed a significant negative impact on antibody titres even after the matching. The weaker humoral response to SARS-CoV-2 vaccination and the higher mortality of COVID-19 in dialysis patients support the enhancement of the regimen of SARS-CoV-2 vaccination. To date, the public recommendation by the Centers for Disease Control and Prevention in the USA defines the primary series of vaccination and two boosters for moderately and severely immunosuppressed adults.21 In Japan, however, the Ministry of Health, Labour and Welfare kept the definition of a booster after the primary series of vaccination.22 Thus, it is necessary to review the vaccination regimen corresponding to the risk of severe COVID-19 in Japan. It is noteworthy that significant differences in the medical history of hypertension, diabetes and cardiovascular disease were observed between the matched cohorts in this study, which might be confounders of antibody titres.

    There are several limitations in this study. First, the small cohort size and a single institute study cause statistical underpower and unknown bias. Second, we evaluated the initial measurement of anti-SARS-CoV-2 antibodies as a preliminary study and did not assess longitudinal changes in antibody titres over time. The short range of postvaccination periods may miss statistical significance. Third, in this study, detailed characteristics of dialysis patients, such as duration of dialysis and epidemiology, were not found. Fourth, there might be a recall bias due to the survey asking for previous medical histories and medications of the participants. Fifth, there is heterogeneity in medical history in the control group, as we saw more than 10% prevalence of hypertension, hyperlipidaemia and diabetes. Sixth, there were no participants in the dialysis group who showed positive IgG antibody titres against the SARS-CoV-2 N protein; therefore, this study could not assess the correlation between SARS-CoV-2 antibody levels and actual infections/severity of the COVID-19 disease. Lastly, the absence of SARS-CoV-2 infection in these cohorts makes it impossible to discriminate the titres associated with the prevention of SARS-CoV-2 infection. More studies are warranted to assess the correlation between antibody titres and actual clinical outcomes, as reported in healthy adults.23 24

    Conclusions

    We observed significantly reduced anti-SARS-CoV-2 S1 antibody and neutralising antibodies in haemodialysis patients compared with cohorts matched for duration after vaccination. Patients receiving haemodialysis should be carefully monitored for immunological responses to vaccination and COVID-19 infection.

    Data availability statement

    All data relevant to the study are included in the article or uploaded as online supplemental information.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study was approved by the institutional review boards of Hirata Central Hospital (Fukushima Prefecture, Japan) (approval number: 2021-0611-1) and Fukushima Medical University (Fukushima Prefecture, Japan) (2021-116). Written consent was obtained from all study participants or their family agents when the cognitive function of the participants was significantly impaired. This study was conducted in accordance with Ethical Guidelines for Life Science and Medical Research Involving Human Subjects in Japan.

    Acknowledgments

    We would like to thank all the staff from Fukushima Medical University, Soma City office, and Soma Central Hospital, Soma General Hospital, who contributed significantly to the accomplishment of this research, especially, Ms. Yuka Harada, Ms. Serina Noji, Ms. Naomi Ito, Dr. Hidekiyo Tachiya, Mr. Kouki Nakatsuka, Ms. Miki Sato, Dr. Masahiko Sato, Mr. Naoharu Tadano Ms. Xujin Zhu and Ms. Tomoyo Nishimura.

    References

    1. ↵
      1. Razzaghi H,
      2. Wang Y,
      3. Lu H, et al
      . Estimated county-level prevalence of selected underlying medical conditions associated with increased risk for severe COVID-19 illness–United States, 2018. MMWR Morb Mortal Wkly Rep 2020;69:945–50.doi:10.15585/mmwr.mm6929a1pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/32701937
      OpenUrlCrossRefPubMed
    2. ↵
      1. Hoxha E,
      2. Suling A,
      3. Turner JE, et al
      . COVID-19 prevalence and mortality in chronic dialysis patients. Deutsches Ärzteblatt international 2021;118:195.doi:10.3238/arztebl.m2021.0160
      OpenUrl
    3. ↵
      1. Corbett RW,
      2. Blakey S,
      3. Nitsch D, et al
      . Epidemiology of COVID-19 in an urban dialysis center. J Am Soc Nephrol 2020;31:1815–23.doi:10.1681/ASN.2020040534pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/32561681
      OpenUrlAbstract/FREE Full Text
    4. ↵
      1. Therapy TJSfD
      . Number of dialysis patients infected with SARS-CoV-2 on March 18, 2022, 2022. Available: https://www.jsdt.or.jp/info/3552.html [Accessed 08 May 2022].
    5. ↵
      1. Buti M,
      2. Viladomiu L,
      3. Jardi R, et al
      . Long-term immunogenicity and efficacy of hepatitis B vaccine in hemodialysis patients. Am J Nephrol 1992;12:144–7.doi:10.1159/000168436pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/1415374
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Davidovic T,
      2. Schimpf J,
      3. Abbassi-Nik A, et al
      . Waning humoral response 6 months after SARS-CoV-2 vaccination with the mRNA-BNT162b2 vaccine in hemodialysis patients: time for a boost. Kidney Int 2021;100:1334–5.doi:10.1016/j.kint.2021.10.006pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/34656642
      OpenUrlCrossRefPubMed
    7. ↵
      1. Shashar M,
      2. Nacasch N,
      3. Grupper A, et al
      . Humoral response to Pfizer BNT162b2 vaccine booster in maintenance hemodialysis patients. Am J Nephrol 2022;53:207–14.doi:10.1159/000521676pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/35172312
      OpenUrlPubMed
    8. ↵
      1. Jahn M,
      2. Korth J,
      3. Dorsch O, et al
      . Humoral response to SARS-CoV-2-Vaccination with BNT162b2 (Pfizer-BioNTech) in patients on hemodialysis. Vaccines 2021;9:360.doi:10.3390/vaccines9040360pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/33918085
      OpenUrlPubMed
    9. ↵
      1. Simon B,
      2. Rubey H,
      3. Treipl A, et al
      . Haemodialysis patients show a highly diminished antibody response after COVID-19 mRNA vaccination compared with healthy controls. Nephrol Dial Transplant 2021;36:1709–16.doi:10.1093/ndt/gfab179pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/33999200
      OpenUrlPubMed
    10. ↵
      1. Terpos E,
      2. Trougakos IP,
      3. Apostolakou F, et al
      . Age‐dependent and gender-dependent antibody responses against SARS-CoV-2 in health workers and octogenarians after vaccination with the BNT162b2 mRNA vaccine. Am J Hematol 2021;96:E257–9.doi:10.1002/ajh.26185pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/33837984
      OpenUrlCrossRefPubMed
    11. ↵
      1. Wang H,
      2. Yuan Y,
      3. Xiao M, et al
      . Dynamics of the SARS-CoV-2 antibody response up to 10 months after infection. Cell Mol Immunol 2021;18:1832–4.doi:10.1038/s41423-021-00708-6pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/34099890
      OpenUrlCrossRefPubMed
    12. ↵
      1. Kobashi Y,
      2. Shimazu Y,
      3. Kawamura T, et al
      . Factors associated with anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein antibody titer and neutralizing activity among healthcare workers following vaccination with the BNT162b2 vaccine. PLoS One 2022;17:e0269917.doi:10.1371/journal.pone.0269917pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/35687563
      OpenUrlPubMed
    13. ↵
      1. Kobashi Y,
      2. Shimazu Y,
      3. Sonoda Y, et al
      . Maturing of public-private-people partnership (4P): lessons from 4P for triple disaster and subsequently COVID-19 pandemic in Fukushima. J Glob Health 2022;12:03028.doi:10.7189/jogh.12.03028pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/35674274
      OpenUrlPubMed
    14. ↵
      1. Yoshida M,
      2. Kobashi Y,
      3. Kawamura T, et al
      . Factors associated with COVID-19 vaccine booster Hesitancy: a retrospective cohort study, Fukushima vaccination community survey. Vaccines 2022;10:515.doi:10.3390/vaccines10040515pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/35455264
      OpenUrlPubMed
    15. ↵
      1. Kobashi Y,
      2. Nishikawa Y,
      3. Kawamura T, et al
      . Seroprevalence of SARS-CoV-2 antibodies among hospital staff in rural central Fukushima, Japan: a historical cohort study. Int Immunopharmacol 2021;98:107884.doi:10.1016/j.intimp.2021.107884pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/34246041
      OpenUrlPubMed
    16. ↵
      1. Kobashi Y,
      2. Shimazu Y,
      3. Kawamura T, et al
      . Peak IgG antibody titers against SARS-CoV-2 spike protein following immunization with the Pfizer/BioNTech BNT162b2 vaccine. Fukushima J Med Sci 2022;68:67–70.doi:10.5387/fms.2021-28pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/35228456
      OpenUrlPubMed
    17. ↵
      1. Kobashi Y,
      2. Shimazu Y,
      3. Nishikawa Y, et al
      . The difference between IgM and IgG antibody prevalence in different serological assays for COVID-19; lessons from the examination of healthcare workers. Int Immunopharmacol 2021;92:107360.doi:10.1016/j.intimp.2020.107360pmid:http://www-ncbi-nlm-nih-gov.ezproxy.u-pec.fr/pubmed/33508702
      OpenUrlPubMed
    18. ↵
      1. Iacus SM,
      2. King G,
      3. Porro G
      . Causal inference without balance checking: Coarsened exact matching. Political Analysis 2012;20:1–24.doi:10.1093/pan/mpr013
      OpenUrlCrossRef
    19. ↵
      1. Stuart EA,
      2. King G,
      3. Imai K
      . MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Softw 2011.doi:10.18637/jss.v042.i08
    20. ↵
      1. Team RC
      . R: a language and environment for statistical computing; 2013.
    21. ↵
      1. CDC
      . COVID-19 vaccines for moderately or severely immunocompromised people, 2022. Available: https://www.cdc.gov/coronavirus/2019-ncov/vaccines/recommendations/immuno.html [Accessed 08 May 2022].
    22. ↵
      1. Ministry of Health LaWiJ
      . COVID-19 vaccine booster Shots (3rd dose), 2022. Available: https://www.mhlw.go.jp/stf/covid-19/booster.html [Accessed 08 May 2022].
    23. ↵
      1. Oxford University Press
      . Antibody level predicts the clinical course of breakthrough infection of COVID-19 caused by delta and omicron variants: a prospective cross-sectional study. In: Open forum infectious diseases, 2022.
    24. ↵
      1. Stærke NB,
      2. Reekie J,
      3. Nielsen H, et al
      . Levels of SARS-CoV-2 antibodies among fully-vaccinated individuals with delta or omicron variant breakthrough infections: a prospective cohort study. SSRN Journal 2022.doi:10.2139/ssrn.4066425

    Supplementary materials

    • Supplementary Data

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    Footnotes

    • Contributors All authors conceived and designed the study, and take responsibility for the integrity of the data and the accuracy of data analysis. TZ and MT wrote the manuscript. MT designed the research. TN, MK, CY, TK and YK performed the research. FO and YN analysed the data. KS, JK and RS played an important role in interpreting the results. All authors critically reviewed the manuscript for important intellectual content and provided final approval of the manuscript.

    • Funding This study was supported by Japan Agency for Medical Research and Development, Development of Vaccines for the Novel Coronavirus Disease, 21nf0101638h0001. This study was also supported by Medical & Biological Laboratories, Shenzhen YHLO Biotech, the distributor and manufacturer of the antibody measurement system (iFlash 3000).

    • Competing interests YK and MT received a research grant from Pfizer Health Research Foundation for research not associated with this work.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.