Clinically vulnerable patients will send dried blood spots through the post so researchers can measure their antibody levels and predict who remains at highest risk of severe COVID-19. Current guidance for these patients—who include people with suppressed immune systems from conditions such as organ transplants, blood cancers, or autoimmune therapies—relies on broad risk categories that do not account for how well an individual actually responds to vaccination. Some patients mount strong antibody defences; others produce barely any. Without knowing which group a patient falls into, doctors cannot tailor advice on shielding, booster timing, or antiviral access. The STRAVINSKY study will first analyse existing data from thousands of patients to identify which disease groups consistently show poor antibody responses. Then it will follow 3,000 patients prospectively, correlating their post-vaccination antibody levels with actual COVID-19 outcomes through 2024. If serology proves predictive, the team aims to define specific antibody thresholds that flag highest risk. Success would allow the NHS and the Department of Health to replace blanket shielding advice with personalised, evidence-based guidance—telling a kidney transplant recipient, for example, whether their next booster can wait or needs to be brought forward. It would also help prioritise limited treatments such as monoclonal antibodies or antivirals for those who need them most.
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Background: Although the COVID-19 vaccination program has proved extraordinarily successful, clinically vulnerable (CV) patients remain at risk of SARS-CoV-2 infection, severe COVID-19 and death. Coordinating large (inter)national studies, we have previously identified patients who make sub-optimal immune responses to COVID-19 vaccines, and those at highest risk of severe COVID-19. Although the precise immune correlates of protection against severe COVID19 are not defined, recent emerging data in patient groups suggests that the serological response to vaccination is a critical determinant in COVID-19 outcomes. Disease cohorts may be particularly informative in defining correlates of protection, as vaccine immune responses are heterogeneous such that correlations of these with disease outcomes is possible. The challenge/aims: Previous government advice to CV patients has recommended shielding, and early, repeat COVID-19 vaccination. The provision of ongoing advice is challenging since robust, evidence describing COVID-19 outcomes following additional boosters, the emergence of omicron variants, and the deployment of bivalent vaccines is lacking. Furthermore, QCOVID (a population study of health care records) has identified additional risk factors that enhance COVID-19 risk, with uncertainty as to whether this relates to vaccine responsiveness. We aim to use SARS-CoV-2 antibody testing to quantify COVID-19 risk, enabling clinicians/DHSC to provide on-going targeted advice over the next two years. Methodology: We will conduct a) a retrospective meta-analysis of existing data with the aim of refining CV groups for future follow up; b) a prospective arm of 3000 CV patients. For the retrospective study, we will collate existing data from national studies, including a minimal dataset of key characteristics and vaccine responsiveness. A meta-analysis will refine those disease groups with reduced or heterogeneous antibody levels compared to healthy controls. Groups with antibody levels comparable to age- and sex-matched healthy controls will be excluded from the prospective study. A multicentre prospective, observational cohort study will assess the predictive value of post COVID-19 vaccine serology in CV patients, including disease groups with baseline low/no antibodies (predicted using existing data, QCOVID4, the report from the Independent Advisory Group for COVID-19 medicines and refined following our retrospective analysis). A healthy control group will be provided by the UKRI funded PITCH2 consortium. Serological responses to bivalent vaccines will be correlated with COVID-19 clinical outcomes after infection with omicron lineage and emerging variants. Participants will be remotely sampled (n=2,600) with dried blood spots posted to a central laboratory, facilitating the recruitment of participants with diverse ethnic and socio-economic status. Additional blood and nasal secretions will be collected in 400 participants for immune assessment should serology fail to predict clinical outcomes. Three follow up visits will capture COVID-19 vaccine responses through to 2024. Significant outputs: We will establish if antibody testing can identify CV individuals at greatest risk of severe COVID-19 infection, and if possible, define serological thresholds for COVID-19 risk. We will improve the understanding of COVID-19 risk in CV individuals to inform future clinical care and guidance.
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