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Abstract Purpose In the context of clinical research, there is an increasing need for new study designs that help to incorporate already available data. With the help of historical controls, the existing information can be utilized to support the new study design, but of course, inclusion also carries the risk of bias in the study results. Methods To combine historical and randomized controls we investigate the Fill-it-up-design, which in the first step checks the comparability of the historical and randomized controls performing an equivalence pre-test. If equivalence is confirmed, the historical control data will be included in the new RCT. If equivalence cannot be confirmed, the historical controls will not be considered at all and the randomization of the original study will be extended. We are investigating the performance of this study design in terms of type I error rate and power. Results We demonstrate how many patients need to be recruited in each of the two steps in the Fill-it-up-design and show that the family wise error rate of the design is kept at 5 $$\%$$ % . The maximum sample size of the Fill-it-up-design is larger than that of the single-stage design without historical controls and increases as the heterogeneity between the historical controls and the concurrent controls increases. Conclusion The two-stage Fill-it-up-design represents a frequentist method for including historical control data for various study designs. As the maximum sample size of the design is larger, a robust prior belief is essential for its use. The design should therefore be seen as a way out in exceptional situations where a hybrid design is considered necessary.

IntroductionA clear immune correlate of protection from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been defined. We explored antibody, B-cell, and T-cell responses to the third-dose vaccine and relationship to incident SARS-CoV-2 infection.MethodsAdults in a prospective cohort provided blood samples at day 0, day 14, and 10 months after the third-dose SARS-CoV-2 vaccine. Participants self-reported incident SARS-CoV-2 infection. Plasma anti–SARS-CoV-2 receptor-binding domain (RBD) and spike-subunit-1 and spike-subunit-2 antibodies were measured. A sub-study assessed SARS-CoV-2–specific plasma and memory B-cell and memory T-cell responses in peripheral blood mononuclear cells by enzyme-linked immunospot. Comparative analysis between participants who developed incident infection and uninfected participants utilised non-parametric t-tests, Kaplan–Meier survival analysis, and Cox proportional hazard ratios.ResultsOf the 132 participants, 47 (36%) reported incident SARS-CoV-2 infection at a median 16.5 (16.25–21) weeks after the third-dose vaccination. RBD titres and B-cell responses, but not T-cell responses, increased after the third-dose vaccine. Whereas no significant difference in day 14 antibody titres or T-cell responses was observed between participants with and without incident SARS-CoV-2 infection, RBD memory B-cell frequencies were significantly higher in those who did not develop infection [10.0% (4.5%–16.0%) versus 4.9% (1.6%–9.3%), p = 0.01]. RBD titres and memory B-cell frequencies remained significantly higher at 10 months than day 0 levels (p < 0.01).DiscussionRobust antibody and B-cell responses persisted at 10 months following the third-dose vaccination. Higher memory B-cell frequencies, rather than antibody titres or T-cell responses, predicted protection from subsequent infection, identifying memory B cells as a correlate of protection.

Objectives: To assess the safety and immunogenicity of a fourth vaccination (second booster) in individuals aged ≥75 years. Methods: Participants were randomized to BNT162b2 (Comirnaty, 30 µg) or messenger RNA (mRNA)-1273 (Spikevax, 100 µg). The primary end point was the rate of two-fold antibody titer increase 14 days after vaccination, targeting the receptor binding domain (RBD) region of wild-type SARS-CoV-2. The secondary end points included changes in neutralizing activity against wild-type and 25 variants. Safety was assessed by monitoring solicited adverse events (AEs) for 7 days. Results: A total of 269 participants (mean age 81 years, mRNA-1273 n = 135/BNT162b2 n = 134) were included. Two-fold anti-RBD immunoglobulin (Ig) G titer increase was achieved by 101 of 129 (78%) and 116 of 133 (87%) subjects in the BNT162b2 and the mRNA-1273 group, respectively (P = 0.054). A second booster of mRNA-1273 provided higher anti-RBD IgG geometric mean titer: 21.326 IU/mL (95% confidence interval: 18.235-24.940) vs BNT162b2: 15.181 IU/mL (95% confidence interval: 13.172-17.497). A higher neutralizing activity was noted for the mRNA-1273 group. The most frequent AE was pain at the injection site (51% in mRNA-1273 and 48% in BNT162b2). Participants in the mRNA-1273 group had less vaccine-related AEs (30% vs 39%). Conclusions: A second booster of either BNT162b2 or mRNA-1273 provided substantial IgG increase. Full-dose mRNA-1273 provided higher IgG levels and neutralizing capacity against SARS-CoV-2, with similar safety profile for subjects of advanced age.

Abstract Extracellular vesicles (EVs) accumulate during packed red blood cell (PRBC) storage. To date, the involvement of EVs in transfusion-related immunomodulation (TRIM) has not been prospectively evaluated in intensive care unit (ICU) patients. This was a prospective subanalysis of a recent observational feasibility study in postoperative ICU patients after: (1) open aortic surgery (Aorta), (2) bilateral lung transplantation (LuTx), and (3) other types of surgery (Comparison). Patient plasma was collected three times each before and after leukoreduced PRBC transfusion at 30-min intervals. The total number of EVs and EVs derived from erythrocytes (EryEVs), total platelets (total PEVs), activated platelets, granulocytes (GEVs), monocytes, and myeloid cells in PRBC samples and patient plasma were analyzed by flow cytometry. Statistical analysis was performed by Spearman’s correlation test, linear mixed models and pairwise comparisons by Wilcoxon matched-pairs test. Twenty-three patients (Aorta n = 5, LuTx n = 9, Comparison n = 9) were included in the final analysis. All EV subgroups analyzed were detectable in all PRBCs samples (n = 23), but concentrations did not correlate with storage time. Moreover, all EVs analyzed were detectable in all plasma samples (n = 138), and EV counts were consistent before transfusion. Concentrations of total EVs, EryEVs, total PEVs, and GEVs increased after transfusion compared with baseline in the entire cohort but not in specific study groups. Furthermore, the change in plasma EV counts (total EVs and EryEVs) after transfusion correlated with PRBC storage time in the entire cohort. Extracellular vesicles were detectable in all PRBC and plasma samples. Individual EV subtypes increased after transfusion in the entire cohort, and in part correlated with storage duration. Future clinical studies to investigate the role of EVs in TRIM are warranted and should anticipate a larger sample size. Trial registration: Clinicaltrials.gov: NCT03782623.

Summary: Platform trials bring the promise of making clinical research more efficient and more patient centric. While their use has become more widespread, including their prominent role during the COVID-19 pandemic response, broader adoption of platform trials has been limited by the lack of experience and tools to navigate the critical upfront planning required to launch such collaborative studies. The European Union-Patient-cEntric clinicAl tRial pLatform (EU-PEARL) initiative has produced new methodologies to expand the use of platform trials with an overarching infrastructure and services embedded into Integrated Research Platforms (IRPs), in collaboration with patient representatives and through consultation with U.S. Food and Drug Administration and European Medicines Agency stakeholders. In this narrative review, we discuss the outlook for platform trials in Europe, including challenges related to infrastructure, design, adaptations, data sharing and regulation. Documents derived from the EU-PEARL project, alongside a literature search including PubMed and relevant grey literature (e.g., guidance from regulatory agencies and health technology agencies) were used as sources for a multi-stage collaborative process through which the 10 more important points based on lessons drawn from the EU-PEARL project were developed and summarised as guidance for the setup of platform trials. We conclude that early involvement of critical stakeholder such as regulatory agencies or patients are critical steps in the implementation and later acceptance of platform trials. Addressing these gaps will be critical for attaining the full potential of platform trials for patients. Funding: Innovative Medicines Initiative 2 Joint Undertaking with support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.