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Record W3197222415 · doi:10.1186/s13063-021-05664-0

A trial platform to assess approved SARS-CoV-2 vaccines in immunocompromised patients: first sub-protocol for a pilot trial comparing the mRNA vaccines Comirnaty® and COVID-19 mRNA Vaccine Moderna®

2021· article· en· W3197222415 on OpenAlexaff
Benjamin Speich, Frédérique Chammartin, Daniel C. Smith, Marcel Stoeckle, Patrizia Amico, Anna Eichenberger, Barbara Hasse, Macé M. Schuurmans, Thomas Müller, Michael Tamm, Michael Dickenmann, Irène A. Abela, Alexandra Trkola, Hans H. Hirsch, Oriol Manuel, Matthias Cavassini, Lars G. Hemkens, Matthias Briel, Nicolas J. Mueller, Andri Rauch, Huldrych F. Günthard, Michael Koller, Heiner C. Bucher, Katharina Kusejko

Bibliographic record

VenueTrials · 2021
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsMcMaster UniversityImpact
FundersUniversitätsspital ZürichSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversity of BernInselspital, Universitätsspital BernSwiss Transplant Cohort StudyUniversitätsspital BaselUniversität BaselNational Science Foundation
KeywordsMedicineClinical trialRandomized controlled trialPandemicCohortVaccine efficacyVaccinationVaccine trialProtocol (science)Coronavirus disease 2019 (COVID-19)Internal medicineImmunologyDiseaseAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Late 2019, a new highly contagious coronavirus SARS-CoV-2 has emerged in Wuhan, China, causing within 2 months a pandemic with the highest disease burden in elderly and people with pre-existing medical conditions. The pandemic has highlighted that new and more flexible clinical trial approaches, such as trial platforms, are needed to assess the efficacy and safety of interventions in a timely manner. The two existing Swiss cohorts of immunocompromised patients (i.e., Swiss HIV Cohort Study (SHCS) and Swiss Transplant Cohort Study (STCS)) are an ideal foundation to set-up a trial platform in Switzerland leveraging routinely collected data. Within a newly founded trial platform, we plan to assess the efficacy of the first two mRNA SARS-CoV-2 vaccines that reached market authorization in Switzerland in the frame of a pilot randomized controlled trial (RCT) while at the same time assessing the functionality of the trial platform. METHODS: We will conduct a multicenter randomized controlled, open-label, 2-arm sub-study pilot trial of a platform trial nested into two Swiss cohorts. Patients included in the SHCS or the STCS will be eligible for randomization to either receiving the mRNA vaccine Comirnaty® (Pfizer/BioNTech) or the COVID-19 mRNA Vaccine Moderna®. The primary clinical outcome will be change in pan-lg antibody response (pan-Ig anti-S1-RBD; baseline vs. 3 months after first vaccination; binary outcome, considering ≥ 0.8 units/ml as a positive antibody response). The pilot study will also enable us to assess endpoints related to trial conduct feasibility (i.e., duration of RCT set-up; time of patient recruitment; patient consent rate; proportion of missing data). Assuming vaccine reactivity of 90% in both vaccine groups, we power our trial, using a non-inferiority margin such that a 95% two-sided confidence interval excludes a difference in favor of the reference group of more than 10%. A sample size of 380 (190 in each treatment arm) is required for a statistical power of 90% and a type I error of 0.025. The study is funded by the Swiss National Science Foundation (National Research Program NRP 78, "COVID-19"). DISCUSSION: This study will provide crucial information about the efficacy and safety of the mRNA SARS-CoV-2 vaccines in HIV patients and organ transplant recipients. Furthermore, this project has the potential to pave the way for further platform trials in Switzerland. TRIAL REGISTRATION: ClinicalTrials.gov NCT04805125 . Registered on March 18, 2021.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.044
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.025
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0440.010

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.346
GPT teacher head0.469
Teacher spread0.124 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2021
Admission routes1
Has abstractyes

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