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Developing and testing a Corona VaccinE tRiAL pLatform (COVERALL) to study Covid-19 vaccine response in immunocompromised patients


Kusejko, Katharina; Chammartin, Frédérique; Smith, Daniel; Odermatt, Marcel; Schuhmacher, Julian; Koller, Michael; Günthard, Huldrych F; Briel, Matthias; Bucher, Heiner C; Speich, Benjamin (2022). Developing and testing a Corona VaccinE tRiAL pLatform (COVERALL) to study Covid-19 vaccine response in immunocompromised patients. BMC Infectious Diseases, 22:654.

Abstract

BACKGROUND

The rapid course of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic calls for fast implementation of clinical trials to assess the effects of new treatment and prophylactic interventions. Building trial platforms embedded in existing data infrastructures is an ideal way to address such questions within well-defined subpopulations.

METHODS

We developed a trial platform building on the infrastructure of two established national cohort studies: the Swiss human immunodeficiency virus (HIV) Cohort Study (SHCS) and Swiss Transplant Cohort Study (STCS). In a pilot trial, termed Corona VaccinE tRiAL pLatform (COVERALL), we assessed the vaccine efficacy of the first two licensed SARS-CoV-2 vaccines in Switzerland and the functionality of the trial platform.

RESULTS

Using Research Electronic Data Capture (REDCap), we developed a trial platform integrating the infrastructure of the SHCS and STCS. An algorithm identifying eligible patients, as well as baseline data transfer ensured a fast inclusion procedure for eligible patients. We implemented convenient re-directions between the different data entry systems to ensure intuitive data entry for the participating study personnel. The trial platform, including a randomization algorithm ensuring balance among different subgroups, was continuously adapted to changing guidelines concerning vaccination policies. We were able to randomize and vaccinate the first trial participant the same day we received ethics approval. Time to enroll and randomize our target sample size of 380 patients was 22 days.

CONCLUSION

Taking the best of each system, we were able to flag eligible patients, transfer patient information automatically, randomize and enroll the patients in an easy workflow, decreasing the administrative burden usually associated with a trial of this size.

Abstract

BACKGROUND

The rapid course of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic calls for fast implementation of clinical trials to assess the effects of new treatment and prophylactic interventions. Building trial platforms embedded in existing data infrastructures is an ideal way to address such questions within well-defined subpopulations.

METHODS

We developed a trial platform building on the infrastructure of two established national cohort studies: the Swiss human immunodeficiency virus (HIV) Cohort Study (SHCS) and Swiss Transplant Cohort Study (STCS). In a pilot trial, termed Corona VaccinE tRiAL pLatform (COVERALL), we assessed the vaccine efficacy of the first two licensed SARS-CoV-2 vaccines in Switzerland and the functionality of the trial platform.

RESULTS

Using Research Electronic Data Capture (REDCap), we developed a trial platform integrating the infrastructure of the SHCS and STCS. An algorithm identifying eligible patients, as well as baseline data transfer ensured a fast inclusion procedure for eligible patients. We implemented convenient re-directions between the different data entry systems to ensure intuitive data entry for the participating study personnel. The trial platform, including a randomization algorithm ensuring balance among different subgroups, was continuously adapted to changing guidelines concerning vaccination policies. We were able to randomize and vaccinate the first trial participant the same day we received ethics approval. Time to enroll and randomize our target sample size of 380 patients was 22 days.

CONCLUSION

Taking the best of each system, we were able to flag eligible patients, transfer patient information automatically, randomize and enroll the patients in an easy workflow, decreasing the administrative burden usually associated with a trial of this size.

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Additional indexing

Contributors:Swiss HIV Cohort Study, Swiss Transplant Cohort Study
Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Medical Virology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Oncology and Hematology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Pneumology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Infectious Diseases
04 Faculty of Medicine > University Hospital Zurich > Clinic for Cardiology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Infectious Diseases
Language:English
Date:28 July 2022
Deposited On:31 Oct 2022 09:45
Last Modified:27 Jun 2024 01:40
Publisher:BioMed Central
ISSN:1471-2334
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s12879-022-07621-x
PubMed ID:35902817
  • Content: Published Version
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)