Lead Investigator: Andreas Artemiou, Cardiff University
Title of Proposal Research: Predicting outcomes (death, improvement, survival) of COVID-19 patients on Standard of Care (SoC) .
Vivli Data Request: 7325
Funding Source: None
Potential Conflicts of Interest: Dr. Crompton-Brown’s placement as a statistical analyst at UCB came to an end on the 27th of August 2021 and they no longer have any access to any UCB company-related matters or systems.
Summary of the Proposed Research:
As of 4th August 2021, the Office of National Statistics (ONS) estimates 496018 patients have been in UK hospitals with COVID-19 and 153734 have died. Whilst hospital rates and deaths are no longer peaking and have been blunted by the UK vaccination program it is important to understand the risk factors associated with poor COVID-19 outcomes.
This project will help further our understanding of COVID-19 and how we can begin to predict the outcome of a patient from their baseline hospital admission data in a clinical trial setting. This could be extended to the general hospitalized COVID-19 population helping to identify high risk patients as early as possible.
Statistical Analysis Plan:
Our main primary analysis will be based upon logistic regression models, in which we will model the probability of a patient’s outcome at the end of the study, based upon variables such as age, gender and weight.
Ordinal regression will be used to observe the impact of variables, such as age, on the overall outcome of the patient, based upon their ordinal clinical score.
Analysis of contingency tables will be used to understand the relationship between categorical variables, such as gender, and patient’s outcome from the study.
Location of studies will also be considered in the analyses.
Forest plots (lasso method) of risk factors will be used when considering a combination of factors.
It is assumed the selected studies are pre-vaccination due to the timing. However, this will be confirmed and re-considered if needed once data is received.
Missing data will be handled by using last observation carried forward (LOCF) for ordinal score data.
Multiplicity will not be adjusted for due to the exploratory nature of the study.
In the pooled dataset, variables will be created to reflect the different attributes of the studies including but not limiting to:
– Study ID
– Randomization ratio
– Level of blinding
– Study phase
– Time study began and ended (as standard of care changed over time with COVID-19). Exact time periods will be assessed once all studies have been received but is planned to be based on Quarter/Year of First Participant First Visit (FPFV) and Quarter/Year of Last Participant Last Visit (LPLV). Eg. FPFV=Q2,2020 and LPLV=Q4,2020.
Further exploratory analyses will take place if time allows. For example, improvement in biomarkers/laboratory results and or oxygenation levels may be explored.
Requested Studies:
A Randomized, Double-Blind, Placebo-Controlled, Multicenter Study to Evaluate the Safety and Efficacy of Tocilizumab in Patients With Severe COVID-19 Pneumonia
Data Contributor: Roche
Study ID: NCT04320615
Sponsor ID: WA42380
A Phase-II, Open-Label, Randomized, Multicenter Study to Investigate the Pharmacodynamics, Pharmacokinetics, Safety, and Efficacy of 8 mg/kg or 4mg/kg Intravenous Tocilizumab in Patients With Moderate to Severe COVID-19 Pneumonia
Data Contributor: Roche
Study ID: NCT04363736
Sponsor ID: CA42481
A Randomized, Double-Blind, Placebo-Controlled, Multicenter Study to Evaluate the Efficacy and Safety of Tocilizumab in Hospitalized Patients With COVID-19 Pneumonia
Data Contributor: Roche
Study ID: NCT04372186
Sponsor ID: ML42528
A Phase II, Randomized, Double-Blind, Placebo-Controlled, Multicenter Study to Evaluate the Safety and Efficacy of MSTT1041A or UTTR1147A in Patients With Severe COVID-19 Pneumonia
Data Contributor: Roche
Study ID: NCT04386616
Sponsor ID: GA42469
Treating COVID-19 With Hydroxychloroquine: A Multicenter Randomized, Double-blind, Placebo-controlled Clinical Trial in Hospitalized Adults
Data Contributor: NYU Grossman School of Medicine
Study ID: NCT04369742
Sponsor ID: 20-00463
Treatment in Patients With Suspected or Confirmed COVID-19 With Early Moderate or Severe Disease: A Randomized Clinical Trial
Data Contributor: University Medical Center, New Orleans
Study ID: NCT04344444
Sponsor ID: COVID 2020-001
A Phase III, Randomized, Double-Blind, Multicenter Study to Evaluate the Efficacy and Safety of Remdesivir Plus Tocilizumab Compared With Remdesivir Plus Placebo in Hospitalized Patients With Severe COVID-19 Pneumonia
Data Contributor: Roche
Study ID: NCT04409262
Sponsor ID: WA42511
Public Disclosures:
Crompton-Brown, E., Artemiou, A. Comparing classification algorithms in predicting COVID19 deaths. Zenodo. 2025. Doi : 10.5281/zenodo.14715032