In April 2020, the Veracuity team developed a survey tool for the collection of data from hospitalized COVID19 patients. This initiative was implemented and widely distributed by the Alliance for Clinical Research Excellence and Safety (ACRES). At the recommendation of the Principal Deputy Commissioner of Food and Drugs, Amy P. Abernethy, M.D., Ph.D., Veracuity joined the COVID-19 Evidence Accelerator, organized by the Reagan-Udall Foundation for the FDA in collaboration with Friends of Cancer Research.
The scarcity of evidence and ambiguity concerning the spread of the coronavirus led our team at Veracuity to think about how we can contribute to improving the knowledge base about this new disease. We have been following the publications and the news as they come out, trying to reconcile all the conflicting information relating to the effectiveness of the therapeutic interventions used to treat COVID-19 patients. Overwhelming news coverage did not seem to help reduce ambiguity pertaining to risk factors and elucidate the true incidence, prevalence and narrow down treatment options.
This initiative is in response to the FDA guidance “Postmarketing Adverse Event Reporting for Medical Products and Dietary Supplements During a Pandemic” that was published on March 20, 2020. The survey tool that addresses the most pressing knowledge gaps through data collection at the point of care. We focus on the symptoms, interventions used in hospitalized patients, treatment outcomes, and adverse drug effects. We will collect data for every COVID-19 patient after the resolution of care (discharge from hospital or death), including retrospective data collection since the beginning of the pandemic for selected healthcare facilities.
To address uncertainties relating to changes in pathogenicity and virulence of the virus, its behavior in different populations, and the impact of timing of hospitalization on patient outcome, we included critical dates. Specifically, we are asking about the onset of symptoms, test date, and availability of test results, hospitalization date, and date of discharge from hospital or date of death. Precise and consistently recorded timelining enables calculation of critical time intervals and detection of shortening or prolongation of these timelines under different conditions.
The condition and comorbidities of patients developing severe disease and dying from COVID-19 have been widely discussed in the media and the scientific press. To bring more clarity into the matter, we incorporated two standardly used scoring scales to ensure accurate and consistent information comparable across multiple facilities, Charlson Comorbidity Index and SOFA score. Sequential Organ Failure Assessment (SOFA) Score on admission describes the state of the patient’s condition. The SOFA score is a significant predictor of patient outcome. Charlson comorbidity index measures the impact of underlying illnesses on the patient’s expected lifespan. Charlson Comorbidity Index helps compare underlying diseases accurately and consistently across facilities. Moreover, it enables the calculation of the expected lifespan and to estimate life-years lost due to COVID-19 with greater accuracy. We also included risk factors associated explicitly with COVID-19, such as obesity, hypertension, COPD, asthma, and smoking. The severity of the disease is measured by the utilization of specific interventions, such as high-flow oxygen, mechanical ventilation, and extracorporeal membrane oxygenation (ECMO).
Many unknowns persist regarding the impact of medications used to treat underlying conditions. To answer the most pressing questions relating to the safety and efficacy of treatment interventions, we ask about symptomatic treatment as well as antivirals and immunomodulators used off-label.
These innovative and sometimes unproven therapeutic approaches may or may not provide the expected benefit to COVID-19 patients. Because of the scarcity of evidence, aggregate data describing the experience of other physicians with experimental therapies of COVID-19 patients may be a valuable source of insight into empirical experiences. For the sake of patient safety, it is essential to understand the harmful effects of drugs as early as possible.
We are aware of the limitations of real-world data compared to randomized controlled trials. Real-world data can support a variety of study designs, including large simple trials, pragmatic trials, and observational studies. Wide-sweeping tools such as the one we developed are also useful to generate hypotheses and detect specific safety signals. We believe in transparency and intend to share the data widely across the scientific community. Insights in the forms of interactive visuals will be available on our website as well as from ACRES.
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