An research published Tuesday in PLOS Medicine discovered that differences in how COVID-19 acts from person to person may contribute to the contradictory outcomes observed in clinical trials for antiviral medicines.
According to the researchers, this inconsistency is exacerbated by the fact that many coronavirus medication trials focus on enrolling critically sick patients in order to offer them with a possibly successful treatment.
As a result, they added, many of these trials may compare medication efficacy in patients with severe disease to non-treatment, or placebo, in those with lesser symptoms.
To address this issue, recruiting study participants shortly after symptom onset or after testing positive for the virus could make patient groups more similar, according to the researchers.
“At the early phase of the pandemic, physicians decided who needed to be treated and non-treated [based on] compassionate use programs, which is non-random,” study co-author Keisuke Ejima told UPI in an email.
“If so, we may not see the difference between treated and untreated individuals because those treated get better due to treatment and those untreated were not seriously sick from the beginning,” said Ejima, an assistant research scientist in biostatistics at Indiana University in Bloomington.
Drugs are typically evaluated in randomized controlled clinical trials in which at least two groups of similar participants are treated differently to determine which approach works best, researchers said.
However, treating all seriously ill patients with one treatment, and those with less severe symptoms with another, may produce varying results, according to the researchers.
Since the beginning of the pandemic, several treatments for COVID-19 have emerged from rapidly conducted clinical trials, including the antiviral drug remdesivir and monoclonal antibodies, which are essentially manmade immune cells.
Still, while these treatments have shown some benefit in those hospitalized with severe illness, none has proved to be a “cure” for the virus, Ejima and his colleagues said.
For this study, the researchers used a model that replicated the dynamics, or behavior, of the coronavirus after someone is infected.
They combined the model with clinical data to examine how viral load, or the amount of virus in a person’s throat, changes over time.
Significant differences appeared in the rate of viral load decline between patients, with some people experiencing more rapid drops than others, according to the researchers.
According to the researchers, this might explain why some study participants responded better to antiviral medications than others in particular studies.
To investigate this, the researchers replicated the results of randomised clinical trials for COVID-19 medicines that successfully block viral reproduction or spread within the human body.
Even if a medication decreased viral replication by 95%, the accompanying randomised clinical trial would need to enrol more than 13,000 people to get it, plus the same number of people given a placebo for comparison, according to the researchers, in order to discover statistically significant changes.
According to the experts, trials of this scale would be difficult to manage and costly.
When scientists changed the simulated randomised clinical trials such that individuals were treated within one day of the beginning of their symptoms, they only needed approximately 600 participants in each group.
This implies that randomised clinical trials for COVID-19 medicines might be enhanced by recruiting individuals as soon as symptoms arise, or by establishing participation criteria depending on the period since symptom start, according to the researchers.
“Studies employing randomization have gradually increased” over the course of the pandemic, Ejima said.
“However, most studies employing randomization recruit patients regardless of the time since symptom onset [and], from our quick survey, the average time from symptom onset to randomization was 7.2 days, which is too late,” he said.