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University of Alberta researchers have developed a new statistical tool to evaluate the results of clinical trials, with the aim of allowing smaller trials to ask more complex research questions and get effective treatments to patients more quickly.
In their paper, the team reports on their new “Chauhan Weighted Trajectory Analysis,” which they developed to improve on the Kaplan-Meier estimator, the standard tool since 1959.
The Kaplan-Meier test limits researchers because it can only assess binary questions, such as whether patients survived or died on a treatment. It can’t include other factors such as adverse drug reactions or quality-of-life measures such as being able to walk or care for yourself. The new tool allows simultaneous evaluation and visualization of multiple outcomes in one graph.
“In general, diseases aren’t binary,” explains first author Karsh Chauhan, a fourth-year MD student at the U of A. “Now we can capture the severity of diseases — whether they make patients sick, whether they put them in hospital, whether they lead to death — and we can capture both the rise and the fall of how patients do on different treatments.”
John Mackey, a breast cancer medical oncologist and professor emeritus of oncology, added this tool allows researchers to do a smaller, less expensive, quicker trial with fewer patients, and get the overall benefit of a new treatment more rapidly out there in the world.
The two began working on the statistical tool three years ago when they were designing a clinical trial for a new device to prevent bedsores, which affect many patients with long-term illness. They wanted to look at how the severity of illness changed during treatment, but the Kaplan-Meier test wasn’t going to help.
“Dr. Mackey said to me, ‘If the tool doesn’t exist, then why don’t you build it yourself?’ That was very exciting,” says Chauhan, who also has a BSc in engineering physics, which he calls a degree in “problem-solving.”