NIH Funds Statistician’s Work toward Pediatric Traumatic Brain Injury Data Bank

November 3, 2014

NIH Funds Statistician’s Work toward Pediatric Traumatic Brain Injury Data Bank

Eloise Kaizar, associate professor, statistics, received $148,621 from the National Institutes of Health for her project, "Statistical methods to support a model pediatric traumatic brain injury data bank.” Data repositories, or “banks,” are becoming increasingly common in medical research, but there are a number of important statistical issues that need to be addressed in their development so that analyses based on the data lead to meaningful conclusions

Kaizar’s project is funded by an award from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHHD).

“It's funded from an R03 grant program,” Kaizar said. “Not everyone is familiar with this type of grant, but they fund research projects that have a short duration and limited budget.

“I think this type of award is exciting because it allows the agency to do three important things: pilot very innovative proposals, multiply the value of already existing data through relatively inexpensive statistical re-analyses, and fund the development of new methodology that will be essential for future ground-breaking research.”

Kaizar’s project does all three – with a bottom line of $148,621 for the two-year project.

“In this project, we will develop novel models to statistically combine data from similar (but not identical) research studies, thus unlocking access to scientific discoveries that would otherwise remain out of reach.

“The potential for application is nearly limitless. But, the new statistical methods will be particularly helpful for overcoming the size and breadth limitations typically seen in research on difficult-to-study populations and conditions, such as pediatric traumatic brain injury (TBI).

“As you can imagine, recruiting families of children with new head injuries and keeping them enrolled for long-term and intensive follow-up is exceedingly difficult and costly. Thus, one of our target studies was made possible by focusing only on school-aged children 6-12 years old, whereas a later project recruited only preschool-aged children 3-6 years old.”

Kaizar explained that only by combining the studies via sound statistical models can reliable conclusions be made across the entire 3-12 age range – a period of profound developmental change for children.

“However, to complete such a synthesis we must overcome statistical modeling problems such as harmonizing different cognitive measurement scales used for the different age ranges without under-estimating the variability in cognition across the affected children,” Kaizar said.

As more than half a million American children visit the emergency room with a head injury each year, even this simple pilot project has the potential for broad impact.

But beyond this one question, the new statistical methodology will pave the way for the first-of-its-kind data bank comprised of completed designed research originating at Ohio’s three major children’s hospitals conducted by an internationally-recognized team of TBI researchers. This data bank would directly facilitate efficient TBI research on previously inaccessible questions.

“Even further, the statistical solutions we create to overcome practical problems, such as the inconsistent use of psychosocial measurements and scales could be easily adopted for data sharing in a wide range of similar fields,” Kaizar said.

In this age of ever-increasing data collection, new statistical methods for integrating research such as the ones this project will develop are in high demand for the pursuit of compelling and reliable science.

—Sandi Rutkowski

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