Lindsay A. Renfro, Ph.D.

Why did you choose to study clinical and translational research?

When most people hear the term "statistics" or imagine a statistician at work, they might picture an individual working at a computer, performing statistical tests on data and reporting results in tables and graphs.

As a statistician myself, I am most interested in real-world clinical problems that happen to be incredibly statistically complex, or which require novel statistical solutions that do not currently exist.

Data is everywhere, and as clinical research advances, we are collecting more and more information from our patients to learn about their diseases. However, I believe that with the ability to gather vast patient data comes the responsibility to use it wisely.

We can do this by learning as much as possible about the individual features of the patients we see today, and subsequently assembling this knowledge to better treat similar individuals who are affected by the same diseases tomorrow.

The problem of how to integrate patient information in a way that motivates clinical practice is what motivates me to think beyond the usual responsibilities of a research statistician, and what led me to the field of translational research.

What type of research are you doing?

I am developing new designs for clinical trials, particularly within oncology, to make timelier use of the rich data we collect from our patients. In a standard clinical trial, patients are enrolled over a period of months or years and then followed for additional months or years, at which point a pre-planned statistical analysis establishes whether an experimental treatment is more effective than some alternative.

In this framework, unique patient features such as biomarkers or genetic mutations are generally analyzed only after this primary analysis is complete, when it may be learned that a subgroup of patients — such as those with a particular genetic feature — responded to the experimental treatment especially well, while other patients did not.

I believe that in many situations, a better approach to clinical trials in oncology can be taken. By actively analyzing individual patient data as it accumulates during a trial, we create an opportunity to use the unique information from patients who enroll early in the trial to better learn from — or better treat — patients who enroll later on in the same trial. This process also allows us to update our original research question to a new set of questions that we may learn midtrial are more critical to answer.

Then, instead of merely concluding from a trial whether an experimental treatment works, we can use readily available data to shift the course of a trial toward concluding for whom the experimental treatment works best.

Why Mayo Clinic?

Mayo Clinic is the perfect environment for a statistician to build a career addressing real-world clinical research problems with novel statistical methodologies. With all of the cutting-edge medical research happening at Mayo, there is a constant need for equally cutting-edge statistical science to bring research goals to fruition.

I began my Mayo Clinic career as a summer intern visiting the Rochester, Minnesota, campus during my Ph.D. program. The internship was intended to last for three months, but once I discovered the fascinating and challenging research problems of my group — led by Daniel J. Sargent, Ph.D. — and became invested in the progress we were making, I happily extended my internship to 13 months.

During that time, I also came to appreciate the excellent quality of life that Rochester has to offer, so accepting an offer to return to Mayo upon graduation was a very easy decision.

What are you looking forward to as a KL2 scholar?

My ultimate goal as a statistician is to understand the science of cancer as well as my collaborators working directly in oncology, so that I can contribute my statistical skillset in ways most likely to impact clinical practice. This is a lofty goal that necessitates broadening my knowledge base far beyond statistics.

The KL2 Program will provide this foundation, including intensive training and mentoring in clinical research methods and topics related to modern oncology and the conduct of clinical trials. The generous time and resources provided by the KL2 Program are critical for my work to have the desired impact on how we perform cancer clinical trials in the future.