Insider Insights: Steven J. Ziemba, Marshfield Clinic Research Foundation
CWWeekly’s semi-monthly company profile feature, Insider Insights, interviews executives of companies and organizations in the clinical trials space. Staff Writer Ronald Rosenberg sat down with Steven J. Ziemba, Ph.D., associate director of the Marshfield Clinic Research Foundation.
Q: Among the new ways of thinking about research is to separate design modifications and focus more on how research designs are used in healthcare. Please explain.
A: One aspect, from my own experience working with various investigators, as well as what I have heard from others, is that clinical research studies haven’t necessarily reflected what you see in the real world. A good example would be a phase III oncology study. It typically has a hard time enrolling patients, and part of the difficulty is that the enrollment criteria are stringent and very narrow.
However, you are never going to find the perfect patient. Some of the new ways of thinking about research are how we can adapt clinical studies to reflect more real-world patients.
Halfway through a trial, an investigator might ask: Is this truly effective for this particular patient population? One aspect we are starting to see is the utilization of adaptive designs, whereby you have some flexibility both in the design and the statistics components to make study adjustments. This enables the study to continue in a successful way and answer the true questions that have developed during the course of the trial.
Another big area, which links research to patient care, is translational research. Essentially, it is how you take what you find from research, both basic science and clinical trials, and apply it to patient care. Then, using what was learned from patient care experiences, you go back and integrate that knowledge into what questions to ask and how to design studies. It is all part of comparative effectiveness research.
Q: The Patient-Centered Outcomes Research Initiative (PCORI) has pushed the importance of patient-focused studies, including patients in formulating research. What are some next steps toward implementing and expanding PCORI results?
A: The strength of PCORI lies in its inclusion of patients. Implementing the results is a big issue. Having Medicare consider PCORI research results in its determinations of treatment coverage certainly is one possible avenue. Similarly, private payers also can consider PCORI results. Such an approach is powerful in that it incorporates payers, which—along with patients and providers—is one of the three legs of healthcare. It includes the payer as an agent of change in accepting new approaches to patient care that have been vetted through a research methodology.
In addition, there are guidelines used in defining standard of care. Providers refer to the guidelines in their field of expertise, along with their own knowledge, experience and judgment, in making patient care decisions. Certainly, such guidelines already are based on best practices and research. However, the inclusion of PCORI results adds the dimension of the patient experience.
Finally, once you can demonstrate effectiveness, expanding the results is just like enlarging the PCORI methodology to other disciplines and other research focuses.
Q: How do you see using electronic medical records and Big Data for better scientific and patient-centered clinical trial designs and patient recruitment?
A: This is a big one. All of our data are going electronic in healthcare. The term Big Data is exactly that—an enormous quantity of information about patients. This is a rich source for identifying specific areas to explore from a scientific research perspective and for identifying more immediate results. You can develop research questions that have a direct impact on patient care. More immediate is the ability to address issues of quality assessment, for a single department, a healthcare organization or a health system.
That’s why Big Data has both a research and quality application. In the end, Big Data can be utilized to find where research needs to be focused and to better design studies that take into account both real-world and clinical trial patient aspects.
What big trend in Big Data can be incorporated into study design to make it more likely to succeed in answering the research question? Patient population study feasibility has always been an area of concern for research sites. Knowing what studies are viable for your participant population is important in determining the success of a study.
Another area is using Big Data to identify trends in patient care and outcomes. For example, a certain patient population prescribed a particular drug may demonstrate a lower incidence of a specific cancer diagnosis. This could lead to identifying a novel cancer treatment.
In another context, using Big Data to explore observationally or retrospectively means looking at certain disease types that may not necessarily lend themselves to traditional clinical trials. One example is rare diseases and the development of registries to study them. So when I say this is a big area, it’s because you can go in many directions.
Q: As traditional clinical trials expand in complexity, retrospective studies are needed to compare standard-of-care treatment, efficacy and cost. What else encourages use of these more complex studies?
A: We’re talking about comparative effectiveness at one end. It now is necessary not to just compare standard-of-care treatment, efficacy and cost. It also requires a look at health economics, now a factor in the comparison of an investigational treatment with standard-of-care. I’ve already started seeing health economics in studies—the investigational drug’s cost and usage are compared to the control.
Another aspect, if we are comparing standard-of-care treatments, is the recognition that a very effective treatment may already exist. Also part of retrospective studies is cost and its importance in deciding if the effective treatment will be accepted.
Realistically, education is needed for the end users (patients), the healthcare systems and the providers, who ultimately are utilizing those study results in the treatment of their patients. You could very well have two treatments for a diagnosis, both effective but one slightly less effective and available at a lower cost. Thus, price is a very big part of some patients’ treatment decisions. That’s where these comparative effectiveness studies will be useful.
As for the payer and provider organizations conducting these studies, there is much more of an emphasis on comparative effectiveness. What would be interesting would be to examine how organizations involved in measuring healthcare costs but which have not worked directly with pharmaceutical companies look at efficacy and pricing differently.
Q: With all the scientific and patient-focused changes in clinical trials over the past 10 years, what steps still are needed to effectively use what has been learned to improve patient recruitment and retention?
A: It is hard to determine the level of research acceptance among the public. Some clinical research participants would describe their experiences as necessary to promote the future of healthcare and science. Others may not have that level of acceptance or trust of clinical research.
Realistically, the biggest steps involve getting the word out to the public about the methods of clinical research, what trials are intended to do and how the advances in medicine today are due to years of research. By moving ahead we gain health benefits.
Some steps already have created greater awareness of clinical trials on a national level. Certainly the NIH and other nonprofit organizations working with the pharmaceutical industry could work together to promote the benefits of clinical research to the public.
Now that we are seeing this push on personal and precision medicine—such as President Obama’s recent plan for precision medicine—there is a new impetus for taking a major step to promote the importance of clinical research.
Email comments to Ronald at firstname.lastname@example.org. Follow @RonRCW
This article was reprinted from Volume 19, Issue 12, of CWWeekly, a leading clinical research industry newsletter providing expanded analysis on breaking news, study leads, trial results and more. Subscribe »