Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Capturing Patients’ Real-World Experiences to Improve Cancer Research and Care

A Q&A with Grace Castillo-Soyao, founder and CEO of Self Care Catalysts;
Q: You are well known as a visionary in the field of Real World Experience-Evidence (RWEE). As the founder and CEO of Self Care Catalysts, headquartered in Toronto, how do you see RWEE evolving to favorably impact the field of oncology?
A: I started Self Care Catalysts with some very basic questions. Why is the patient at the farthest end of the care line, treated as simply the recipient of care? It’s a very industrial mindset, a bit like an assembly line; the patient as something to be acted upon. But patients are often experts at their own conditions, including the many kinds of cancer. Why are they not invited to become participants in their own care, in contributing their own experiences? Why are patient experiences not considered to be scientifically valid?
As noted physician Sir William Osler famously said, “It is much more important to know what sort of a patient has a disease than what sort of a disease a patient has.”
About 90% of disease management happens at home, but very little information has been gathered about what happens in between clinical visits, and how self care might impact outcomes. This knowledge gap between caring for and living with cancer is wide, yet patients’ experiences—such as the burden of their cancer, their treatments, side effects, and the impact on their sleep, diet, relationships, and work—are barely acknowledged, documented, or discussed with their clinical care team. It’s not because nobody cares; it’s because of a time barrier and an economic barrier. Physicians traditionally get paid for services that happen inside the clinic, not beyond it.
Oncology is one of the disease states for which treatment technologies have undergone significant growth and evolution. Recently, the U.S. Food and Drug Administration has been employing new approaches to expedite the drug development and approval process. These include an emphasis on understanding the “real world,” or what happens with patients outside of clinics and clinical trials.
Because of these changes, and the complexity of cancer management by patients themselves, clinical trials will increasingly need to employ new measures that account for patients’ day-to-day experiences with their disease and treatments. And, as more promising cancer drugs enter the oncology market, the need to collect real world patient experience evidence (RWEE) will become a cornerstone in patient care and treatment decisions.
This shift in oncology will be enabled by the use of digital tools that collect data in a more rigorous way. Such tools can now address long-standing doubts and concerns regarding the validity and subjectivity of data reported by patients. The same tools can also be applied to disease management, which we at Self Care Catalysts believe will dramatically improve clinical outcomes. Indeed, Ethan Basch, MD, MSc, an oncologist at the University of North Carolina and one of our advisors, recently demonstrated that enabling patients to report their symptoms in clinical cancer care improved outcomes dramatically.
For the medical and scientific community, I’m sure it’s comforting to see that collecting patient-reported outcomes in cancer actually provides a dramatic improvement to care! We expect to see that digital engagement has a dramatic effect in how well a patient’s disease is managed and the quality of outcomes that can be gained, and we’ll see it in ever more rigorous studies.
At Self Care Catalysts, we design and build tools to capture the true patient experience. Patient experience data from approximately 3,500 cancer patients who use our Health Storylines Real World Experience Evidence platform reveal that their most common concerns are related to psychosocial, mood, quality-of-life, disease, and treatment experiences. These factors are hardly captured in clinical, lab, and medical reports at all, and not accurately represented in validated quality-of-life surveys.
RWEE combined with traditional clinical, medical, and even genomics data will bring quality of life realities to oncology, and it will advance many aspects of research and care, including drug development, clinical trials, and commercialization. Most importantly, RWEE will improve how cancer patients are involved in their own care, leading to big improvements in outcomes.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Patient-Reported Outcomes Could Transform Cancer Care

A Q&A with Jared Adams MD, PhD, Chief Science Officer at Self Care Catalysts;
Q: Patient-reported outcomes (PROs) are health care outcomes, such as symptoms or quality of life, reported directly by a patient. In recent years, PROs have emerged as a potentially powerful new way to understand cancer outcomes. Could PROs lead to the next breakthrough in our understanding of cancer?
A: When biochemist and Nobel Prize winner Kary Mullis spoke to my undergraduate class some 20 years ago about his invention of the PCR method for genetic amplification, he put it in historical context by mentioning that every major clinical advance has been preceded by a breakthrough in scientific investigative methods that allowed us to “see” in new ways. Dutch scientist Antonie Van Leeuwenhoek’s microscope allowed scientists to see cells for the first time, advancing us beyond the notion of cancer being caused by an abundance of black bile. The PCR method allowed us to see and manipulate cancer at the genetic level, leading us down the road to targeted therapies aimed at specific genetic mutations. Advances in computer hardware and modeling techniques have allowed us to map the genomes of cancers, moving us beyond a simplistic organ-based model of disease and setting up the possibility of new drug discoveries in silico. Observing and understanding how cancer cells interact with circulatory and immune systems led to VEGF inhibitors, PD-1/PD-L1 inhibitors, and the list goes on…
As our understanding of cancer grows to include larger and more complex systems, we should start to pay serious attention to how cancer interacts with systems outside the human body; its ecology, so to speak. In the last decade cancer researchers have drawn inspiration from studying how invasive species, such as the zebra mussel, take root and overwhelm the ecology of native systems. The word “ecology” comes from the Greek oikos, meaning “home” or “place to live,” and relates cancer to its organic and inorganic environment; not just within the host, but the environment of the host itself. We’ve known for some time how specific exposures to pathogens and substances can influence the rates of specific cancers and how diet, activity, and social network can in some cases influence cancer rates and outcomes.
However, through smartphones, wearables, and integrated sensors, tools to capture PROs are becoming more mainstream and sophisticated in their ability to record granular details about a person’s environment, routine, exposure, and more. Such advancements may be opening up a new era where these details become as important to prognosis and treatment decision making as clinical metrics like cancer stage and genetic profile. Just as we are entering a new era of cancer disease classification based not on primary location but on genetic profile and targeted therapy response, the next sea change may be classifying cancers by their relation and responsiveness to environmental variables and self-care behaviors. Human behavior is complex, but if privacy and regulatory considerations can be worked out and financial incentives aligned, the technology and tools exist to understand it and cancer in a way that’s only been hinted at in epidemiology and health services research up to now.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.