At the recent 47th Annual Oncology Nursing Society (ONS) Congress in Anaheim, California, Dr. Nada Lukkahatai of Johns Hopkins School of Nursing gave a presentation about symptom science and her research regarding nonpharmacological interventions to reduce symptom burden. In this interview with Oncology Data Advisor, Dr. Lukkahatai further delves into this research and explains the future of personalized interventions and biomarkers studies for symptom management.
Oncology Data Advisor: Welcome to Oncology Data Advisor. Today I'm here with Dr. Nada Lukkahatai to discuss her recent ONS Congress presentation about symptom science. Thank you for joining us.
Nada Lukkahatai, PhD, MSN, RN, FAAN: I am Nada Lukkahatai. I am a faculty member at Johns Hopkins School of Nursing. My research area is in symptom science and symptom management.
What is symptom science? Basically, it's the underlying mechanism of how we can manage symptoms and how to understand the trajectories and developments of symptoms and how they have actually happened. Generally, cancer patients suffer from symptoms a lot, right? Before treatment, during treatment, after treatment, and for a very long time after—even if we cannot detect cancer anymore—there are just some leftover symptoms that they're still bothered by. As a nurse, that is my interest: how symptoms are developed, what causes symptoms, why they are activated at some point, and what makes some people experience symptoms a little longer than others. That is what my symptom science area is about.
Understanding symptoms does not make a lot of difference if we don't have a good way to manage them, right? I'm also looking at ways to manage them. With nursing, we mostly involve nonpharmacological intervention. Based on my clinical experience, I have observed that people respond to nonpharmacological interventions differently. Some people like music; some people like exercise; some people like this type of exercise but not that type of exercise. At the beginning, I realized, "Oh, okay, it might be preference." So, we tried to evaluate preference and see if it makes any difference. The effectiveness of the nonpharmacological intervention also varies from person to person. Even though you might like the same music, you would still benefit from it differently than someone else. The uniqueness of each individual. That is what got me interested in personalized intervention.
I actually started off by looking at a model for symptom management focusing on just one intervention. If we personalize it, would it actually help people by improving symptoms? We did that with exercise. As we know, many of us struggle with keeping up well with exercise. I looked at whether we can exercise at home and personalize it based on preference. Well, I learned along the way that's preference is not the only factor. There are some other things besides preference, like the availability of exercise at home. There are some goals in life that people have that motivate them to exercise. If they're doing it at home, it would be hard for clinicians or a researcher to monitor them, so I included some wearable devices to monitor them at home as well.
When we added in that, it's helped a little, but then when the COVID hit, everything changed with all these ideas becoming a central part of personalized intervention. Everything is turning online, and a lot of people come to us because they feel that online would be feasible, especially with cancer patients, because they are one of the populations that can have a serious consequence when they get COVID. Online, wearable devices and mobile applications become a central element of the intervention. Before that, we were actually doing a home visit. With COVID, we cannot really do a home visit. We turned that into a follow-up phone call at the beginning, because a lot of people don't have smartphones. Once we'd been dealing with COVID for a year, then I think smartphones became more of an important thing to have. People became more familiar with Zoom and everything else, so it's starting to come together unexpectedly. At the beginning, before COVID, we thought, "Home visits will be fine, and online will help us monitor." But then online follow-up became more important, because our participants basically had to stay at home in in the middle of the clinical trial. Our weekly follow-up has become something that the participants are looking forward to, because they have someone to reach out to them at home and talk to them.
I think that actually gets me moving forward a little more, adding more elements online, and including virtual training, virtual treatment, and virtual data collections to try to streamline the data collection and the way we personalize the intervention and recommendations on a weekly basis. We make sure that the participants feel like even though they see us on their phone screen, we're still keeping them engaged.
So that is a process with the personalized virtual program that we are doing. We've also learned along the way that that single intervention doesn't actually work as well because there are other symptoms that happen. We know that cancer patients don't have just one symptom. They may have one serious symptom, but they have multiple symptoms that happen, especially during their treatment and then after the treatment. I had one participant who said, "We get a lot of attention during the treatment, but then when the treatment is done, what's next?" The program is designed in a way to help them during the treatment by managing their symptoms, and hopefully they will transition all those techniques that they learn during treatment and implement them after it ends.
At this current stage, we're refining the process of personalizing. We are looking at other ways to personalize other than by preference. Of course, people have different preferences. Some people say, "You have to push me really hard for me to do it really well." Then some people say, "No, don't push me too hard. There's already a lot on my plate." That preference is still a part of it. But then we're also looking at physical performance and how much they can do, as well as other symptoms that they have—let's say, knee pain—and the other comorbidities that they have and see what other elements that we can add.
We're also adding in Chinese-based interventions like acupressure—both ear acupressure and body acupressure. We're looking at symptom data that we collect on a daily basis to see what types of symptom patients experience, and then we're making adjustments to our recommendations based on their symptom report.
That is the process that we are doing now, but moving forward, we hope to create a screening tool, in a way, that can help clinicians' decision making on how to personalize. It's not just preference. We usually will ask what patients like or don't like, but basically there needs to be a better way than that. We should actually take into consideration biomarkers and clinical conditions and then give a recommendation. It's personalized based on all of those elements, including preference and biomarkers. That is the aim that we want to develop and move forward to. We're learning, along the way, the key elements for when we personalize intervention to the participant. There are things that we learned and said, "Oops, we should have had that in our protocol," but we haven't.
Regarding the biomarker piece, we haven't completed our data collection yet, so we don't have a large data set to confirm our finding. At the moment, we're looking at some sort of oxidative stress biomarker and then looking at epigenetic age or biological age—looking at DNA methylation and signals of biomarkers that could potentially predict whether we can tailor our intervention based on the level of the biomarker. We are collecting the data at the moment, so we have to wait until all the samples are collected and then run the samples at the same time.
With the biomarkers, with the DNA methylation that we are looking at, we see some positive trends and signals, but it's inconclusive because the sample is so small. We see some signals, and it's promising, but we want to confirm that before jumping to a conclusion.
There is a lot of research out there talking about inflammation such as cytokines that play a key role. Everything is sort of like the feedback loop, with inflammation to explain every symptom. What is actually causing people to experience symptoms differently is something that still needs more study. That would be the part on oxidative stress that we are studying at the moment. We're following up some key biomarkers such as brain-derived neurotrophic factor, and then also heat shock protein. Those are the two main biomarkers that we are studying at moment, and then the DNA methylation is also something we hope to expand on.
These are still early-stage, but at the moment, we are looking at the changes in relation to the interventions that we implemented and the association of the biomarkers with the changes in symptoms. We want to see, with the 12-week program, why some people have improved symptoms, and some don't. Part of it is did they did the intervention and complied. If they have the same compliance and everything is same with staging, treatments, and everything else, they still benefit differently at the end of the intervention. These biomarkers will be something that to look at and understand the difference. Is it different at the molecular level? We aim to move forward and better personalize interventions for the patient. Hopefully if we personalize them differently, then perhaps at the end, everybody will achieve the same benefit from the intervention.
Oncology Data Advisor: Thank you so much for sharing all of this really exciting research with us.
About Dr. Lukkahatai
Nada Lukkahatai, PhD, MSN, RN, FAAN, is an Assistant Professor and Director of the MSN Research Honors Program at Johns Hopkins School of Nursing. Her research focuses on understanding the biological mechanisms in symptom development, including genomic and proteomic markers that can be used as interventional symptom management targets.
For More Information
Von Ah D & Lukkahatai N (2022). Symptom science: state-of-the-science. Presented at: 47th Annual ONS Congress.
Transcript edited for clarity. Any views expressed above are the speaker's own and do not necessarily reflect those of Oncology Data Advisor.