Evolution of Research Using Patient-Reported Outcomes in Lung Cancer: A Q&A With Dr. Benjamin Movsas

Evolution of Research Using Patient-Reported Outcomes in Lung Cancer: A Q&A With Dr. Benjamin Movsas

Evolving Standards of Care
Jun 24, 2020
Posted: June 24, 2020

The IASLC Lung Cancer News spoke with Benjamin Movsas, MD, regarding the evolution of patient-reported outcomes (PROs) for lung cancer. Dr. Movsas is the co-chair of the Patient-Centered Outcomes Research Committee for the NRG Oncology Cooperative Group, chair of the radiation oncology department at the Henry Ford Cancer Institute in Michigan, and an expert in radiation oncology, lung and prostate cancers, and quality-of-life issues related to cancer. After 2 decades of involvement in PRO-based research, Dr. Movsas now sees quality of life as “a new vital sign” with a profound impact on clinical decisions.

Q: How can quality-of-life PROs be implemented into clinical trials in a standardized way?
A: When it comes to clinical trials incorporating quality of life, the key issue—just as it is with any other trial—is that its use needs to be hypothesis driven. Just as in comparing two treatments, the hypothesis regarding how quality of life differs between arms is the driving factor. That is important because the anticipated differences in quality of life between the arms of a trial will determine which validated instrument will best be able to show whether that difference is real using a “clinically meaningful change.” Then, of course, the appropriate statistics, design, and patient population need to be considered.

There are many validated PRO instruments. For example, the European Organisation for Research and Treatment of Cancer has many validated instruments, both generic and specific to lung cancer. There also is the validated Functional Assessment of Cancer Therapy (FACT) instrument. These instruments are available in multiple languages. These are great places to start, but it should not be one size fits all; investigators might want to pick a specific instrument based on their hypothesis. If we ask too much of our patients, we risk missing data, which is an extremely important issue. PRO data cannot be obtained retrospectively, so the design of the study is very important to ensure compliance.

For example, in a lung cancer study,1 we decided not to use the full FACT-Lung instrument, which is approximately 30 to 40 questions. Instead, we used a shorter validated subscale called the FACT-Trials Outcome Index (TOI); the FACT-TOI focuses on physical and functional well-being, as well as the lung cancer symptom subscale. It consists of approximately 20 questions and takes only approximately 5 minutes to complete, which helped with patient compliance. The FACT-TOI also has pre-determined values for defining clinically meaningful changes, so it provides researchers with pre-defined metrics to look for in the data.

Q: Can you explain the key role of PROs in lung cancer?
A: There are a number of research studies from the past 2 decades that show quality of life to be a very powerful prognostic factor. In one analysis in which I was involved, we looked at patients with stage III NSCLC who were receiving chemoradiation, and baseline quality of life was found to be the most important prognostic factor for survival.2 This remains true even 5 years after the study’s completion. Although we have traditional prognostic factors that we use all of the time in the clinic, it would be very helpful to add quality of life to that list because it will better guide our clinical decisions.

Indeed, multiple studies in various cancer settings have shown that PROs tend to be more sensitive than other outcome measures, such as clinical toxicity measures.3 So if a physician is trying to determine the benefit of a new technology, he or she may have the ability to detect more subtle but clinically meaningful differences using PROs. For example, in RTOG 0617, while this study was not randomized to compare 3-D conformal radiation (3-D CRT) versus intensity-modulated radiation therapy (IMRT), overall the patients were reasonably well balanced, and almost half were treated with each technique. Although there were not many differences between standard toxicity measures for the two techniques, the patients who received IMRT (vs. 3-D CRT) had a relative clinically meaningful improvement in quality of life 1 year post-therapy. It was pretty dramatic in that almost half of the patients who received 3-D CRT had a clinically meaningful decline, but only a quarter of patients who received IMRT showed the same decline.1
Now that we have this highly cost-effective real-time PRO approach that achieves a significant survival improvement, this justifies moving quality of life from research into the clinic.

What is most exciting to me is that we are starting to really get a sense that PROs can directly impact and potentially increase survival itself, which is truly amazing. Ethan Basch, MD, and colleagues performed a recent study of more than 700 patients with stage IV cancers of various kinds who were receiving chemotherapy. Patients in this study were randomly divided into two groups: one group reported symptoms using traditional in-clinic methods, and the other had real-time PRO reporting via a tablet or email communication with nurses. Results showed that patients in the real-time PRO group not only had better quality of life, which was expected, but those patients also had fewer emergency department visits (34% vs. 41% for traditional reporting). These patients were more compliant with chemotherapy and had increased survival rates compared to patients who were not reporting symptoms in real time. So not only did patients who participated in the real-time PRO receive more therapy with better quality of life, but they lived longer, and cost of care with respect to emergency department visits was decreased.4

It seems that the research on PROs has come full circle in that, in the past, we were excited about the idea that PROs helped us to prognosticate for survival; not only did that happen, but identifying and acting on PROs in real time actually helps us improve survival itself. A recent study in metastatic lung cancer showed the same results as the all-cancers study.5

If we had an expensive novel drug that showed the same increase in survival, we would probably be using it. Now that we have this highly cost-effective real-time PRO approach that achieves a significant survival improvement, this justifies moving quality of life from research into the clinic.

Q: Are there commercial products in the works for this?
A: A number of companies are working on web-based products that make it possible for patients to relay information to care providers in real time. Some of the products even allow for real-time back and forth with patients. For example, if the patient is having diarrhea, their web-based system can provide a recommendation immediately; if that does not work, the patient can feed this back to the care team in real time for other recommendations.

Q: Where do you see PRO research going in the future?
A: There appear to be some fascinating links between genetics and quality of life. The GENEQOL Consortium, for example, is conducting some really interesting studies evaluating genetics and fatigue, wellness, and happiness.6 Clearly, quality of life is influenced by our environment and life events, but it may also, at some level, be influenced by our underlying genetics. ✦

1. Movsas B, Hu C, Sloan J, et al. Quality of Life Analysis of a Radiation Dose-Escalation Study of Patients With Non-Small-Cell Lung Cancer: A Secondary Analysis of the Radiation Therapy Oncology Group 0617 Randomized Clinical Trial. JAMA Oncol. 2016;2(3):359-367.

2. Movsas B, Moughan J, Sarna L, et al. Quality of life supersedes the classic prognosticators for long-term survival in locally advanced non-small-cell lung cancer: an analysis of RTOG 9801. J Clin Oncol. 2009;27(34):5816-5822.

3. Siddiqui F, Liu AK, Watkins-Bruner D, Movsas B. Patient-reported outcomes and survivorship in radiation oncology: overcoming the cons. J Clin Oncol. 2014;32(26):2920-2927.

4. Basch E, Deal AM, Dueck AC, et al. Overall Survival Results of a Trial Assessing Patient-Reported Outcomes for Symptom Monitoring During Routine Cancer Treatment. JAMA. 2017;318(2):197-198.

5. Denis F, Basch E, Septans AL, et al. Two-Year Survival Comparing Web-Based Symptom Monitoring vs Routine Surveillance Following Treatment for Lung Cancer. JAMA. 2019;321(3): 306-307.

6. Sprangers MA, Sloan JA, Veenhoven R, et al. The establishment of the GENEQOL consortium to investigate the genetic disposition of patient-reported quality-of-life outcomes. Twin Res Hum Genet. 2009;12(3):301-311.