Rich Christie, MD, PhD, Chief Medical Officer,AiCure
Oncology clinical trials can be complex –patients participating in these studies are often subject to care plan regimens that require multiple medications with varying dosages and intricate protocols. While a number of cancer drugs are administered in the clinic via infusion by a clinical team member, many oncology programs also require patients to take companion medications at home, making confirmation of dosing adherence less straightforward and subject to error. Easy-to-use technologies, accessible through a smartphone or similar device, can help keep patients on track as well as identify patients that are most likely to comply to their care plan early on. Once the study is underway, these technologies can provide clinical trial site teams with valuable insights into patient health and behavior between clinical visits.
Benefits of an Optimized Patient Pool
Optimizing your patient pool for maximum medication adherence can have a significant impact on your clinical study. For example, patient pools with 80% or higher adherence result in:
●Less stress on sites: Higher performing patients require less follow-up and proactive engagement from site-based clinicians, allowing those clinicians to be more efficient.
●Smaller patient pools: Patients with typically low rates of adherence are also the patients most likely to drop out of studies. Using data from the lead-in period, you can avoid enrolling these patients to begin with, reducing the need to “over-enroll” as a contingency for dropouts.
●Faster trials: Studies that require fewer patients to produce statistically significant, quality data are usually faster studies.
●Better data: A higher rate of medication adherence leads to more complete and accurate data.
Ultimately, a more adherent patient pool means an improved understanding of the patient experience and how a medication will perform in the real-world – from practicalities of convenient dosing, to palatability, to a patient’s overall wellbeing. Technology that supports a patient’s engagement can play a critical role in gaining these insights.
How to Use a Lead-in Period to Select Participants in Your Oncology Study
In just one or two weeks, technology can be applied to analyze participant data and develop accurate predictive trends. When applied to dosing behavior, this information reveals which patients are most likely to maintain a high rate of medication adherence over the course of a study.
To validate this claim, we at AiCure selected a pool of patient data representing 4,182 patients, ranging widely in demographics, disease state and other factors.
We reviewed the first week and then, separately, the first two weeks of dosing data for these patients. We wanted to compare dosing behaviors in these short timeframes to dosing behaviors in full-length studies over time, looking for those patients who met or exceeded the industry gold standard of 80% medication adherence.
We found that the first week of dosing data accurately predicted beginning-to-end adherence at a rate of 72.2%. After two weeks, that accuracy rose to 76.6%. This means that roughly 75% of the time, the one- or two-week timeframes were able to accurately identify patients that would - and would not - meet or exceed that 80% rate of medication adherence.
With this in mind, sponsors can optimize patient pools by adding a one- or two-week lead-in period. For a short amount of time, patients can take part in this pre-trial placebo test period. The adherence shown during this period will help predict which patients will adhere at a high rate, and sponsors can use these insights to help inform decisions about which patients should be enrolled in the full study.
Leveraging Technology Reduce Patient and Site Burden during Oncology Trials
Oncology patients have a lot on their plates. Symptoms of their disease often leave them tired, not to mention anxious about their health and prognosis. They also, of course, have personal lives, including jobs, interests and responsibilities not related to their participation in a clinical trial. This can leave many oncology study patients feeling overwhelmed, and overwhelmed patients require more support from sites.
Employing remote technologies to collect data in between mandatory visits can go a long way in reducing the burden for patients and, through that, the burden on sites. Here are some examples:
● More focused in-clinic visits: Patients can spend time at the clinic getting necessary infusions or other therapies without spending time answering assessment questions. Site team members can access data from in-between visits, saving time and reducing the stress of the clinical trip. Sites can then focus on providing targeted support to patients who need it, helping to keep engagement high and reducing the risk of future issues.
● Shorter check-ins: Many high-performing patients won’t need a lot of facetime with clinical site team members. This allows sites to focus on other tasks and get more done, more efficiently.
● Informed patient data: Data collected between visits can help signal the presence of - or risk of - a problem. Adverse events are often under reported during oncology clinical trials because of a lack of tools to obtain regular communication with patients. Technology-enabled daily engagement allows researchers to have a more comprehensive view of patient well-being during their treatment protocols. This can help inform site team members of patient conditions so they can quickly step in, reach out to the patient, and solve issues before they exacerbate and jeopardize study data.
Oncology trials can be overwhelming for both patients and sites. Highly complicated medication regimens combining in-clinic treatments such as chemotherapy or immunotherapy with companion medications can be a lot to keep track of. Remote technology can be used to collect better data and help sites manage these studies more effectively.