Feasibility and Acceptability of Wearable Sensors and ePROs in Early Phase Clinical Trials

In oncology, clinicians and researchers look at a person's clinical condition and functional status to understand how cancer and its treatment affect them. They use standardized rating scales to measure side effects from the disease or treatment. These scales grade how severe symptoms are based on factors such as the need for medical care, hospital stays, and whether a person can carry out daily activities.

Standard grading systems are commonly used in oncology to measure treatment- and disease-related side effects. These systems assign levels of severity based on clinical criteria, such as whether a person needs medical treatment, hospitalization, or has trouble with daily activities. These methods work well for measuring objective side effects, such as low blood cell counts or high liver enzyme levels. However, they are less accurate for symptoms that depend on a person's personal experience, such as fatigue, pain, or general discomfort. In these cases, there can be a gap between what people feel and what clinicians record. Because these symptoms depend on individual perception, they may be underreported or remembered inaccurately, which can make it harder for clinician reports to fully capture the person's symptom burden.

Most clinical trials, including large phase III randomized studies, use functional assessment scales to estimate how active participants are and how well they can tolerate treatment. Common tools include the Karnofsky Performance Status (KPS) and the Eastern Cooperative Oncology Group (ECOG) Performance Status. These scales are widely used in both research and clinical care to estimate prognosis, measure functional ability, and decide whether people are eligible for clinical trials. Although these scales are generally consistent, they do not always match closely with patient-reported outcomes or quality-of-life measures. Agreement between clinicians is usually good when people are grouped into broad categories (such as ECOG 0-2 versus 3-4). However, reliability decreases when clinicians try to distinguish between more specific categories, such as ECOG 0, 1, or 2.

Because of these limitations in measuring treatment tolerability, data often show differences in how well people tolerate treatment. This highlights the need for more objective and person-centered ways to measure functional status and symptoms. Wearable activity monitors may help address this issue by collecting continuous, real-time data about a person's physical activity and physiology. These devices may provide a clearer picture of how a person's function changes during treatment. When combined with electronic patient-reported outcomes (ePROs), wearable technology could improve symptom monitoring, help classify people more accurately, and support better treatment decisions in early-phase oncology trials.

Although earlier studies have shown that wearable devices can be used to monitor functional status in people with advanced gastrointestinal and lung cancers, their use in early-phase clinical trials is still limited. This study aims to address that gap by evaluating digital monitoring across several early-phase clinical trials, focusing on whether the approach is feasible rather than on disease-specific outcomes. By combining wearable activity data with ePROs, we hope to improve early detection of treatment-related side effects, refine dose-limiting toxicity (DLT) assessments, and support more accurate estimation of the maximum tolerated dose (MTD). Ultimately, this approach may help improve person-centered decision-making in early cancer drug development and guide future studies.