Mobile Sensor Technologies to Assess General Symptomology of People With Cancer

Background:

A growing number of mobile health solutions are enabling the tracking, diagnosis, and management of various physiological processes and disease conditions, and many common devices such as smartphones (e.g., iPhone) have integrated robust sensors to collect and track this data.
The two most commonly used tools in oncology include the Eastern Cooperative Oncology Group Performance Status (ECOG PS) and Karnofsky Performance Status (KPS) scales that were invented more than 50 years ago.
Although standard performance status (PS) measurements are simple to implement in the clinic, they are retrospective, subject to bias and limitations including intra- or inter- observer variability, they are intermittent, providing a snapshot of the participants status at the time of assessment, and they are largely subjective, relying on physician judgement and participants ability to recall events and describe their symptoms. The inability to retrospectively verify or confirm the accuracy of PS assessment is another limitation.
The benefits to participant care of knowing the accurate PS are extensive, including making the right treatment decision based on the side effect profile, survival benefit and eligibility on clinical trials.
Biometric data can also play a role in empowering participants to become active participants in their own care, by providing them with quantitative feedback on activities of daily living and other functions.
There are some studies exploring the accuracy of available electronic activity monitoring (EAM) systems, but the available data on use of EAM systems in oncology participants is limited.
Continuous biometric data can provide actionable insights into fluctuations in not only the activity level of cancer participants, but also their cognitive function and mood throughout treatment cycles.
Given the current limitations in the overall clinical evaluation of cancer participants, the use of remote sensor technologies can provide an objective, frequent, and near-real time stream of data in a machine-readable format that is free of human bias and can greatly enhance the ability of both clinicians and participants to manage the complexities of cancer care.

Objective:

This study will evaluate the feasibility of collecting data to assess fatigue, reaction time, and cognitive functioning, in participants with cancer, using an Apple iPhone and Apple Watch in the clinic setting and with or without additional activity monitoring in the home setting.

Eligibility:

Inclusion criteria: Male or female subjects aged >= 18 years with a diagnosis of malignant tumors who are under active treatment for cancer.
Exclusion Criteria: Active central nervous system (CNS) metastases, known current alcohol or drug abuse, any psychiatric condition that would prohibit the understanding or rendering of informed consent.

Design:

This pilot study will be done in two arms (enrolled concurrently) with the goal of 60 evaluable participants across both arms (accrual ceiling will be set at 80).

Participants assigned to Arm 1 will have all assessments done in the clinic. A specially programmed iPhone, Apple Watch, an NIH iPad, and investigator conducted assessments will be used to collect data assessing participant fatigue, reaction time, and cognitive functioning. These data will be compared with data collected from questionnaires including: patient reported outcome (PRO)-CTCAE fatigue and mood grading, ECOG/KPS, Neuro-QOL Ability to Participate in Social Roles and Activities short form, the Delis-Kaplan Executive Functioning System, and The NIH Toolbox.

Arm 2 of this study will be a subset of enrolled participants who have a personally owned iPhone. Participants in Arm 2 will complete the same battery of assessments in the clinic as those in Arm 1, with additional continuous measurement of their activity recorded by an Apple Watch at home, between clinic visits. Participants in Arm 2 will have the option of having the apps designed for this study installed on their personally owned iPhones so they can complete the app assessments at home. The Apple Watch will be given to these participants (or they may use a personally owned Apple Watch) who will be trained by study staff on using the device for continuous monitoring. Participants who agree to have the study apps installed on their personally owned iPhone will be trained by study staff on the use of the apps.