Although widely used and accepted in oncology practice to determine patient eligibility and physical tolerance
for clinical trial participation, performance status—the single most powerful prognostic and key clinical
decision-making tool across all solid tumor types—has one very significant limitation: its subjectivity. Because
of the association with survival, performance status scores are routinely assigned by the clinician as a
prediction of survival (prognostication). These subjectively determined scores are also used to evaluate fitness
capability for treatment, as a stratification and selection factor for clinical trial eligibility, to assess ability to
continue treatment on a clinical trial protocol, as a global indicator of quality of life, and to evaluate eligibility
and allocation of healthcare funds for hospice and home care services. We propose to examine the association
between continuously and objectively measured physical activity (PA) and clinician-assessed performance
status scores, overall patient survival, and clinical outcomes of significance (i.e., symptom burden, quality of
life measures, death, disease progression, treatment termination due to toxicity, hospitalizations and
emergency room visits, and referral for supportive/hospice care). This project will harness the technological
capacity of a system (CYCORE) that links home-based monitoring sensors to a cyber-infrastructure and can
send data in real time to the patient's healthcare team. To determine if objectively assessed PA levels are
associated with health care provider-assessed performance status scores and overall survival, we will recruit
75 patients for each of four performance status groups (levels 0-3). They will provide PA-related data for 7
days by wearing two PA devices—one commercially available and the second research-grade. We will
correlate those data with physician-assessed performance status scores and survival outcomes. To evaluate
the feasibility of long-term and continuous PA monitoring and the associations with clinical outcomes in
advanced cancer patients, we will recruit 100 patients who, for 6 months, will wear a commercially available PA
device and will provide PA- and self-reported data from their personal smartphone. We will correlate those data
to multiple clinical outcomes. Our long-term goal is to eliminate the subjectivity in performance status
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