PLOS Digital Health (Jan 2023)

Wearable sensor-based performance status assessment in cancer: A pilot multicenter study from the Alliance for Clinical Trials in Oncology (A19_Pilot2)

  • William A. Wood,
  • Deepika Dilip,
  • Andriy Derkach,
  • Natalie S. Grover,
  • Olivier Elemento,
  • Ross Levine,
  • Gita Thanarajasingam,
  • John A. Batsis,
  • Charlotte Bailey,
  • Arun Kannappan,
  • Steven M. Devine,
  • Andrew S. Artz,
  • Jennifer A. Ligibel,
  • Ethan Basch,
  • Erin Kent,
  • Jacob Glass

Journal volume & issue
Vol. 2, no. 1

Abstract

Read online

Clinical performance status is designed to be a measure of overall health, reflecting a patient’s physiological reserve and ability to tolerate various forms of therapy. Currently, it is measured by a combination of subjective clinician assessment and patient-reported exercise tolerance in the context of daily living activities. In this study, we assess the feasibility of combining objective data sources and patient-generated health data (PGHD) to improve the accuracy of performance status assessment during routine cancer care. Patients undergoing routine chemotherapy for solid tumors, routine chemotherapy for hematologic malignancies, or hematopoietic stem cell transplant (HCT) at one of four sites in a cancer clinical trials cooperative group were consented to a six-week prospective observational clinical trial (NCT02786628). Baseline data acquisition included cardiopulmonary exercise testing (CPET) and a six-minute walk test (6MWT). Weekly PGHD included patient-reported physical function and symptom burden. Continuous data capture included use of a Fitbit Charge HR (sensor). Baseline CPET and 6MWT could only be obtained in 68% of study patients, suggesting low feasibility during routine cancer treatment. In contrast, 84% of patients had usable fitness tracker data, 93% completed baseline patient-reported surveys, and overall, 73% of patients had overlapping sensor and survey data that could be used for modeling. A linear model with repeated measures was constructed to predict the patient-reported physical function. Sensor-derived daily activity, sensor-derived median heart rate, and patient-reported symptom burden emerged as strong predictors of physical function (marginal R2 0.429–0.433, conditional R2 0.816–0.822). Trial Registration: Clinicaltrials.gov IdNCT02786628. Author summary Performance status acquisition relies on clinician judgment though additional data sources could inform its assessment. Physical performance testing is safe in patients with cancer undergoing treatment, though the feasibility of obtaining cardiopulmonary exercise testing during routine care is unclear. Patient-generated health data acquisition during cancer treatment is feasible but the contribution of these data to understanding performance status is not known. In this multicenter observational study, we used fitness trackers in addition to validated survey instruments as a means of remotely and continuously monitoring patient physical function, a concept closely related to performance status. We found that this approach was more feasible than advanced physical performance testing during routine cancer care. Daily physical activity, heart rate, and patient-reported symptom burden provided meaningful information relevant to physical function. Prospective studies analyzing these data in the context of clinical endpoints are needed to determine whether this type of assessment could be used in place of traditional performance status assessment. Multicenter consortia could facilitate development of refined models in cancer patients and identify opportunities for interventions to improve clinical outcomes.