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Pretreatment prognostication, on-treatment monitoring, and early detection of physiological symptoms are considerable challenges in cancer. We describe the feasibility of high-resolution wearable data (steps per day, walking speed) to longitudinally profile physiological trajectories extracted from Apple Health data in three patients with lung cancer from diagnosis through cancer treatment after obtaining informed consent. We used descriptive statistics to describe our approach of building longitudinal physiological profiles. The wearable data monitoring period ranged from 58 to 135 weeks, with between 34,319 and 103,535 distinct digital physiological measures collected during this period--the equivalent to 41 measures per day/patient. Longitudinal profiling revealed that wearable data accurately captured physiological changes linked with clinical events such as surgery and hospitalizations as well as initiation (and cessation) of systemic cancer treatment in all three patients. These findings suggest that wearable devices could play a critical role in the management of lung cancer, although larger studies are needed to confirm these preliminary observations and validate their generalizability. Wearable devices hold significant promise for the development of personalized "digital biomarkers," which may enhance risk stratification and management in oncology. [ABSTRACT FROM AUTHOR]

Background: Modifiable lifestyle-related factors heighten the risk and severity of coronavirus disease 2019 (COVID-19) in patients with cancer. Whether exercise lowers susceptibility or severity is not known. Methods: We identified 944 cancer patients from Memorial Sloan Kettering Cancer Center (mean age: 64; 85% female; 78% White) completing an exercise survey before receiving a confirmed positive or negative SARS-CoV-2 test. Exercise was defined as reporting moderate-intensity ≥5 days per week, ≥30 minutes/session or strenuous-intensity ≥3 days per week, ≥20 minutes/session. Multivariable logistic regression was used to determine the relationship between exercise and COVID-19 susceptibility and severity (i.e., composite of hospital admission or death events) with adjustment for clinical-epidemiologic covariates. Results: Twenty-four percent (230/944) of the overall cohort were diagnosed with COVID-19 and 35% (333/944) were exercisers. During a median follow-up of 10 months, 26% (156/611) of nonexercising patients were diagnosed with COVID-19 compared with 22% (74/333) of exercising patients. The adjusted OR for risk of COVID-19 was 0.65 [95% confidence interval (CI), 0.44-0.96, P = 0.03] for exercisers compared with nonexercisers. A total of 20% (47/230) of COVID-19 positive patients were hospitalized or died. No difference in the risk of severe COVID-19 as a function of exercise status was observed (P > 0.9). Conclusions: Exercise may reduce the risk of COVID-19 infection in patients with a history of cancer, but not its severity. Impact: This study provides the first data showing that exercise might lower the risk of COVID-19 in cancer patients, but further research is required. [ABSTRACT FROM AUTHOR]