Daily Step Counts: A New Prognostic Factor in Locally Advanced Non-Small Cell Lung Cancer?

Ohri, Nitin; Halmos, Balázs; Bodner, William; Cheng, Haiying; Guha, Chandan; Kalnicki, Shalom; Garg, Madhur

doi:10.1016/j.ijrobp.2019.07.055

Cited by 50 publications

(34 citation statements)

References 23 publications

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“…39 Several studies have reported the association between physical inactivity and medical resources in patients with cancer. 36,40 As per the present study results, inactive patients required more extended hospital stays and had higher costs than active patients. Moreover, medical treatments were considerably different between active and inactive patients.…”

supporting

confidence: 78%

“…34 Specifically, in patients with advanced NSCLC, physical inactivity has been shown to affect prognosis negatively. 35,36 However, few studies have focused on physical inactivity in the early phase of the cancer trajectory. Our study indicated that physical inactivity during initial chemotherapy may deteriorate the overall survival and DFS of older patients with advanced NSCLC.…”

mentioning

confidence: 99%

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Impact of Physical Inactivity on the Risk of Disability and Hospitalization in Older Patients with Advanced Lung Cancer

Yonenaga¹,

Naito²,

Okayama³

et al. 2021

JMDH

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This prospective observational study aimed to explore the influence of physical inactivity during initial chemotherapy on the risk of disability and hospitalization in later life among older patients with advanced non-small-cell lung cancer (NSCLC). Patients and Methods: Patients aged 70 or above who were scheduled to receive first-line chemotherapy for newly diagnosed advanced NSCLC were recruited for the study. An electronic pedometer was used to measure daily steps; based on the change rate (cutoff: −12.5%) from pretreatment to 12 ± 4 weeks after enrolment, patients were classified as active or inactive. The Barthel Index estimated activities of daily living. We compared disabilityfree survival time, mean cumulative functions of hospital stays, and medical costs, between the active and inactive groups. Results: Among the 29 patients enrolled, 21 were evaluable. Compared with active patients (n = 11), inactive patients (n = 10) showed shorter disability-free survival (6.4 vs 19.9 months, p < 0.05) and tended to have longer hospital stays (23.7 vs 6.3 days/person) and higher inpatient care cost (¥1.6 vs ¥0.3 million/person [US$16,000 vs US$3000/person]) during the first year. Conclusion: Physical inactivity during initial chemotherapy may be a risk factor for developing disability and requiring hospitalization in later life for older patients with advanced NSCLC. Our findings may indicate the need for lifestyle interventions with multidisciplinary teams, which include physicians, nurses, and physiotherapists, for older patients with advanced lung cancer during an active cancer treatment. A large-sample-sized study is needed to validate our findings.

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supporting

confidence: 78%

mentioning

confidence: 99%

Impact of Physical Inactivity on the Risk of Disability and Hospitalization in Older Patients with Advanced Lung Cancer

Yonenaga¹,

Naito²,

Okayama³

et al. 2021

JMDH

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“…Studies have also shown that wearable device data relate to clinical outcomes. During outpatient chemoradiation therapy, lower levels of activity as measured with Garmin devices were associated with greater hospitalization risk, lower likelihood of completing treatment without delays, and shorter survival 27 , 28 . In a sample of 71 patients undergoing surgery for advanced abdominal cancer, lower Fitbit step counts during inpatient recovery were associated with greater risk of unplanned 30- and 60-day hospital readmission 29 .…”

Section: Consumer Wearable Devices In Oncology Researchmentioning

confidence: 98%

Harnessing consumer smartphone and wearable sensors for clinical cancer research

Low

2020

npj Digit. Med.

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As smartphones and consumer wearable devices become more ubiquitous, there is a growing opportunity to capture rich mobile sensor data continuously, passively, and in real-world settings with minimal burden. In the context of cancer, changes in these passively sensed digital biomarkers may reflect meaningful variation in functional status, symptom burden, quality of life, and risk for adverse clinical outcomes. These data could enable real-time remote monitoring of patients between clinical encounters and more proactive, comprehensive, and personalized care. Over the past few years, small studies across a variety of cancer populations support the feasibility and potential clinical value of mobile sensors in oncology. Barriers to implementing mobile sensing in clinical oncology care include the challenges of managing and making sense of continuous sensor data, patient engagement issues, difficulty integrating sensor data into existing electronic health systems and clinical workflows, and ethical and privacy concerns. Multidisciplinary collaboration is needed to develop mobile sensing frameworks that overcome these barriers and that can be implemented at large-scale for remote monitoring of deteriorating health during or after cancer treatment or for promotion and tailoring of lifestyle or symptom management interventions. Leveraging digital technology has the potential to enrich scientific understanding of how cancer and its treatment affect patient lives, to use this understanding to offer more timely and personalized support to patients, and to improve clinical oncology outcomes.

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“…Notably, it has been demonstrated that the acceptability of smartphones is superior to that of wrist‐based activity trackers 111 . Several observational studies have shown that higher levels of physical activity are associated with a reduced risk of all‐cause mortality and/or cancer‐specific mortality in patients with local or regional breast cancer, 111‐115 colorectal cancer, 115,116 locally advanced non–small cell lung cancer, 117 and other cancer types 118,119 . Higher levels of physical activity are also associated with a reduced risk of several of these cancers, whereas sedentary time is associated with higher risk, independent of physical activity 120 .…”

Section: Digital Phenotyping: Mobile Technology To Collect Pghdmentioning

confidence: 99%

Innovations in research and clinical care using patient‐generated health data

Jim

Hoogland

Brownstein

et al. 2020

CA A Cancer J Clinicians

109

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Patient-generated health data (PGHD), or health-related data gathered from patients to help address a health concern, are used increasingly in oncology to make regulatory decisions and evaluate quality of care. PGHD include self-reported health and treatment histories, patient-reported outcomes (PROs), and biometric sensor data. Advances in wireless technology, smartphones, and the Internet of Things have facilitated new ways to collect PGHD during clinic visits and in daily life. The goal of the current review was to provide an overview of the current clinical, regulatory, technological, and analytic landscape as it relates to PGHD in oncology research and care. The review begins with a rationale for PGHD as described by the US Food and Drug Administration, the Institute of Medicine, and other regulatory and scientific organizations. The evidence base for clinic-based and remote symptom monitoring using PGHD is described, with an emphasis on PROs. An overview is presented of current approaches to digital phenotyping or device-based, real-time assessment of biometric, behavioral, self-report, and performance data. Analytic opportunities regarding PGHD are envisioned in the context of big data and artificial intelligence in medicine. Finally, challenges and solutions for the integration of PGHD into clinical care are presented. The challenges include electronic medical record integration of PROs and biometric data, analysis of large and complex biometric data sets, and potential clinic workflow redesign. In addition, there is currently more limited evidence for the use of biometric data relative to PROs. Despite these challenges, the potential benefits of PGHD make them increasingly likely to be integrated into oncology research and clinical care.

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Daily Step Counts: A New Prognostic Factor in Locally Advanced Non-Small Cell Lung Cancer?

Cited by 50 publications

References 23 publications

Impact of Physical Inactivity on the Risk of Disability and Hospitalization in Older Patients with Advanced Lung Cancer

Impact of Physical Inactivity on the Risk of Disability and Hospitalization in Older Patients with Advanced Lung Cancer

Harnessing consumer smartphone and wearable sensors for clinical cancer research

Innovations in research and clinical care using patient‐generated health data

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