Promise of Wearable Physical Activity Monitors in Oncology Practice

The Future of Wearable Technologies and Remote Monitoring in Health Care

Mobile technology has become a ubiquitous part of everyday life and is changing the way we offer clinical care and perform clinical research. We have unprecedented access to data for one's self-care as well as for sharing with health care providers. Meeting the challenge posed by the influx of wearable device data requires a multidisciplinary team of researchers, clinicians, software developers, information technologists, and statisticians. Although the possibility of what can be achieved with the ever-evolving wearable technologies seems to be unlimited, regulatory agencies have provided a framework to establish standards for clinical applications, which will also affect research applications. Clinical programs and electronic medical records vendors should prepare to establish a framework to implement these technologies into clinicians' workflow and to allow feedback to measure the impact on clinical outcome. In this article, we discuss how a new brand of multidisciplinary care is evolving around mobile health devices and present a vision of up-and-coming technology in this space.

Obesity, Leptin and Breast Cancer: Epidemiological Evidence and Proposed Mechanisms

The prevalence of obesity has been steadily increasing over the past few decades in several developed and developing countries, with resultant hazardous health implications. Substantial epidemiological evidence has shown that excessive adiposity strongly influences risk, prognosis, and progression of various malignancies, including breast cancer. Indeed, it is now well recognized that obesity is a complex physiologic state associated with multiple molecular changes capable of modulating the behavior of breast tumor cells as well of the surrounding microenvironment. Particularly, insulin resistance, hyperactivation of insulin-like growth factor pathways, and increased levels of estrogen due to aromatization by the adipose tissue, inflammatory cytokines, and adipokines contribute to breast cancerogenesis. Among adipokines, leptin, whose circulating levels increase proportionally to total adipose tissue mass, has been identified as a key member of the molecular network in obesity. This review summarizes the current knowledge on the epidemiological link existing between obesity and breast cancer and outlines the molecular mechanisms underlying this connection. The multifaceted role of the obesity adipokine leptin in this respect is also discussed.

Feasibility of Wearable Physical Activity Monitors in Patients With Cancer

PURPOSE

The feasibility of using physical activity monitors (PAMs) to measure functional status in patients with cancer is unclear. We aimed to determine the feasibility of using PAMs to longitudinally assess physical activity and performance status (PS) in patients with cancer.

METHODS

Patients with cancer who had Eastern Cooperative Oncology Group (ECOG) PS of 0 to 2 and were receiving systemic therapy were enrolled in a prospective pilot trial of PAM use. Feasibility was defined as patients using the PAM for > 50% of the observation period. We correlated PAM-reported measures with scores from ECOG PS and quality-of-life tools (Functional Assessment of Cancer Therapy-General [FACT-G], Quick Inventory of Depressive Symptoms-Self-Rated 16 [QIDS-SR16], and Brief Fatigue Inventory [BFI]) using Pearson's correlation test. Patients were surveyed regarding their experience with PAMs at study completion.

RESULTS

In all, 24 patients were enrolled; mean age was 54 years, 16 (67%) were women, and 19 (79%) were white. Twenty-three patients (96%) met the primary end point of feasibility. The median duration of follow-up was 69 days. Mean PAM-measured steps for ECOG PS of 0, 1, and 2 were 5,911, 1,890, and 845 steps per day, respectively ( P = .002). Minimum steps per day correlated with BFI ( r = -0.53; P < .01), FACT-G ( r = 0.45; P = .02), and QIDS-SR16 ( r = -0.57; P < .01). Eighteen patients (75%) reported a positive experience with the PAM.

CONCLUSION

PAMs are a feasible tool for measuring long-term physical activity in patients with cancer who are receiving systemic therapy. PAM-derived measures correlated with clinician-assessed PS.

Is preoperative physical activity level of patients undergoing cancer surgery associated with postoperative outcomes? A systematic review and meta-analysis

BACKGROUND

There is uncertainty about the role of preoperative physical activity (PA) level and its influence on postoperative outcomes, especially for patients undergoing cancer surgery.

AIM

To investigate if the level of preoperative PA in patients undergoing cancer surgery is associated with postoperative complication rates, length of hospital stay (LOS) and quality of life (QOL).

METHODS

An electronic search was performed from inception to 26th November 2017 in MEDLINE, Embase, AMED and CINAHL. Studies investigating the association between objective or subjective level of PA and postoperative complication rates, LOS and QOL were included. Risk of bias was assessed using the Quality in Prognosis Studies (QUIPS) tool. When possible, summary odds ratios (OR) and 95% confidence intervals (CI) were calculated using random-effect models.

RESULTS

13 studies (5523 unique patients) were included. Overall, most studies were rated as having low or moderate risk of bias. Higher preoperative level of PA was not significantly associated with absence of postoperative complications (OR = 2.60; 95%CI = 0.59 to 11.37) but was significantly associated with shorter LOS (OR = 3.66; 95%CI = 1.38 to 9.6) and postoperative QOL (OR = 1.29; 95%CI = 1.11 to 1.49).

CONCLUSIONS

The available literature suggests higher levels of preoperative PA in patients undergoing cancer surgery may be associated with better postoperative outcomes, particularly shorter LOS and better QOL. There is a need for high-quality studies investigating the association between preoperative PA and postoperative outcomes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO 2017 CRD42017082334. Available from:http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42017082334.

Barriers to physical activity: a study of academic and community cancer survivors with pain

PURPOSE

Despite the numerous benefits of physical activity (PA) for patients with cancer, many cancer survivors report challenges to participating in PA. The objectives of this study were (1) to assess barriers to PA and (2) to examine participant characteristics associated with modifiable barriers to PA among cancer survivors with pain.

METHODS

We conducted a cross-sectional survey study at one academic medical center and 11 community hospitals. Participants completed the 12-item Physical Activity Barriers After Cancer (PABAC) instrument (Cronbach's alpha = 0.75). Multivariable regression models examined participant characteristics associated with PABAC scores with a higher score indicating more barriers to PA.

RESULTS

Among 662 survivors, 67% had moderate or severe pain (rating 4 or greater on a scale of 0 to 10). Seventy-five percent of survivors did not meet the American Cancer Society PA recommendations on average, and these individuals had higher mean PABAC scores (beta coefficient (β) = 2.02, 95% confidence interval (CI) 0.96-3.09, p < 0.001). In adjusted analyses, cancer survivors who were non-white (β = 1.55, 0.28-2.82, p = 0.02), treated at a community hospital (β = 1.07, 0.09-2.05, p = 0.03), had surgery (β = 1.69, 0.69-2.69, p = 0.001), or within 12 months of diagnosis (β = 1.15, 0.20-2.10, p = 0.02) reported greater barriers to PA.

CONCLUSIONS

The majority of cancer survivors with pain are not adequately participating in PA. Key demographic and clinical characteristics are associated with survivors' barriers.

IMPLICATIONS FOR CANCER SURVIVORS

Efforts to overcome specific barriers are needed to promote PA after a cancer diagnosis.

Wearable Devices in Clinical Trials: Hype and Hypothesis

The development of innovative wearable technologies has raised great interest in new means of data collection in healthcare and biopharmaceutical research and development. Multiple applications for wearables have been identified in a number of therapeutic areas; however, researchers face many challenges in the clinic, including scientific methodology as well as regulatory, legal, and operational hurdles. To facilitate further evaluation and adoption of these technologies, we highlight methodological and logistical considerations for implementation in clinical trials, including key elements of analytical and clinical validation in the specific context of use (COU). Additionally, we provide an assessment of the maturity of the field and successful examples of recent clinical experiments.

Free-Living Physical Activity Monitoring in Adult US Patients with Multiple Sclerosis Using a Consumer Wearable Device

Introduction

Wearable devices have been used to characterize physical activity in multiple sclerosis (MS). The objectives of this study were to advance the literature on the utility of free-living physical activity tracking from secondary analyses of a pilot study in MS patients.

Method

The original observational study was conducted in participants with MS at PatientsLikeMe (PatientsLikeMe (www.PatientsLikeMe.com), an online network of patients with chronic diseases. Participants completed a baseline self-assessment, and received a Fitbit One^TM wearable device with instructions to upload data. Eligible participants (1) self-reported MS, (2) logged on to the PatientsLikeMe website 90 days prior to enrollment, and (3) consented to participate electronically. Participants (1) < 18 years, (2) living outside the United States, and (3) requiring wheelchair assistance for most daily activities were excluded. The secondary analyses were limited to participants with complete data on MS type, disease duration, and Multiple Sclerosis Rating Scale (MSRS) and at least 7 days of wearable data. Step count was used as a measure of physical activity.

Results

The analysis cohort of 114 participants uploaded a mean of 20.1 days of wearable data over the 23-day study (87% adherence); participants averaged 4,393 steps per day. The mean age of participants was 52 years, predominantly female (75%), relapsing-remitting type (79%), with mean disease duration of 16 years. Mean MSRS score within 30-day of baseline was 32; 72% reported mild-moderate walking disability. The reliability of step count measured by intraclass correlation was 0.55 for a single day, ≥0.7 for 2-day average, and ≥0.9 for 7-day average. After controlling for covariates, self-reported disease severity (MSRS quartile) was an independent predictor of step count (p < 0.001). Least square means (LS means) for participants that were least disabled (lowest quartile) was 5,937 steps, which was significantly higher than participants in the second, third, and fourth quartiles (4,570, 3,490, and 3,272, respectively). Similarly, LS means of participants with no ambulatory disability (measured by MSRS walk component) was 6,931 steps, significantly higher than participants with greater disability (4,743, 4,394, 2,727 steps for symptomatic, mild, and moderate disability, respectively, p < 0.001).

Discussion

Using an interactive platform, this study captured free-living mobility data in MS patients. Important metrics such as the use of a minimum of 2-day estimates and self-reported disability were found to be robust indicators and correlates, respectively, of participant activity levels. Further triangulation of such metrics may reduce the burden on patients, clinicians, and researchers when monitoring clinical status.