A systematic review of randomized controlled trials (RCTs) of exercise interventions using digital activity trackers (E-DAT) in cancer patients.

Abstract

108 Background: Exercise ameliorates cancer and treatment-related toxicities but adherence to exercise is a barrier. Few studies in the general population suggest that E-DAT may improve exercise adherence. We conducted a systematic review to examine the effects of E-DAT on physical function, health-related quality of life (HRQOL), and serum inflammatory markers during and after cancer treatment. Methods: We used PubMed, Embase, and the Cochrane Library to identify RCTs of E-DAT in cancer patients aged ≥18 years published in English between 1/1/2008 and 7/27/2017. Two authors independently reviewed the titles of articles from the search (n = 160), removed duplicates (n = 49), and reviewed the remaining 111 articles for eligibility and substantive results. We excluded RCTs that used digital activity trackers solely for data collection. Results: Twelve RCTs met eligibility criteria, including 1,450 patients (mean age: 50-70 years) with the following cancers: breast (n = 5 RCTs), colon or breast (n = 2), prostate (n = 1), acute leukemia (n = 1) and various type (n = 3). Duration of E-DAT ranged from 4-24 weeks. Follow-up period was 4-24 weeks with retention of 54-95%. Half of the RCTs had E-DAT with in-person exercise training and the rest had self-directed training. The technology component of E-DAT included pedometers (n = 8); pedometers with smart phone application (n = 1), Wii-Fit (n = 1), or heart rate monitor (n = 1); and a wireless sensor with accelerometer, gyroscope, and magnetometer (n = 1). Adherence to E-DAT was > 70% in 5 of 7 RCTs. Compared to controls (exercise interventions without digital activity trackers or standard of care), E-DAT significantly improved the step count in 60% of 5 RCTs, activity level in 56% of 9 RCTs, and HRQOL in 56% of 9 RCTs (all p < 0.05), with no significant changes of inflammatory markers (i.e. TNF, CRP, c-peptide) in 2 RCTs. No significant correlations were found between duration of E-DAT with adherence (Spearman’s r = 0.16; p = 0.75) or study retention (Spearman’s r = -0.42; p = 0.17). Conclusions: This systematic review shows that E-DAT is feasible to implement in cancer patients. Future research should examine the optimal type, dose and schedule of E-DAT.

ATOPE+: An mHealth System to Support Personalized Therapeutic Exercise Interventions in Patients With Cancer

“…The small presence of similar approaches with patients with cancer in TE interventions served as a major impulse for this work, specially noting the lack of sophisticated personalization strategies. Most of the personalization strategies found were based on selfmanagement and/or self-monitoring of physical activity with wearable devices [12]. ATOPE+ takes a different approach by rooting its personalization strategy in the physiological foundations of workload-recovery ratio assessment by means of HRV (and its most relevant modulating factors: sleep satisfaction, distres, recovery perception and fatige.…”

“…Focusing on PA and TE interventions with patients with cancer, just a few works leverage the mHealth paradigm. A recent systematic review [12] identified twelve randomized controlled trials meeting the characteristics of an mHealth exercise intervention. In most cases, there was no objectivelymonitored personalization strategy.…”

“…This has recently driven the research community to seek after new means to deliver TE interventions in remote environments by leveraging mobile technology [11]. In fact, to date, the literature shows that mHealth PA interventions are a feasible, cost-effective approach to improve overall activity levels, body composition, quality of life and self-reported symptoms in patients with cancer [12] and survivors [13].…”

“…Personalization primarily relied on patients' self-management to meet the minimal levels of recommended PA [26], and intervention materials were given as printed booklets, multimedia content or communicated by phone calls. The broad-range nature of these methods is still present in many mHealth interventions [12], [13], thus hampering the introduction of more sophisticated personalization strategies. This opens up opportunities to introduce mobile technologies and monitoring devices to gather objective, comparable and quantifiable information about each patient's health and performance during the intervention process [27], [28], which can potentially be used to tailor and adapt such process to the specific user needs.…”