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Interest in the use of wearables in medical care is increasing. Wearables can be used to monitor different variables, such as vital signs and physical activity. A crucial point for using wearables in oncology is if patients already under the burden of severe disease and oncological treatment can accept and adhere to the device. At present, there are no specific recommendations for the use of wearables in oncology, and little research has examined the purpose of using wearables in oncology.
The purpose of this review is to explore the use of wearables in clinical trials during cancer treatment, with a special focus on adherence.
PubMed and EMBASE databases were searched prior and up to October 3, 2019, with no limitation in the date of publication. The search strategy was aimed at studies using wearables for monitoring adult patients with cancer during active antineoplastic treatment. Studies were screened independently by 2 reviewers by title and abstract, selected for inclusion and exclusion, and the full-text was assessed for eligibility. Data on study design, type of wearable used, primary outcome, adherence, and device outcome were extracted. Results were presented descriptively.
Our systematic search identified 1269 studies, of which 25 studies met our inclusion criteria. The types of cancer represented in the studies were breast (7/25), gastrointestinal (4/25), lung (4/25), and gynecologic (1/25); 9 studies had multiple types of cancer. Oncologic treatment was primarily chemotherapy (17/25). The study-type distribution was pilot/feasibility study (12/25), observational study (10/25), and randomized controlled trial (3/25). The median sample size was 40 patients (range 7-180). All studies used a wearable with an accelerometer. Adherence varied across studies, from 60%-100% for patients wearing the wearable/evaluable sensor data and 45%-94% for evaluable days, but was differently measured and reported. Of the 25 studies, the most frequent duration for planned monitoring with a wearable was 8-30 days (13/25). Topics for wearable outcomes were physical activity (19/25), circadian rhythm (8/25), sleep (6/25), and skin temperature (1/25). Patient-reported outcomes (PRO) were used in 17 studies; of the 17 PRO studies, only 9 studies reported correlations between the wearable outcome and the PRO.
We found that definitions of outcome measures and adherence varied across studies, and limited consensus among studies existed on which variables to monitor during treatment. Less heterogeneity, better consensus in terms of the use of wearables, and established standards for the definitions of wearable outcomes and adherence would improve comparisons of outcomes from studies using wearables. Adherence, and the definition of such, seems crucial to conclude on data from wearable studies in oncology. Additionally, research using advanced wearable devices and active use of the data are encouraged to further explore the potential of wearables in oncology during treatment. Particularly, randomized clinical studies are warranted to create consensus on when and how to implement in oncological practice.
Technology expansion over the past decade, along with the use of various sensors and electronic devices and the arrival of more advanced devices, has led to new possibilities [
A wearable is a device with a sensor that can collect health-related data remotely [
In oncology, wearables may offer new vital information about patients, which can potentially lead to better management of cancer treatment [
To understand the potential use of wearables, it is relevant to capture what the wearable’s objective outcome is, what effect or role it has on the clinical outcome, and what it can be used for in a medical setting [
The purpose of this review is to explore the use of wearables in clinical trials during cancer treatment, with a focus on adherence and the setting.
Systematic searches were performed in PubMed and EMBASE. Both databases were searched prior and up to October 3, 2019, with no limitation in the date of publication. Searches consisted of cancer/neoplasm keywords and terms for wearable devices.
In PubMed, the search consisted of the medical-subject-heading (MeSH) terms “neoplasms,” “medical oncology,” “surgical oncology,” and “wearable electronic devices,” along with a combination of free-text words for the topics “oncology,” “cancer,” “wearable device,” “accelerometer,” and “actigraph.” In EMBASE, the search included categorized terms for neoplasms and electronic monitoring devices such as “neoplasm,” “patient monitoring,” and “electronic device.” Additional search terms “ambulatory monitoring” and “telemedicine” were added. The search was limited to articles published in English. The search strategy is shown in
Studies found with the selected search strategy were screened by title and abstract, which was performed independently by 2 reviewers who were blinded to each other’s decisions. Cases of disagreement about whether to include or exclude a study were decided through a consensus decision. The included studies had their full text assessed for eligibility; disagreements were resolved by consensus, which was achieved in all cases.
For a study to be included, it had to be written in English and be either a randomized controlled trial (RCT), observational study, or pilot study/ feasibility study. Patients had to be 18 years of age or older and diagnosed with a solid malignant tumor. It was mandatory that studies took place during active cancer treatment; treatment could be either radiation or antineoplastic treatment, such as chemotherapy or targeted therapy. Studies investigating all types of wearables were considered eligible if they had an objective measure. Studies had to include a description of adherence to the wearable to be eligible for inclusion.
Exclusion criteria were studies registered as protocol descriptions, study protocols, abstracts from conferences, editorials, letters, or case reports. Also excluded were studies in which patients were cancer survivors or had hematologic malignancies and were treated with endocrine therapy only or surgery only. If the wearable devices were worn only pretreatment, the study used hearing aids as the wearable device, or wearables were used as treatment or for diagnostics, then these studies were also excluded.
The search is graphically presented according to the PRISMA flow diagram (
PRISMA flow diagram of the screening and selection of studies.
The following study characteristics data were extracted: study title, author, year of publication, country, study design, number of patients included, and main objectives. Study population information that was extracted included age group, cancer type, treatment type, and intent of treatment. Study data regarding the adherence to the wearable were the type of wearable used (hardware, software), placement, device outcome, planned wear time, valid wear time, and adherence to the wearable. For the purposes of this review, the device outcome was defined as the objective measures used in the study (eg, step count); planned wear time was defined as the time period that patients were supposed to use the device; and valid wear time was defined as the minimum wear time for data inclusion, extracted if available (eg, ≥10 hours/day). Adherence could either be the percentage of patients wearing the wearable for the period, the percentages of patients with evaluable sensor data, or the percentages of total evaluable days. Study outcomes were extracted and thematically grouped into wearable outcome, PRO, and clinical outcome. Wearable outcome was defined as circadian rhythm, physical activity (PA), skin temperature, and sleep. PRO topics were quality of life, PA, mental health, symptom registration, and others. Clinical outcomes included adverse events, performance status (PS), and hospitalization.
When reading through the full text of included studies, synonyms for “wearable” were registered and extracted from each study.
The review was conducted to give a descriptive presentation of the use of wearables in clinical trials. The primary outcome was adherence to the wearable. The secondary outcomes were the study outcomes: the wearable outcome, the PRO, and the clinical outcome. The wearable outcome was subtracted from the device outcome by the authors, and thematically grouped as a wearable outcome. We also investigated whether the studies reported a relationship between the wearable outcome and the PRO. All data were presented descriptively.
This review did not require national or institutional approval.
The search strategies were performed in PubMed and EMBASE on October 3, 2019. A total of 1281 studies were identified through the searches. There were 12 duplicated records, which were excluded, leaving 1269 studies eligible for screening. Titles and abstracts were examined, which resulted in the exclusion of 1180 studies that did not meet our inclusion criteria. The remaining 89 studies were evaluated for eligibility. Through full-text access, 64 other irrelevant studies were excluded, leaving a total of 25 studies to be reviewed for the purpose of this review. This process of study screening and selection is illustrated in a PRISMA flow chart (
Study characteristics are presented in
In 5 of the 25 studies, the planned wear time was ≤7 days, 13 were between 8-30 days, 5 were between 31-90 days, and in 2 studies, the planned wear time was over 90 days (
Characteristics of included studies, n=25.
Study (year) | Country | Primary cancer site | Treatment type | Sample size, n | Age group (range or mean [SD]) | Study type |
Broderick et al (2019) [ |
United States | Mixed | Chemotherapy | 42 | 24-72 | Pilot / feasibility study |
Champ et al (2018) [ |
United States | Breast | Radiotherapy | 10 | 52-79 | Pilot / feasibility study |
Chevalier et al (2003) [ |
France | Gastrointestinal | Chemotherapy | 10 | 43-73 | Pilot / feasibility study |
Dean et al (2013) [ |
United States | Lung | Chemotherapy | 35 | 48-94 | Observational study |
Dreher et al (2019) [ |
United States | Breast | Chemotherapy | 65 | 29-72 | Observational study |
Edbrooke et al (2019) [ |
Australia | Lung | Mixed | 92 | 63 (12.3) | Randomized controlled trial |
Gupta et al (2018) [ |
United States | Mixed | Systemic therapy | 24 | 54 (12.5) | Pilot / feasibility study |
Innominato et al (2016) [ |
United Kingdom | Mixed | Chemotherapy | 31 | 35-91 | Pilot / feasibility study |
Li et al (2019) [ |
China | Breast | Adjuvant chemotherapy | 180 | 22-74 | Observational study |
Low et al (2017) [ |
United States | Gastrointestinal | Chemotherapy | 14 | 40-74 | Pilot / feasibility study |
Lowe et al (2014) [ |
Canada | Mixed | Radiotherapy (whole brain) | 31 | 63.5 (10.4) | Observational study |
Mouri et al (2018) [ |
Japan | Mixed | Chemotherapy | 30 | 70-84 | Pilot / feasibility study |
Nyrop et al (2018) [ |
United States | Breast | Chemotherapy | 100 | 24-64 | Observational study |
Ohri et al (2019) [ |
United States | Lung | Chemo-radiotherapy | 50 | 38-90 | Observational study |
Ohri et al (2017) [ |
United States | Mixed | Chemo-radiotherapy | 38 | 33-82 | Pilot / feasibility study |
Ortiz-Tudela et al (2014) [ |
France | Mixed | Chemotherapy | 49 | 35-90 | Observational study |
Parker et al (2019) [ |
United States | Pancreas | Chemotherapy; chemo-radiotherapy | 50 | 66 (8) | Observational study |
Roche et al (2014) [ |
France | Gastrointestinal | Chemotherapy | 16 | 51-89 | Pilot / feasibility study |
Roscoe et al (2002) [ |
United States | Breast | Chemotherapy +/- radiotherapy | 102 | 34-79 | Randomized controlled trial |
Sarna et al (2001) [ |
United States | Mixed | Radiotherapy | 7 | 48-74 | Pilot / feasibility study |
Savard et al (2009) [ |
United States | Breast | Chemotherapy | 95 | 34-79 | Observational study |
Solk et al (2019) [ |
United States | Breast | Chemotherapy | 67 | 31-71 | Observational study |
van der Meij et al (2012) [ |
The Netherlands | Lung | Chemo-radiotherapy | 40 | 39-80 | Randomized controlled trial |
Vassbakk-Brovold et al (2016) [ |
Norway | Mixed | Chemotherapy | 66 | 59 (11) | Pilot / feasibility study |
Wright et al (2018) [ |
United States | Gynaecological | Chemotherapy | 10 | 60 (11) | Pilot / feasibility study |
Description of wearables and adherence.
Planned wear time interval and study (year) | Hardware / software | Device outcome | Planned wear time / valid wear time | Adherence description | |
≤ |
|
|
|
|
|
|
Chevalier et al (2003) [ |
Actigraph, Ambulatory Monitoring Inc / Action 3.8 |
Rest activity cycle (movements/period) |
3 days / 3 days |
100% (10/10) of the patients wore the device for the full period |
|
Dean et al (2013) [ |
Motionlogger actigraph / Action 3 |
Sleep efficiency (%) Sleep (hours) Wake after sleep onset (minutes) |
7 days / not reported |
86% (30/35) of the patients wore the device for the full period |
|
Lowe et al (2014) [ |
activPALa / not reported |
Position time (hours/day) Energy expenditure (metabolic equivalent of task [MET] h/day) Step count (steps/day) |
7 days / not reported |
77% (24/31) of the patients provided evaluable sensor data between 3 and 7 days |
|
Roscoe et al (2002) [ |
Mini-Motionlogger Actigraph / Action 3 |
Circadian consistency (I<Ob) Daytime activity level (minutes) Sleep (%) |
72 hours at 2 timepoints / not reported |
89% (91/102) provided evaluable sensor data at second cycle of chemotherapy 44% (45/102) provided evaluable sensor data at fourth cycle of chemotherapy |
|
Vassbakk-Brovold et al 2016) [ |
SenseWear Armband Pro3 or SenseWear Armband Minia / SenseWear version 6.1 for Pro3 and version 7.0 for Mini |
Physical activity (minutes/week) recorded in 1-minute epochs |
5 days / ≥19.2 hrs, for ≥1 day |
79 % (66/84) of the patients wore the device for the full period |
|
|
|
|
|
|
|
Edbrooke et al (2019) [ |
SenseWear accelerometera / not reported |
Step count (steps/day) Number of 10+ minutes step bouts/day Duration of 10+ minutes bouts (minutes) Cadence of 10+ minutes bouts (steps/min) |
7 days at 3 timepoints / 8hrs/day, for ≥4 days |
87% (80/92) of the patients provided evaluable sensor data at baseline 71%(65/92) of the patients provided evaluable sensor data at 9 weeks 60% (55/92) of the patients provided evaluable data at 6 months |
|
Innominato et al (2016) [ |
Micro Motionlogger / Action 4 |
Circadian rest-activity (I<Ob) |
30 days / not reported |
Evaluable sensor data were available in 75 % of the total days (653/874) |
|
Li et al (2019) [ |
GENEActiv Original / not reported |
Sleep efficiency (%) Sleep duration (minutes) Nighttime total wake time (minutes) |
7 days at 3 timepoints / ≥5 days per timepoint |
97% (175/180) of the patients provided evaluable sensor data at T2 76% (136/180) of the patients provided evaluable sensor data at T3 |
|
Low et al (2017) [ |
Fitbit Charge HR / not reported |
Step count (steps/day) Floors climbed (n) Sleep (minutes) Awakenings (n) Time in bed (minutes) |
4 weeks / not reported |
Evaluable sensor data were available in 75 % of the total days (295/392 days) |
|
Mouri et al (2018) [ |
Kenz Lifecorder‐GSa / Lifelyzer‐05 coach |
Step count (steps/day) Physical activity (minutes/day) (physical activity was rated ≥1.8 METs) |
7 days at 3 timepoints / ≥5 hrs/day |
93% (28/30) of the patients wore the device for the full period |
|
Ohri et al (2019) [ |
Garmin Vivofit a / not reported |
Step count (steps/day) |
Up to 3 weeks / not reported |
Evaluable sensor data were available in 94 % of the total days (741/791) |
|
Ortiz-Tudela et al (2014) [ |
Mini-Motionlogger Actigraph / Action 4 |
Rest-activity (I<Ob) Wrist accelerations (acc/minute) |
10-14 days split into 4 periods of 3-4 days / not reported |
86% (42/49) of the patients provided evaluable sensor data the full period |
|
Roche et al (2014) [ |
Mini-Motionlogger and VitalSense / Action 4, version 1.10 |
Rest-activity (I<Ob) Wrist accelerations (acc/minute) Skin surface temperature (°C/minute) |
12 days split into 3 periods of 4 days/ not reported |
100% (16/16) of patients provided evaluable sensor data at baseline 63% (10/16) of patients provided evaluable sensor data during therapy and after therapy administration |
|
Sarna et al (2001) [ |
Actiwatch 2 / not reported |
Wrist movement (n/second) Physical activity (15-minute intervals) |
5 days at 2 timepoints/ ≥3 days per timepoint |
100% (7/7) of the patients wore the device the full period |
|
Savard et al (2009) [ |
Actillume / Action 3 |
Circadian rhythm variables (calculated from orientation and movement) |
72 hrs at 7 timepoints/ not reported |
91% (86/95) of patients provided evaluable sensor data at baseline (first cycle of chemotherapy week 1: 80%, week 2: 73% and week 3: 76%; fourth cycle of chemotherapy week 1: 74%, week 2 63% and week 3: 68%) |
|
Solk et al (2019) [ |
ActiGraph, model wGT3X-BT / ActiLife, version 6.13.3 |
Activity data (1-minutes intervals) |
10 days at 3 timepoints / ≥10 hrs/day |
84% (63/75) of the patients provided evaluable sensor data for the full period |
|
van der Meij et al (2012) [ |
PAM accelerometer, model AM101a / not reported |
Physical activity (index score, 3 points reflects about 10 min of walking) |
7 days at 3 timepoints / ≥3 full days |
65% (26/40) of the patients wore the device for the full period |
|
Wright et al (2018) [ |
Fitbit Zip and Fitbit Charge 2 / Fitabase |
Step count (steps/day) Heart rate |
30 days / ≥4 days/week |
90% (9/10) of the patients wore the devices for the full period |
|
|
|
|
|
|
|
Broderick et al (2019) [ |
Microsoft Band 2 / not reported |
Step count (steps/day) Heart rate Calories (calories/hour) |
60 days / ≥6 hrs/day |
Evaluable sensor data were available 86 % of the days (only day 1-14 included) |
|
Champ et al (2018) [ |
Misfit Shinea / not reported |
Step count (steps/day) Calories (calories/day) Walking distance (miles) Sleep (hours) |
10 weeks / not reported |
90% (9/10) of the patients wore the device for the full period |
|
Gupta A et al (2018) [ |
Fitbit Flex / not reported |
Step count (steps/day) Physical activity (sedentary minutes/day) Sleep (minutes) |
12 weeks / ≥1 steps/day recorded |
96% (23/24) wore the device for >50% of the period |
|
Nyrop et al (2018) [ |
Fitbit Zipa / not reported |
Step count (steps/day) |
6-12 weeks / ≥3 weeks |
79% (100/127) of the patients provided evaluable sensor data |
|
Ohri et al (2017) [ |
Garmin / not reported |
Step count (steps/day) |
Up to 80 days / 80% of the days |
Evaluable sensor data were available 94 % of the days |
|
|
|
|
|
|
|
Dreher et al (2019) [ |
Fitbit Charge HR or Fitbit Charge 2 / Fitabase |
Step count (steps/day) Heart rate Sleep data |
Up to 270 days / ≥10 hrs/day |
Evaluable sensor data were available in 45% of the days across 9 months |
|
Parker et al (2019) [ |
ActiGraph GT3X+a / ActiLife Software, Version 6 |
Physical activity (minutes/week) (1-min epochs) |
14 days at each therapy phase / ≥10 hrs/day, for ≥7 days per timepoint |
88 % (44/50) of the patients provided evaluable sensor data |
aPlacement other than wrist (anterior mid-thigh, hip, triceps muscle waist, not reported).
bbI<O is computed as the percentage of activity epochs when in-bed (I), whose values are lower than the median level of activity when out-of-bed(O).
Adherence data, presenting how many patients were able to use or collect data from the wearable device, or how many evaluable days the wearable was worn, were collected. Adherence varied across studies, from 60%-100% and 45%-94%, respectively, but was differently measured and reported. Valid wear time was defined in 16 of the 25 studies. Different hardware and software were used. The most frequent placement of the wearable was the wrist.
In
Study outcomes
Cancer type and study (year) | Wearable outcomes | Patient-reported outcomes | Clinical outcomes | ||||||||||||
|
|
Circ. |
Phys. |
Skin |
Sleep | Mental |
Phys. |
QoLd | Symptoms | Other | Adverse |
Perf. |
Hospitalization | Other | |
|
|||||||||||||||
|
Roscoe et al (2002) [ |
✓ | ✓ |
|
✓ | ✓ |
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|
✓ |
|
✓ |
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Savard J et al (2009) [ |
✓ |
|
|
✓ |
|
|
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|
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||
Champ et al (2017) [ |
|
✓ |
|
✓ |
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||
Li et al (2019) [ |
✓ | ✓ |
|
|
|
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|
|
|
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|
|
✓ | ||
Nyrop et al (2018) [ |
|
✓ |
|
|
✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
|
✓ | ||
Dreher et al (2019) [ |
✓ | ✓ |
|
|
|
|
|
|
|
|
|
|
|
||
Solk et al (2019) [ |
|
✓ |
|
|
✓ | ✓ |
|
✓ | ✓ |
|
|
|
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||
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|||||||||||||||
|
Chevalier et al (2003) [ |
✓ |
|
|
|
|
|
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Roche et al (2014) [ |
✓ |
|
✓ |
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||
Low et al (2017) [ |
|
✓ |
|
✓ |
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|
✓ |
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||
Parker et al (2019) [ |
|
✓ |
|
|
|
✓ |
|
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|
✓ | ||
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|||||||||||||||
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Wright et al (2018) [ |
|
✓ |
|
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|
|
✓ |
✓ |
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|
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|
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|||||||||||||||
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van der Meij et al (2012) [ |
|
✓ |
|
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|
|
✓ |
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Dean et al (2013) [ |
|
|
|
✓ | ✓ |
|
✓ |
|
✓ |
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||
Edbrooke et al (2019) [ |
|
✓ |
|
|
✓ | ✓ | ✓ | ✓ |
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||
Ohri et al (2019) [ |
|
✓ |
|
|
|
|
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✓ | ✓ | ||
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|||||||||||||||
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Sarna et al (2001) [ |
|
✓ |
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✓ |
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✓ | ✓ |
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Ortiz-Tudela et al (2014) [ |
✓ |
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✓ |
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Lowe et al (2014) [ |
|
✓ |
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✓ | ✓ | ✓ |
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Innominato et al (2016) [ |
✓ |
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|
✓ |
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Vassbakk-Brovold et al (2016) [ |
|
✓ |
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✓ |
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✓ | |
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Ohri et al (2017) [ |
|
✓ |
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✓ |
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✓ | ✓ | |
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Gupta et al (2018) [ |
|
✓ |
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✓ | ✓ |
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✓ |
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✓ |
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✓ |
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Mouri et al (2018) [ |
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✓ |
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✓ |
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Broderick et al (2019) [ |
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✓ |
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✓ |
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✓ |
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✓ |
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aCirc. rhythm: Circadian rhythm.
bPhys. activity: Physical activity.
cSkin temp.: Skin temperature.
dQoL: Quality of life.
ePerf. status: Performance status.
Of the 17 PRO studies, only 9 studies reported correlations between the wearable outcome and the PRO (
Synonyms for “wearable” were also collected for each study (data not shown) while reading through the full text, which reflected both the terms used to address the technology in general and the terms describing the actual device used in the study. The most commonly used term was “accelerometer,” which was used in 12 studies; next was “actigraph,” which was mentioned in 8 studies. The term “tracker” was used in 6 studies as a part of several terms, including “activity tracker,” “wearable activity tracker,” and “fitness tracker.” The latter term was used similarly to “monitor,” which was mentioned in 9 studies.
Studies that reported relationships between wearable outcomes and patient-reported outcomes (PRO; n=9).
PRO | Wearable outcome | |||
|
Circadian rhythm | Physical activity | Skin temperature | Sleep |
Mental health | [ |
[ |
—a | [ |
Physical activity | — | [ |
— | — |
Quality of life | — | [ |
— | [ |
Symptoms | — | [ |
— | [ |
Others | [ |
[ |
— | [ |
aNo relationship reported.
The use of wearable sensor devices has become a popular self-awareness gadget for many people today, especially when it comes to measuring physical activity [
Other studies have reviewed the use and effects of eHealth tools, such as those for patient self-reporting of medication management and use, and have concluded that more high-quality research is needed before standard implementation of such tools can occur [
To our knowledge, this is the first review of the use of wearables in clinical trials during cancer treatment. This review was limited to studies that included adherence as an issue, but was not restricted to specific types of wearables. However, we and others believe that the choice of wearable outcome is highly important. Determination of which variables to measure is crucial to ensure the purpose of the wearable when incorporated into patients’ daily routines [
Many different terms are being used to describe electronic devices for use in health care [
The patient populations represented in this review mostly reflect breast and mixed cancer populations. Additionally, most studies are from the United States. It is questionable if results from such studies can be transferred to other diagnoses, countries, and cultural settings.
As in this review, overall adherence to wear time or to wearable device interventions in general are difficult to compare. This is because almost every study has a different way of defining how many minutes or hours of wear time should count as a valid active day. By establishing standards for definitions of wear time, this could allow results across different patient populations to be compared more easily. This could also be solved by using a parameter other than step count as a measure of physical activity [
This review provides an overview of the frequently used wearables in oncology during therapy. Many of the wearables used have similar competencies, which might suggest the need to expand research into using more advanced wearables like smartwatches; according to Lu et al [
This review provides an inventory for the status of wearables in clinical trials and can be used in addition to the CTTI studies database when designing new clinical trials with wearables [
This review provides an overview of the use of wearable devices in oncology care for patients with solid tumors receiving antineoplastic treatment. We extracted data from studies monitoring patients with cancer and presented these results specifically regarding adherence, the device outcomes, and the types of wearables used.
We found that definitions of outcome measures and adherence varied across studies, and limited consensus among studies existed on which variables to monitor during treatment.
Less heterogeneity and better consensus in terms of use and establishing standards for definitions of wearable outcomes and adherence would improve the comparisons of outcomes among studies using wearables. Adherence and consistent definitions are crucial for drawing conclusions from data from wearable studies in oncology. Additionally, research using advanced wearable devices and active use of the data are encouraged to further explore the potential of wearables in oncology during treatment. Especially, randomized clinical studies are warranted to create consensus on when and how to implement in oncological practice.
Search strategy.
Clinical Transformation Initiative
gastrointestinal
gynecological
physical activity
patient-reported outcome
randomized controlled trial
CHM is supported by the Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
None declared.