Evidence map›Paper›PMID 28387544›Full record

ReviewJournal of oncology practice2017

Promise of Wearable Physical Activity Monitors in Oncology Practice.

Muhammad S Beg, Arjun Gupta, Tyler Stewart, Chad D Rethorst

3 registry-linked trialsOpen access · bronzeAbstract readReview
In one paragraph

Review in Journal of oncology practice, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 36 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 2 pooled it
4.9field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03529383 nacompletednot on this mapstarted 2018, after this paper: background citation

Randomized Controlled Trial Evaluating the Efficacy of an Adapted Physical Activity Program Using a Connected Device With Activity Trackers and a Therapeutic Education Program Among Women With Localized Breast Cancer

TypeinterventionalSponsorCentre Leon BerardRan2018 to 2022Enrolled436ConditionsBreast CancerArmsConnected device, Therapeutic education
NCT05318027 phase2active not recruitingnot on this mapstarted 2023, after this paper: background citation

Use of Natural Language Processing ChatBot and Automated Continuous Activity Monitoring Via Mobile Phones for Early Detection and Management of Symptoms in Patients Undergoing Cancer Treatment

TypeinterventionalSponsorAbramson Cancer Center at Penn MedicineRan2023 to 2026Enrolled70ConditionsLung Cancer, Gastrointestinal Cancer, Head and Neck CancerArmsChatBot
NCT07541365 narecruitingnot on this mapstarted 2026, after this paper: background citation

Feasibility and Acceptability of Wearable Sensors and ePROs in Early Phase Clinical Trials

TypeinterventionalSponsorCase Comprehensive Cancer CenterRan2026 to 2027Enrolled30ConditionsCancerArmsWearable actigraphy, Electronic Patient-Reported Outcomes (ePROs)
3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 89 citations in OpenAlex.

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  10. Physical activity and physical fitness assessments in adolescents and young adults diagnosed with cancer: a scoping review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Muhammad S BegUniversity of Texas Southwestern Medical Center; Harold C. Simmons Cancer Center, Dallas, TX; and Yale University, New Haven, CT.
Arjun GuptaUniversity of Texas Southwestern Medical Center; Harold C. Simmons Cancer Center, Dallas, TX; and Yale University, New Haven, CT.
Tyler StewartUniversity of Texas Southwestern Medical Center; Harold C. Simmons Cancer Center, Dallas, TX; and Yale University, New Haven, CT.
Chad D RethorstUniversity of Texas Southwestern Medical Center; Harold C. Simmons Cancer Center, Dallas, TX; and Yale University, New Haven, CT.
The University of Texas Southwestern Medical Center · USYale University · US

Funding

An Exercise Intervention to Prevent Interferon-Induced Depression in Hepatitis CK01MH097847 · NIMH · UT SOUTHWESTERN MEDICAL CENTER · PI RETHORST, CHAD D · 2013 to 2016
$595k
NIMH NIH HHS K01 MH097847
6 · The paper itself

Abstract

Commercially available physical activity monitors provide clinicians an opportunity to obtain oncology patient health measures to an unprecedented degree. These devices can provide objective and quantifiable measures of physical activity, which are not subject to errors or bias of self-reporting or shorter duration of formal testing. Prior work on so-called quantified-self data was based on older-generation, research-grade accelerometers, which laid the foundation for consumer-based physical activity monitoring devices to be validated as a feasible and reliable tool in patients with cancer. Physical activity monitors are being used in chronic conditions including chronic obstructive pulmonary disease, congestive heart failure, diabetes mellitus, and obesity. Differing demographics, compounded with higher symptom and treatment burdens in patients with cancer, imply that additional work is needed to understand the unique strengths and weaknesses of physical activity monitors in this population. Oncology programs can systematically implement these tools into their workflows in an adaptable and iterative manner. Translating large amounts of data collected from an individual physical activity monitoring device into clinically relevant information requires sophisticated data compilation and reduction. In this article, we summarize the characteristics of older- and newer-generation physical activity monitors, review the validation of physical activity monitors with respect to health-related quality-of-life assessments, and describe the current role of these devices for the practicing oncologist. We also highlight the challenges and next steps needed for physical activity monitors to provide relevant information that can change the current state of oncology practice.

Indexed as

Fitness TrackersEquipment DesignExerciseHumansMedical OncologyMonitoring, PhysiologicNeoplasmsRandomized Controlled Trials as TopicTechnology Assessment, Biomedical

Identifiers

PMID28387544
PMCPMC6075841
OpenAlexW2588852707

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.