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Delrieu L, Hamy AS, Coussy F, Kassara A, Asselain B, Antero J, De Villèle P, Dumas E, Forstmann N, Guérin J, Hotton J, Jouannaud C, Milder M, Leopold A, Sedeaud A, Soibinet P, Toussaint JF, Vercamer V, Laas E, Reyal F. Digital phenotyping in young breast cancer patients treated with neoadjuvant chemotherapy (the NeoFit Trial): protocol for a national, multicenter single-arm trial. BMC Cancer 2022; 22:493. [PMID: 35509030 PMCID: PMC9069776 DOI: 10.1186/s12885-022-09608-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 03/22/2022] [Indexed: 11/17/2022] Open
Abstract
Background Breast cancer (BC) has particular characteristics in young women, with diagnosis at more advanced stages, a poorer prognosis and highly aggressive tumors. In NeoFit, we will use an activity tracker to identify and describe various digital profiles (heart rate, physical activity, and sleep patterns) in women below the age of 45 years on neoadjuvant chemotherapy for BC. Methods NeoFit is a prospective, national, multicenter, single-arm open-label study. It will include 300 women below the age of 45 years treated with neoadjuvant chemotherapy for BC. Participants will be asked to wear a Withing Steel HR activity tracker round the clock for 12 months. The principal assessments will be performed at baseline, at the end of neoadjuvant chemotherapy and at 12 months. We will evaluate clinical parameters, such as toxicity and the efficacy of chemotherapy, together with quality of life, fatigue, and parameters relating to lifestyle and physical activity. The women will complete REDCap form questionnaires via a secure internet link. Discussion In this study, the use of an activity tracker will enable us to visualize changes in the lifestyle of young women on neoadjuvant chemotherapy for BC, over the course of a one-year period. This exploratory study will provide crucial insight into the digital phenotypes of young BC patients on neoadjuvant chemotherapy and the relationship between these phenotypes and the toxicity and efficacy of treatment. This trial will pave the way for interventional studies involving sleep and physical activity interventions. Trial registration Clinicaltrials.gov identifier: NCT05011721. Registration date: 18/08/2021.
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Affiliation(s)
- Lidia Delrieu
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
| | - Anne-Sophie Hamy
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France.,Department of Medical Oncology, Institut Curie, University Paris, Paris, France
| | - Florence Coussy
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France.,Department of Medical Oncology, Institut Curie, University Paris, Paris, France
| | - Amyn Kassara
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
| | | | - Juliana Antero
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France.,Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France
| | | | - Elise Dumas
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
| | - Nicolas Forstmann
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France.,Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France
| | | | - Judicael Hotton
- Department of Surgical Oncology, Institut de Cancérologie Jean-Godinot, Reims, France
| | - Christelle Jouannaud
- Department of Medical Oncology, Institut de Cancérologie Jean-Godinot, Reims, France
| | | | | | - Adrien Sedeaud
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France.,Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France
| | - Pauline Soibinet
- Department of Medical Oncology, Institut de Cancérologie Jean-Godinot, Reims, France
| | - Jean-François Toussaint
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France.,Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France.,Center for Sports Medicine Research, Hôtel-Dieu, Publics Assistance Hospitals of Paris, Paris, France
| | | | - Enora Laas
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France.,Department of Surgical Oncology, Institut Curie, University Paris, Paris, France
| | - Fabien Reyal
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France. .,Department of Surgical Oncology, Institut Curie, University Paris, Paris, France.
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Telemonitoring of Real-World Health Data in Cardiology: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18179070. [PMID: 34501659 PMCID: PMC8431660 DOI: 10.3390/ijerph18179070] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/24/2021] [Accepted: 08/26/2021] [Indexed: 11/16/2022]
Abstract
Background: New sensor technologies in wearables and other consumer health devices open up promising opportunities to collect real-world data. As cardiovascular diseases remain the number one reason for disease and mortality worldwide, cardiology offers potent monitoring use cases with patients in their out-of-hospital daily routines. Therefore, the aim of this systematic review is to investigate the status quo of studies monitoring patients with cardiovascular risks and patients suffering from cardiovascular diseases in a telemedical setting using not only a smartphone-based app, but also consumer health devices such as wearables and other sensor-based devices. Methods: A literature search was conducted across five databases, and the results were examined according to the study protocols, technical approaches, and qualitative and quantitative parameters measured. Results: Out of 166 articles, 8 studies were included in this systematic review; these cover interventional and observational monitoring approaches in the area of cardiovascular diseases, heart failure, and atrial fibrillation using various app, wearable, and health device combinations. Conclusions: Depending on the researcher’s motivation, a fusion of apps, patient-reported outcome measures, and non-invasive sensors can be orchestrated in a meaningful way, adding major contributions to monitoring concepts for both individual patients and larger cohorts.
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Osei E, Nkambule SJ, Vezi PN, Mashamba-Thompson TP. Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa. Diagnostics (Basel) 2021; 11:diagnostics11061081. [PMID: 34204848 PMCID: PMC8231511 DOI: 10.3390/diagnostics11061081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 06/08/2021] [Indexed: 12/24/2022] Open
Abstract
Mobile health devices are emerging applications that could help deliver point-of-care (POC) diagnosis, particularly in settings with limited laboratory infrastructure, such as Sub-Saharan Africa (SSA). The advent of Severe acute respiratory syndrome coronavirus 2 has resulted in an increased deployment and use of mHealth-linked POC diagnostics in SSA. We performed a systematic review and meta-analysis to evaluate the accuracy of mobile-linked point-of-care diagnostics in SSA. Our systematic review and meta-analysis were guided by the Preferred Reporting Items requirements for Systematic Reviews and Meta-Analysis. We exhaustively searched PubMed, Science Direct, Google Scholar, MEDLINE, and CINAHL with full text via EBSCOhost databases, from mHealth inception to March 2021. The statistical analyses were conducted using OpenMeta-Analyst software. All 11 included studies were considered for the meta-analysis. The included studies focused on malaria infections, Schistosoma haematobium, Schistosoma mansoni, soil-transmitted helminths, and Trichuris trichiura. The pooled summary of sensitivity and specificity estimates were moderate compared to those of the reference representing the gold standard. The overall pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of mobile-linked POC diagnostic devices were as follows: 0.499 (95% CI: 0.458–0.541), 0.535 (95% CI: 0.401–0.663), 0.952 (95% CI: 0.60–1.324), 1.381 (95% CI: 0.391–4.879), and 0.944 (95% CI: 0.579–1.538), respectively. Evidence shows that the diagnostic accuracy of mobile-linked POC diagnostics in detecting infections in SSA is presently moderate. Future research is recommended to evaluate mHealth devices’ diagnostic potential using devices with excellent sensitivities and specificities for diagnosing diseases in this setting.
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Affiliation(s)
- Ernest Osei
- Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban 4001, South Africa; (S.J.N.); (P.N.V.); (T.P.M.-T.)
- Correspondence: or ; Tel.: +233-242-012-953
| | - Sphamandla Josias Nkambule
- Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban 4001, South Africa; (S.J.N.); (P.N.V.); (T.P.M.-T.)
| | - Portia Nelisiwe Vezi
- Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban 4001, South Africa; (S.J.N.); (P.N.V.); (T.P.M.-T.)
| | - Tivani P. Mashamba-Thompson
- Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban 4001, South Africa; (S.J.N.); (P.N.V.); (T.P.M.-T.)
- Faculty of Health Sciences, Prinshof Campus, University of Pretoria, Pretoria 0084, South Africa
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Abstract
Cardiovascular diseases (CVDs) are responsible for more deaths than any other cause, with coronary heart disease and stroke accounting for two-thirds of those deaths. Morbidity and mortality due to CVD are largely preventable, through either primary prevention of disease or secondary prevention of cardiac events. Monitoring cardiac status in healthy and diseased cardiovascular systems has the potential to dramatically reduce cardiac illness and injury. Smart technology in concert with mobile health platforms is creating an environment where timely prevention of and response to cardiac events are becoming a reality.
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Affiliation(s)
- Jeffrey W. Christle
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California 94305, USA
- Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California 94305, USA
| | - Steven G. Hershman
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California 94305, USA
| | - Jessica Torres Soto
- Biomedical Informatics Program, Department of Biomedical Data Science, Stanford University, Stanford, California 94305, USA
| | - Euan A. Ashley
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California 94305, USA
- Stanford Center for Inherited Cardiovascular Disease, Stanford University, Stanford, California 94305, USA
- Biomedical Informatics Program, Department of Biomedical Data Science, Stanford University, Stanford, California 94305, USA
- Stanford Center for Digital Health, Stanford University, Stanford, California 94305, USA
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Kramer JN, Künzler F, Mishra V, Presset B, Kotz D, Smith S, Scholz U, Kowatsch T. Investigating Intervention Components and Exploring States of Receptivity for a Smartphone App to Promote Physical Activity: Protocol of a Microrandomized Trial. JMIR Res Protoc 2019; 8:e11540. [PMID: 30702430 PMCID: PMC6374735 DOI: 10.2196/11540] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 10/26/2018] [Accepted: 10/31/2018] [Indexed: 11/27/2022] Open
Abstract
Background Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. Using machine learning techniques to infer each user’s context from smartphone sensor data is a promising approach to further enhance tailoring. Objective The primary objective of this study is to quantify main effects, interactions, and moderators of 3 intervention components of a smartphone-based intervention for physical activity. The secondary objective is the exploration of participants’ states of receptivity, that is, situations in which participants are more likely to react to intervention notifications through collection of smartphone sensor data. Methods In 2017, we developed the Assistant to Lift your Level of activitY (Ally), a chatbot-based mobile health intervention for increasing physical activity that utilizes incentives, planning, and self-monitoring prompts to help participants meet personalized step goals. We used a microrandomized trial design to meet the study objectives. Insurees of a large Swiss insurance company were invited to use the Ally app over a 12-day baseline and a 6-week intervention period. Upon enrollment, participants were randomly allocated to either a financial incentive, a charity incentive, or a no incentive condition. Over the course of the intervention period, participants were repeatedly randomized on a daily basis to either receive prompts that support self-monitoring or not and on a weekly basis to receive 1 of 2 planning interventions or no planning. Participants completed a Web-based questionnaire at baseline and postintervention follow-up. Results Data collection was completed in January 2018. In total, 274 insurees (mean age 41.73 years; 57.7% [158/274] female) enrolled in the study and installed the Ally app on their smartphones. Main reasons for declining participation were having an incompatible smartphone (37/191, 19.4%) and collection of sensor data (35/191, 18.3%). Step data are available for 227 (82.8%, 227/274) participants, and smartphone sensor data are available for 247 (90.1%, 247/274) participants. Conclusions This study describes the evidence-based development of a JITAI for increasing physical activity. If components prove to be efficacious, they will be included in a revised version of the app that offers scalable promotion of physical activity at low cost. Trial Registration ClinicalTrials.gov NCT03384550; https://clinicaltrials.gov/ct2/show/NCT03384550 (Archived by WebCite at http://www.webcitation.org/74IgCiK3d) International Registered Report Identifier (IRRID) DERR1-10.2196/11540
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Affiliation(s)
- Jan-Niklas Kramer
- Center for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
| | - Florian Künzler
- Center for Digital Health Interventions, Department of Management, Technology and Economics, Swiss Federal Institute of Technology, Zurich, Switzerland
| | - Varun Mishra
- Department of Computer Science, Dartmouth College, Hanover, NH, United States
| | - Bastien Presset
- Institute of Sports Studies, University of Lausanne, Lausanne, Switzerland
| | - David Kotz
- Department of Computer Science, Dartmouth College, Hanover, NH, United States.,Center for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Shawna Smith
- Institute for Social Research, University of Michigan - Ann Arbor, Ann Arbor, MI, United States.,Medical School, University of Michigan - Ann Arbor, Ann Arbor, MI, United States
| | - Urte Scholz
- Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Tobias Kowatsch
- Center for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland
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Sandberg K, Wright SP, Umans JG. Activity Tracking's Newest Companion: Pulse Wave Velocity. Hypertension 2018; 72:294-295. [PMID: 29967043 DOI: 10.1161/hypertensionaha.118.11276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Kathryn Sandberg
- From the Georgetown-Howard Universities Center for Clinical and Translational Science, Georgetown University, Washington, DC (K.S., S.P.W., J.G.U.)
| | - Stephen P Wright
- From the Georgetown-Howard Universities Center for Clinical and Translational Science, Georgetown University, Washington, DC (K.S., S.P.W., J.G.U.)
| | - Jason G Umans
- From the Georgetown-Howard Universities Center for Clinical and Translational Science, Georgetown University, Washington, DC (K.S., S.P.W., J.G.U.).,MedStar Health Research Institute, Hyattsville, MD (J.G.U.)
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