Digital phenotyping in young breast cancer patients treated with neoadjuvant chemotherapy (the NeoFit Trial): protocol for a national, multicenter single-arm trial

Lidia Delrieu, Anne-Sophie Hamy, Florence Coussy, Amyn Kassara, Bernard Asselain, Juliana Antero, Paul De Villèle, Elise Dumas, Nicolas Forstmann, Julien Guérin, Judicael Hotton, Christelle Jouannaud, Maud Milder, Armand Leopold, Adrien Sedeaud, Pauline Soibinet, Jean-François Toussaint, Vincent Vercamer, Enora Laas, Fabien Reyal, Lidia Delrieu, Anne-Sophie Hamy, Florence Coussy, Amyn Kassara, Bernard Asselain, Juliana Antero, Paul De Villèle, Elise Dumas, Nicolas Forstmann, Julien Guérin, Judicael Hotton, Christelle Jouannaud, Maud Milder, Armand Leopold, Adrien Sedeaud, Pauline Soibinet, Jean-François Toussaint, Vincent Vercamer, Enora Laas, Fabien Reyal

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.

Keywords: Activity trackers; Breast cancer; Digital; Neoadjuvant; Prevention.

Conflict of interest statement

The authors have no competing interests to declare.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Participant flow chart for the NeoFit study, France (original flow chart)

References

    1. ©Les cancers en France, Les Données, INCa, édition 2015.
    1. Konat-Bąska K, Matkowski R, Błaszczyk J, Błaszczyk D, Staszek-Szewczyk U, Piłat-Norkowska N, et al. Does Breast Cancer Increasingly Affect Younger Women? Int J Environ Res Public Health. 2020;17:4884. doi: 10.3390/ijerph17134884.
    1. Paluch-Shimon S, Cardoso F, Partridge AH, Abulkhair O, Azim HA, Bianchi-Micheli G, et al. ESO–ESMO 4th International Consensus Guidelines for Breast Cancer in Young Women (BCY4) Ann Oncol. 2020;31:674–696. doi: 10.1016/j.annonc.2020.03.284.
    1. Rubino C, Arriagada R, Delaloge S, Lê MG. Relation of risk of contralateral breast cancer to the interval since the first primary tumour. Br J Cancer. 2010;102:213–219. doi: 10.1038/sj.bjc.6605434.
    1. Voogd AC, van Gestel K, Ernst MF. Trends in survival of patients with metastatic breast cancer. J Clin Oncol Off J Am Soc Clin Oncol. 2005;23:2116. doi: 10.1200/JCO.2005.05.254.
    1. Asselain B, Barlow W, Bartlett J, Bergh J, Bergsten-Nordström E, Bliss J, et al. Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials. Lancet Oncol. 2018;19:27–39. doi: 10.1016/S1470-2045(17)30777-5.
    1. Mieog JSD, van der Hage JA, van de Velde CJH. Neoadjuvant chemotherapy for operable breast cancer. Br J Surg. 2007;94:1189–1200. doi: 10.1002/bjs.5894.
    1. Yau C, Osdoit M, van der Noordaa M, Shad S, Wei J, de Croze D, et al. Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients. Lancet Oncol. 2022;23:149–160. doi: 10.1016/S1470-2045(21)00589-1.
    1. Mauri D, Pavlidis N, Ioannidis JPA. Neoadjuvant Versus Adjuvant Systemic Treatment in Breast Cancer: A Meta-Analysis. JNCI J Natl Cancer Inst. 2005;97:188–194. doi: 10.1093/jnci/dji021.
    1. Fukuda T, Horii R, Gomi N, Miyagi Y, Takahashi S, Ito Y, et al. Accuracy of magnetic resonance imaging for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy: association with breast cancer subtype. Springerplus. 2016;5:152. doi: 10.1186/s40064-016-1800-x.
    1. Namura M, Tsunoda H, Yagata H, Hayashi N, Yoshida A, Morishita E, et al. Discrepancies Between Pathological Tumor Responses and Estimations of Complete Response by Magnetic Resonance Imaging After Neoadjuvant Chemotherapy Differ by Breast Cancer Subtype. Clin Breast Cancer. 2018;18:128–134. doi: 10.1016/j.clbc.2017.07.001.
    1. Houssami N, Macaskill P, von Minckwitz G, Marinovich ML, Mamounas E. Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy. Eur J Cancer. 2012;48:3342–3354. doi: 10.1016/j.ejca.2012.05.023.
    1. LeVasseur N, Sun J, Gondara L, Diocee R, Speers C, Lohrisch C, et al. Impact of pathologic complete response on survival after neoadjuvant chemotherapy in early-stage breast cancer: a population-based analysis. J Cancer Res Clin Oncol. 2020;146:529–536. doi: 10.1007/s00432-019-03083-y.
    1. Brandão M, Reyal F, Hamy A-S, Piccart-Gebhart M. Neoadjuvant treatment for intermediate/high-risk HER2-positive and triple-negative breast cancers: no longer an “option” but an ethical obligation. ESMO Open. 2019;4:e000515. doi: 10.1136/esmoopen-2019-000515.
    1. Reyal F, Hamy AS, Piccart MJ. Neoadjuvant treatment: the future of patients with breast cancer. ESMO Open. 2018;3:e000371. doi: 10.1136/esmoopen-2018-000371.
    1. Delrieu L, Bouaoun L, Fatouhi DE, Dumas E, Bouhnik A-D, Noelle H, et al. Patterns of Sequelae in Women with a History of Localized Breast Cancer: Results from the French VICAN Survey. Cancers. 2021;13:1161. doi: 10.3390/cancers13051161.
    1. Bower JE, Ganz PA, Desmond KA, Rowland JH, Meyerowitz BE, Belin TR. Fatigue in breast cancer survivors: occurrence, correlates, and impact on quality of life. J Clin Oncol Off J Am Soc Clin Oncol. 2000;18:743–753. doi: 10.1200/JCO.2000.18.4.743.
    1. de Kruif JTCM, Visser M, van den Berg MMGA, Derks MJM, de Boer MR, van Laarhoven HWM, et al. A longitudinal mixed methods study on changes in body weight, body composition, and lifestyle in breast cancer patients during chemotherapy and in a comparison group of women without cancer: study protocol. BMC Cancer. 2019;19:7. doi: 10.1186/s12885-018-5207-7.
    1. Arab C, Dias DPM, de Barbosa RTA, de Carvalho TD, Valenti VE, Crocetta TB, et al. Heart rate variability measure in breast cancer patients and survivors: A systematic review. Psychoneuroendocrinology. 2016;68:57–68. doi: 10.1016/j.psyneuen.2016.02.018.
    1. Helbrich H, Braun M, Hanusch C, Mueller G, Falk H, Flondor R, et al. Congruence and trajectories of device-measured and self-reported physical activity during therapy for early breast cancer. Breast Cancer Res Treat. 2021 doi: 10.1007/s10549-021-06195-7.
    1. Lahart IM, Metsios GS, Nevill AM, Carmichael AR. Physical activity, risk of death and recurrence in breast cancer survivors: A systematic review and meta-analysis of epidemiological studies. Acta Oncol Stockh Swed. 2015;54:635–654. doi: 10.3109/0284186X.2014.998275.
    1. Holmes MD, Chen WY, Feskanich D, Kroenke CH, Colditz GA. Physical activity and survival after breast cancer diagnosis. JAMA. 2005;293:2479–2486. doi: 10.1001/jama.293.20.2479.
    1. Irwin ML. Physical activity interventions for cancer survivors. Br J Sports Med. 2009;43:32–38. doi: 10.1136/bjsm.2008.053843.
    1. Ibrahim EM, Al-Homaidh A. Physical activity and survival after breast cancer diagnosis: meta-analysis of published studies. Med Oncol Northwood Lond Engl. 2011;28:753–765. doi: 10.1007/s12032-010-9536-x.
    1. Foucaut A-M, Berthouze SE, Touillaud M, Morelle M, Bourne-Branchu V, Kempf-Lépine A-S, et al. Deterioration of Physical Activity Level and Metabolic Risk Factors After Early-Stage Breast Cancer Diagnosis. Cancer Nurs. 2015;38:E1–9. doi: 10.1097/NCC.0000000000000187.
    1. IARC. Les cancers attribuables au mode de vie et à l’environnement en France métropolitaine. Lyon: International Agency for Research on Cancer. 2018. Accès à: .
    1. Bluethmann SM, Vernon SW, Gabriel KP, Murphy CC, Bartholomew LK. Taking the next step: a systematic review and meta-analysis of physical activity and behavior change interventions in recent post-treatment breast cancer survivors. Breast Cancer Res Treat. 2015;149:331–342. doi: 10.1007/s10549-014-3255-5.
    1. Perakslis E, Ginsburg GS. Digital Health—The Need to Assess Benefits, Risks, and Value. JAMA. 2020 doi: 10.1001/jama.2020.22919.
    1. Haberlin C, O’Dwyer T, Mockler D, Moran J, O’Donnell DM, Broderick J. The use of eHealth to promote physical activity in cancer survivors: a systematic review. Support Care Cancer. 2018 doi: 10.1007/s00520-018-4305-z.
    1. Torous J, Onnela J-P, Keshavan M. New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices. Transl Psychiatry. 2017;7:e1053–e1053. doi: 10.1038/tp.2017.25.
    1. Radhakrishnan K, Kim MT, Burgermaster M, Brown RA, Xie B, Bray MS, et al. The potential of digital phenotyping to advance the contributions of mobile health to self-management science. Nurs Outlook. 2020;68:548–559. doi: 10.1016/j.outlook.2020.03.007.
    1. Jaimini U, Thirunarayan K, Kalra M, Venkataraman R, Kadariya D, Sheth A. “How Is My Child’s Asthma?” Digital Phenotype and Actionable Insights for Pediatric Asthma. JMIR Pediatr Parent. 2018;1:e11988. doi: 10.2196/11988.
    1. Ienca M, Vayena E, Blasimme A. Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy. Front Med. 2018;5:13. doi: 10.3389/fmed.2018.00013.
    1. Panda N, Solsky I, Haynes AB. Redefining shared decision-making in the digital era. Eur J Surg Oncol. 2019;45:2287–2288. doi: 10.1016/j.ejso.2019.07.025.
    1. Bjordal K, de Graeff A, Fayers PM, Hammerlid E, van Pottelsberghe C, Curran D, et al. A 12 country field study of the EORTC QLQ-C30 (version 3.0) and the head and neck cancer specific module (EORTC QLQ-H&N35) in head and neck patients. EORTC Quality of Life Group. Eur J Cancer Oxf Engl. 1990;2000(36):1796–807.
    1. Weis J, Tomaszewski KA, Hammerlid E, et al. International Psychometric Validation of an EORTC Quality of Life Module Measuring Cancer Related Fatigue (EORTC QLQ-FA12). J Natl Cancer Inst. 2017;109(5). .
    1. Amireault S, Godin G, Lacombe J, Sabiston CM. The use of the Godin-Shephard Leisure-Time Physical Activity Questionnaire in oncology research: a systematic review. BMC Med Res Methodol. 2015;15:60. doi: 10.1186/s12874-015-0045-7.
    1. Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci J Can Sci Appl Au Sport. 1985;10:141–146.
    1. Connelly K, Molchan H, Bidanta R, Siddh S, Lowens B, Caine K, et al. Evaluation framework for selecting wearable activity monitors for research. Mhealth. 2021;7:6. doi: 10.21037/mhealth-19-253.
    1. Patel MS, Small DS, Harrison JD, Hilbert V, Fortunato MP, Oon AL, et al. Effect of Behaviorally Designed Gamification With Social Incentives on Lifestyle Modification Among Adults With Uncontrolled Diabetes: A Randomized Clinical Trial. JAMA Netw Open. 2021;4:e2110255. doi: 10.1001/jamanetworkopen.2021.10255.
    1. Patel MS, Small DS, Harrison JD, Fortunato MP, Oon AL, Rareshide CAL, et al. Effectiveness of Behaviorally Designed Gamification Interventions With Social Incentives for Increasing Physical Activity Among Overweight and Obese Adults Across the United States: The STEP UP Randomized Clinical Trial. JAMA Intern Med. 2019;179:1624. doi: 10.1001/jamainternmed.2019.3505.
    1. Modena BD, Bellahsen O, Nikzad N, Chieh A, Parikh N, Dufek DM, et al. Advanced and Accurate Mobile Health Tracking Devices Record New Cardiac Vital Signs. Hypertension. 2018;72:503–10. doi: 10.1161/HYPERTENSIONAHA.118.11177.
    1. Casaccia S, Revel GM, Scalise L, Cucchieri G, Rossi L. Smartwatches selection: market analysis and metrological characterization on the measurement of number of steps. In: 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA). Lausanne, Switzerland: IEEE; 2021. p. 1–5. 10.1109/MeMeA52024.2021.9478770.
    1. Frie K, Hartmann-Boyce J, Jebb S, Oke J, Aveyard P. Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis. J Med Internet Res. 2020;22:e15790. doi: 10.2196/15790.
    1. Ruggeri M, Pagan E, Bagnardi V, Bianco N, Gallerani E, Buser K, et al. Fertility concerns, preservation strategies and quality of life in young women with breast cancer: Baseline results from an ongoing prospective cohort study in selected European Centers. The Breast. 2019;47:85–92. doi: 10.1016/j.breast.2019.07.001.
    1. Ganz PA, Greendale GA, Petersen L, Kahn B, Bower JE. Breast cancer in younger women: reproductive and late health effects of treatment. J Clin Oncol Off J Am Soc Clin Oncol. 2003;21:4184–4193. doi: 10.1200/JCO.2003.04.196.
    1. Kroenke CH, Rosner B, Chen WY, Kawachi I, Colditz GA, Holmes MD. Functional impact of breast cancer by age at diagnosis. J Clin Oncol Off J Am Soc Clin Oncol. 2004;22:1849–1856. doi: 10.1200/JCO.2004.04.173.
    1. Triberti S, Savioni L, Sebri V, Pravettoni G. eHealth for improving quality of life in breast cancer patients: A systematic review. Cancer Treat Rev. 2019;74:1–14. doi: 10.1016/j.ctrv.2019.01.003.
    1. Zhang X, Pérez-Stable EJ, Bourne PE, Peprah E, Duru OK, Breen N, et al. Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century. Ethn Dis. 2017;27:95. doi: 10.18865/ed.27.2.95.
    1. Ure C, Cooper-Ryan AM, Condie J, Galpin A. Exploring Strategies for Using Social Media to Self-Manage Health Care When Living With and Beyond Breast Cancer: In-Depth Qualitative Study. J Med Internet Res. 2020;22:e16902. doi: 10.2196/16902.
    1. Cutrona SL, Roblin DW, Wagner JL, Gaglio B, Williams AE, Torres Stone R, et al. Adult Willingness to Use Email and Social Media for Peer-to-Peer Cancer Screening Communication: Quantitative Interview Study. JMIR Res Protoc. 2013;2:e52. doi: 10.2196/resprot.2886.
    1. Onnela J-P. Opportunities and challenges in the collection and analysis of digital phenotyping data. Neuropsychopharmacol Off Publ Am Coll Neuropsychopharmacol. 2020 doi: 10.1038/s41386-020-0771-3.
    1. Hudson K, Lifton R, Patrick-Lake B, Burchard EG, Coles T, Collins R, Conrad A, Desmond-Hellmann S, Dishman E, Giusti K, et al. The precision medicine initiative cohort program: building a research foundation for 21st century medicine. Bethesda: National Institutes of Health; 2105. . Accessed 13 Mar 2017.
    1. Hilbert M. Big Data for Development: A Review of Promises and Challenges. Dev Policy Rev. 2016;34:135–174. doi: 10.1111/dpr.12142.
    1. Bates DW, Saria S, Ohno-Machado L, Shah A, Escobar G. Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff Proj Hope. 2014;33:1123–1131. doi: 10.1377/hlthaff.2014.0041.
    1. Hochster HS, Niedzwiecki D. Big Data, Small Effects. J Clin Oncol Off J Am Soc Clin Oncol. 2016;34:1170–1171. doi: 10.1200/JCO.2015.65.8161.
    1. Phillips SM, Cadmus-Bertram L, Rosenberg D, Buman MP, Lynch BM. Wearable Technology and Physical Activity in Chronic Disease: Opportunities and Challenges. Am J Prev Med. 2018;54:144–150. doi: 10.1016/j.amepre.2017.08.015.

Source: PubMed

3
Předplatit