Article (Scientific journals)
Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors.
Mlakar, Izidor; Lin, Simon; Aleksandraviča, Ilona et al.
2021In BMC Medical Informatics and Decision Making, 21 (1), p. 243
Peer Reviewed verified by ORBi
 

Files


Full Text
12911_2021_Article_1603.pdf
Publisher postprint (1.2 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Keywords :
Artificial Intelligence; Big Data; Breast Neoplasms; Cancer Survivors; Female; Humans; Multicenter Studies as Topic; Prospective Studies; Quality of Life; Retrospective Studies; Survivorship; Conversational agent; Digital intervention; Health application; Single-case experimental prospective study; Well-being
Abstract :
[en] BACKGROUND: It is encouraging to see a substantial increase in individuals surviving cancer. Even more so since most of them will have a positive effect on society by returning to work. However, many cancer survivors have unmet needs, especially when it comes to improving their quality of life (QoL). Only few survivors are able to meet all of the recommendations regarding well-being and there is a body of evidence that cancer survivors' needs often remain neglected from health policy and national cancer control plans. This increases the impact of inequalities in cancer care and adds a dangerous component to it. The inequalities affect the individual survivor, their career, along with their relatives and society as a whole. The current study will evaluate the impact of the use of big data analytics and artificial intelligence on the self-efficacy of participants following intervention supported by digital tools. The secondary endpoints include evaluation of the impact of patient trajectories (from retrospective data) and patient gathered health data on prediction and improved intervention against possible secondary disease or negative outcomes (e.g. late toxicities, fatal events). METHODS/DESIGN: The study is designed as a single-case experimental prospective study where each individual serves as its own control group with basal measurements obtained at the recruitment and subsequent measurements performed every 6 months during follow ups. The measurement will involve CASE-cancer, Patient Activation Measure and System Usability Scale. The study will involve 160 survivors (80 survivors of Breast Cancer and 80 survivors of Colorectal Cancer) from four countries, Belgium, Latvia, Slovenia, and Spain. The intervention will be implemented via a digital tool (mHealthApplication), collecting objective biomarkers (vital signs) and subjective biomarkers (PROs) with the support of a (embodied) conversational agent. Additionally, the Clinical Decision Support system (CDSS), including visualization of cohorts and trajectories will enable oncologists to personalize treatment for an efficient care plan and follow-up management. DISCUSSION: We expect that cancer survivors will significantly increase their self-efficacy following the personalized intervention supported by the m-HealthApplication compared to control measurements at recruitment. We expect to observe improvement in healthy habits, disease self-management and self-perceived QoL. Trial registration ISRCTN97617326. https://doi.org/10.1186/ISRCTN97617326 . Original Registration Date: 26/03/2021.
Disciplines :
Orthopedics, rehabilitation & sports medicine
Author, co-author :
Mlakar, Izidor
Lin, Simon
Aleksandraviča, Ilona
Arcimoviča, Krista
Eglītis, Jānis
Leja, Mārcis
Salgado Barreira, Ángel
Gómez, Jesús G.
Salgado, Mercedes
Mata, Jesús G.
Batorek, Doroteja
Horvat, Matej
Molan, Maja
Ravnik, Maja
Kaux, Jean-François  ;  Université de Liège - ULiège > Département des sciences de la motricité > Médecine physique, réadaptation et traumatologie du sport
BLERET, Valerie ;  Centre Hospitalier Universitaire de Liège - CHU > Département de gynécologie-obstétrique > Service de sénologie
LOLY, Catherine ;  Centre Hospitalier Universitaire de Liège - CHU > Département de médecine interne > Service de gastroentérologie, hépatologie, onco. digestive
Maquet, Didier ;  Université de Liège - ULiège > Département des sciences de la motricité > Département des sciences de la motricité
Sartini, Elena
Smrke, Urška
More authors (10 more) Less
Language :
English
Title :
Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors.
Publication date :
August 2021
Journal title :
BMC Medical Informatics and Decision Making
eISSN :
1472-6947
Publisher :
BioMed Central, United Kingdom
Volume :
21
Issue :
1
Pages :
243
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 01 October 2021

Statistics


Number of views
127 (8 by ULiège)
Number of downloads
143 (6 by ULiège)

Scopus citations®
 
14
Scopus citations®
without self-citations
8
OpenCitations
 
4
OpenAlex citations
 
18

Bibliography


Similar publications



Contact ORBi