Most cited article - PubMed ID 36959613
Home-based cardio-oncology rehabilitation using a telerehabilitation platform in hematological cancer survivors: a feasibility study
PURPOSE OF REVIEW: A critical evaluation of contemporary literature regarding the role of big data, artificial intelligence, and digital technologies in precision cardio-oncology care and survivorship, emphasizing innovative and groundbreaking endeavors. RECENT FINDINGS: Artificial intelligence (AI) algorithm models can automate the risk assessment process and augment current subjective clinical decision tools. AI, particularly machine learning (ML), can identify medically significant patterns in large data sets. Machine learning in cardio-oncology care has great potential in screening, diagnosis, monitoring, and managing cancer therapy-related cardiovascular complications. To this end, large-scale imaging data and clinical information are being leveraged in training efficient AI algorithms that may lead to effective clinical tools for caring for this vulnerable population. Telemedicine may benefit cardio-oncology patients by enhancing healthcare delivery through lowering costs, improving quality, and personalizing care. Similarly, the utilization of wearable biosensors and mobile health technology for remote monitoring holds the potential to improve cardio-oncology outcomes through early intervention and deeper clinical insight. Investigations are ongoing regarding the application of digital health tools such as telemedicine and remote monitoring devices in enhancing the functional status and recovery of cancer patients, particularly those with limited access to centralized services, by increasing physical activity levels and providing access to rehabilitation services. SUMMARY: In recent years, advances in cancer survival have increased the prevalence of patients experiencing cancer therapy-related cardiovascular complications. Traditional cardio-oncology risk categorization largely relies on basic clinical features and physician assessment, necessitating advancements in machine learning to create objective prediction models using diverse data sources. Healthcare disparities may be perpetuated through AI algorithms in digital health technologies. In turn, this may have a detrimental effect on minority populations by limiting resource allocation. Several AI-powered innovative health tools could be leveraged to bridge the digital divide and improve access to equitable care.
- Keywords
- Artificial Intelligence, Cardio-Oncology, Digital health, Machine Learning,
- Publication type
- Journal Article MeSH
PURPOSE: This systematic review aims to evaluate the feasibility, safety, and adherence of home-based exercise interventions in people diagnosed with cancer. The primary research question is: Are home-based exercise interventions safe and feasible for people diagnosed with cancer? METHODS: A comprehensive search of databases including PubMed, EMBASE, and Cochrane Library was conducted in January 2025, focusing on randomized controlled trials (RCTs) that involved home-based exercise interventions people diagnosed with cancer. Studies were included if they reported on safety, feasibility, and health-related outcomes. The Physiotherapy Evidence Database (PEDro) scale was used to assess study quality and risk of bias. Adverse events were categorized by severity, and feasibility which was determined based on recruitment, withdrawal, and adherence rates. RESULTS: From 127 eligible studies involving 10,562 participants, the review found that home-based exercise interventions are generally safe, with less than 3.2% of participants experiencing exercise-related adverse events, most of which were minor. Feasibility was supported by an average recruitment rate of 50.1%, which was calculated as the proportion of eligible participants who consented to participate across the included studies. Additionally, the review found a withdrawal rate of 13.7%, and an adherence rate of 76.2%. However, significant variability in these rates were observed across the studies, highlighting the challenges in maintaining participant engagement. CONCLUSIONS: Home-based exercise interventions are feasible and safe for people diagnosed with cancer, with minor adverse events being the most common. However, there is a need for standardized protocols in reporting adverse events and better strategies to improve recruitment and adherence. IMPLICATIONS FOR CANCER SURVIVORS: These findings support the integration of home-based exercise into standard cancer care, offering a practical and safe option for enhancing the health and well-being of cancer survivors. However, the successful implementation of these programs may require additional support from exercise professionals within primary care or community settings to ensure appropriate guidance and adherence. Personalized exercise programs, developed by qualified exercise professionals such as physiotherapists or clinical exercise physiologists, and improved reporting standards are essential to optimizing these interventions.
- Keywords
- Adherence, Adverse events, Cancer survivors, Feasibility, Home-based exercise, Physical activity, Safety,
- Publication type
- Journal Article MeSH
- Review MeSH
BACKGROUND: Participation in cardio-oncological rehabilitation is low, and the effects incline to decrease after the initial rehabilitation term. Home-based exercise has the potential to enhance involvement in cardio-oncology rehabilitation and was demonstrated to be feasible, safe, and helpful in increasing short-term cardiorespiratory fitness. The lasting effects on cardiorespiratory fitness and physical activity are uncertain. Hence, a novel approach via telehealth management based on objectively measured exercise at home was proposed. OBJECTIVES: To improve self-monitoring, such as self-confidence, behavioral change, and goal setting for individual exercise, and afterward, increase long-term effects concerning cardiorespiratory fitness. DESIGN: This randomized controlled trial compares a 12-week guided home exercise telehealth intervention with a center-based exercise intervention of the same duration and intensity of exercise in lymphoma cancer survivors entering cardio-oncology rehabilitation after treatment. Participants will be instructed to exercise gradually at 60-85% of their maximum heart rate for 30-50 min 3 times a week. Participants will receive individual remote guidance (feedback about frequency, duration, and exercise intensity) by preferred contact (phone call, text message) once a week based on shared exercise data through the web platform. The primary outcome is a change in cardiorespiratory fitness expressed as maximal oxygen uptake assessed through cardiopulmonary exercise test at baseline, 12 weeks, and 1 year. Secondary objectives are quality of life, muscle strength, body composition, incidence of adverse events, and exercise adherence. This study will determine whether a telehealth model is effective and safe compared to a center-based model in cancer survivors and whether exercise prescriptions are followed by participants. Additionally, an overview of the long-term effectiveness of telehealth cardio-oncology rehabilitation will be provided. This approach aligns with the trend of moving non-complex healthcare services into the patients' home environment. TRIAL REGISTRATION: ClinicalTrials.Gov Identifier: NCT05779605.
- Keywords
- Cancer survivors, Cardio-oncology rehabilitation, Home-based exercise, Telehealth, Telemonitoring,
- Publication type
- Journal Article MeSH
PURPOSE: Exercise-based cancer rehabilitation via digital technologies can provide a promising alternative to centre-based exercise training, but data for cancer patients and survivors are limited. We conducted a meta-analysis examining the effect of telehealth exercise-based cancer rehabilitation in cancer survivors on cardiorespiratory fitness, physical activity, muscle strength, health-related quality of life, and self-reported symptoms. METHODS: PubMed, Web of Science, and reference lists of articles related to the aim were searched up to March 2023. Randomized controlled clinical trials were included comparing the effect of telehealth exercise-based cancer rehabilitation with guideline-based usual care in adult cancer survivors. The primary result was cardiorespiratory fitness expressed by peak oxygen consumption. RESULTS: A total of 1510 participants were identified, and ten randomized controlled trials (n = 855) were included in the meta-analysis. The study sample was 85% female, and the mean age was 52.7 years. Meta-analysis indicated that telehealth exercise-based cancer rehabilitation significantly improved cardiorespiratory fitness (SMD = 0.34, 95% CI 0.20, 0.49, I2 = 42%, p < 0.001) and physical activity (SMD = 0.34, 95% CI, 0.17, 0.51, I2 = 71%, p < 0.001). It was uncertain whether telehealth exercise-based cancer rehabilitation, compared with guideline-based usual care, improved the quality of life (SMD = 0.23, 95%CI, -0.07, 0.52, I2 = 67%, p = 0.14) body mass index (MD = 0.46, 95% CI, -1.19, 2.12, I2 = 60%, p = 0.58) and muscle strength (SMD = 0.07, 95% CI, -0.14, 0.28, I2 = 37%, p = 0.51). CONCLUSION: This meta-analysis showed that telehealth exercise cancer rehabilitation could significantly increase cardiorespiratory fitness and physical activity levels and decrease fatigue. It is uncertain whether these interventions improve quality of life and muscle strength. High-quality and robust studies are needed to investigate specific home-based exercise regimens in different cancer subgroups to increase the certainty of the evidence.
- Keywords
- Cancer rehabilitation, Exercise-based rehabilitation, Home-based exercise, Telehealth,
- MeSH
- Exercise MeSH
- Cardiorespiratory Fitness * MeSH
- Quality of Life * MeSH
- Middle Aged MeSH
- Humans MeSH
- Neoplasms * rehabilitation MeSH
- Cancer Survivors MeSH
- Randomized Controlled Trials as Topic MeSH
- Muscle Strength * MeSH
- Telemedicine MeSH
- Telerehabilitation MeSH
- Exercise Therapy * methods MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Meta-Analysis MeSH
- Systematic Review MeSH