Mobile application to support oncology patients during treatment on patient outcomes: Evidence from a randomized controlled trial

Mapping the Evidence on the Impact of mHealth Interventions on Patient-Reported Outcomes in Patients With Breast Cancer: A Systematic Review

PURPOSE

To comprehensively synthesize the existing evidence concerning mHealth interventions for patients with breast cancer (BC).

DESIGN

On July 30, 2023, we searched PubMed, PsycINFO, and Google Scholar for articles using the following inclusion criteria: evaluation of mHealth interventions in patients with cancer, at least 30 participants with BC, randomized control trials or prospective pre-post studies, determinants of health (patient-reported outcomes [PROs] and quality of life [QoL]) as primary outcomes, interventions lasting at least 8 weeks, publication after January 2015. Publications were excluded if they evaluated telehealth or used web-based software for desktop devices only. The quality of the included studies was analyzed with the Cochrane Collaboration Risk of Bias Tool and the Methodological Index for Non-Randomized Studies.

RESULTS

We included 30 studies (20 focused on BC), encompassing 5,691 patients with cancer (median 113, IQR, 135.5). Among these, 3,606 had BC (median 99, IQR, 75). All studies contained multiple interventions, including physical activity, tailored information for self-management of the disease, and symptom tracker. Interventions showed better results on self-efficacy (3/3), QoL (10/14), and physical activity (5/7). Lifestyle programs (3/3), expert consulting (4/4), and tailored information (10/11) yielded the best results. Apps with interactive support had a higher rate of positive findings, while interventions targeted to survivors showed worse results. mHealth tools were not available to the public in most of the studies (17/30).

CONCLUSION

mHealth interventions yielded heterogeneous results on different outcomes. Identifying lack of evidence on clinical scenarios (eg, patients undergoing systemic therapy other than chemotherapy) could aid in refining strategic planning for forthcoming research endeavors within this field.

New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology

Until recently the application of artificial intelligence (AI) in precision oncology was confined to activities in drug development and had limited impact on the personalisation of therapy. Now, a number of approaches have been proposed for the personalisation of drug and cell therapies with AI applied to therapy design, planning and delivery at the patient's bedside. Some drug and cell-based therapies are already tuneable to the individual to optimise efficacy, to reduce toxicity, to adapt the dosing regime, to design combination therapy approaches and, preclinically, even to personalise the receptor design of cell therapies. Developments in AI-based healthcare are accelerating through the adoption of foundation models, and generalist medical AI models have been proposed. The application of these approaches in therapy design is already being explored and realistic short-term advances include the application to the personalised design and delivery of drugs and cell therapies. With this pace of development, the limiting step to adoption will likely be the capacity and appropriateness of regulatory frameworks. This article explores emerging concepts and new ideas for the regulation of AI-enabled personalised cancer therapies in the context of existing and in development governance frameworks.

Digital Therapeutics for Improving Effectiveness of Pharmaceutical Drugs and Biological Products: Preclinical and Clinical Studies Supporting Development of Drug + Digital Combination Therapies for Chronic Diseases

Limitations of pharmaceutical drugs and biologics for chronic diseases (e.g., medication non-adherence, adverse effects, toxicity, or inadequate efficacy) can be mitigated by mobile medical apps, known as digital therapeutics (DTx). Authorization of adjunct DTx by the US Food and Drug Administration and draft guidelines on "prescription drug use-related software" illustrate opportunities to create drug + digital combination therapies, ultimately leading towards drug-device combination products (DTx has a status of medical devices). Digital interventions (mobile, web-based, virtual reality, and video game applications) demonstrate clinically meaningful benefits for people living with Alzheimer's disease, dementia, rheumatoid arthritis, cancer, chronic pain, epilepsy, depression, and anxiety. In the respective animal disease models, preclinical studies on environmental enrichment and other non-pharmacological modalities (physical activity, social interactions, learning, and music) as surrogates for DTx "active ingredients" also show improved outcomes. In this narrative review, we discuss how drug + digital combination therapies can impact translational research, drug discovery and development, generic drug repurposing, and gene therapies. Market-driven incentives to create drug-device combination products are illustrated by Humira® (adalimumab) facing a "patent-cliff" competition with cheaper and more effective biosimilars seamlessly integrated with DTx. In conclusion, pharma and biotech companies, patients, and healthcare professionals will benefit from accelerating integration of digital interventions with pharmacotherapies.

Guided versus non-guided digital psychological interventions for cancer patients: A systematic review and meta-analysis of engagement and efficacy

OBJECTIVE

To evaluate engagement with and efficacy of guided versus non-guided digital interventions targeting psychological symptoms of cancer via a systematic review of current evidence.

METHODS

PubMed, Scopus, PsychINFO, MEDLINE, and CINAHL databases were searched. Eligible publications were randomised controlled trials of guided or non-guided digital psychological interventions used in cancer settings reporting intervention efficacy and/or engagement. Study methodological quality was assessed using the Cochrane risk of bias (RoB) tool. Random effects meta-analyses were performed on outcomes with sufficient data, with sub-group analyses of intervention type and follow-up period.

RESULTS

Forty-three studies were included. Studies varied by level of guidance, type of technology used, duration, and outcomes assessed. Most studies had a high overall RoB. Meta-analysis indicated that guided interventions significantly reduced distress, anxiety, and fatigue, while non-guided did not. For depression and quality of life, both guided and non-guided interventions produced significant improvements. Guided interventions reported higher levels of intervention engagement than non-guided.

CONCLUSIONS

Guided digital psychological interventions were likely to be more effective than non-guided ones for cancer patients, particularly in reducing distress, anxiety, and fatigue. Whilst both types were found to improve depression and life quality, guided interventions were associated with higher patient engagement. These findings suggest digital interventions could supplement traditional cancer care, warranting further research concerning long-term effects and cost-efficiency.

Supportive Digital Health Service During Cancer Chemotherapy: Single-Arm Before-and-After Feasibility Study

BACKGROUND

Digital supportive cancer care is recommended to improve patient outcomes. A portal was designed and embedded within the electronic medical record and public health portal of Iceland, consisting of symptom and needs monitoring, educational material, and messaging.

OBJECTIVE

This study aims to assess (1) portal feasibility (adoption, engagement, usability, and acceptability), (2) potential predictors of usability and acceptability, and (3) the potential impact of the portal on patient-reported outcomes.

METHODS

This was a single-arm, before-and-after feasibility study at a university hospital among patients with cancer who were undergoing chemotherapy. Participation included filling out the Edmonton Symptom Assessment System-Revised (ESASr) weekly and the Distress Thermometer and Problem List (DT&PL) 3 times; reading educational material and messaging; and completing study questionnaires. Clinical and portal engagement data were collected from medical records. Data from patients were collected electronically at baseline and 7 to 10 days after the third chemotherapy round. Usability was assessed using the System Usability Scale (score 0-100), and acceptability was assessed using a 35-item survey (score 1-5). Patient-reported outcome measures included ESASr and DT&PL; a single-item scale for quality of life, family support, and quality of care; and multi-item scales for health literacy (Brief Health Literacy Screener), health engagement (Patient Health Engagement Scale), self-care self-efficacy (Self-Care Self-Efficacy scale), symptom interference (MD Anderson Symptom Inventory), knowledge expectations (Hospital Patients' Knowledge Expectations), and received knowledge (Hospital Patients' Received Knowledge). Health care professionals were interviewed regarding portal feasibility.

RESULTS

The portal adoption rate was 72% (103/143), and the portal use rate was 76.7% (79/103) over a mean 8.6 (SD 2.7) weeks. The study completion rate was 67% (69/103). The combined completion rate of the ESASr and DT&PL was 78.4% (685/874). Patients received a mean 41 (SD 13) information leaflets; 33% (26/79) initiated messaging, 73% (58/79) received messages, and 85% (67/79) received follow-up phone calls. The mean System Usability Scale score was 72.3 (SD 14.7), indicating good usability. Usability was predicted by age (β=-.45), ESASr engagement (β=.5), symptom interference (β=.4), and received knowledge (β=.41). The mean acceptability score, 3.97 (SD 0.5), was above average and predicted by age (β=-.31), ESASr engagement (β=.37), symptom interference (β=.60), self-care self-efficacy (β=.37), and received knowledge (β=.41). ESASr scores improved for total symptom distress (P=.003; Cohen d=0.36), physical symptoms (P=.01; Cohen d=0.31), and emotional symptoms (P=.01; Cohen d=0.31). Daily symptom interference increased (P=.03; Cohen d=0.28), quality of life improved (P=.03; Cohen d=0.27) and health engagement (P=.006; Cohen d=0.35) improved, while knowledge expectations decreased (P≤.001; Cohen d=2.57). Health care professionals were positive toward the portal but called for clearer role delineation and follow-up.

CONCLUSIONS

This study supports the feasibility of a support portal and the results indicate the possibility of improving patient outcomes, but further developments are warranted.