PURPOSE: The adoption of artificial intelligence (AI) in health care may afford new avenues for personalized and patient-centered care. This systematic review explored the role of AI in symptom monitoring for adult cancer survivors. METHODS: A comprehensive search was performed from inception to November 2023 in seven bibliographic databases and three clinical trial registries. This PROSPERO registered review (ID: CRD42023476027) assessed reports of empirical research studies of AI use in symptom monitoring (physical and psychological symptoms) across all cancer types in adults. RESULTS: A total of 18,530 reports were identified, of which 41 met review criteria and were analyzed. Included studies were predominantly published between 2021 and 2023, originated in the United States (39.0%) and Japan (14.6%), and primarily used cohort designs (80.5%), followed by cross-sectional designs (12.2%). The mean sample size was 617.14 (standard deviation = 1,401.37), with most studies primarily including multiple tumor types (31.7%) or breast cancer survivors (26.8%). Machine learning algorithms (43.9%) was the most used AI method, followed by natural language processing (29.3%), AI-driven chatbots (17.1%), and decision support tools (9.8%). The most common inputs to the AI algorithms were textual data, patient-reported symptoms, and physiologic measurements. The most examined symptom was pain (34.2% of studies), followed by fatigue and nausea (17.1% of studies each). Overall, the review showed increasing AI technology use in the prediction and monitoring of cancer symptoms. CONCLUSION: AI is being used to enhance symptom monitoring in various cancer settings. When considering integration into clinical practice, standardization of data capture, the use of analytics, investing in infrastructure, and the end-user experience should be considered for successful implementation and monitoring the improvement of patient outcomes.

Background/Objectives: This study describes the sequelae, side effects, and toxicities experienced by Canadian breast cancer survivors at a breast cancer survivorship clinic at a tertiary academic cancer centre and identifies potential risk factors which may be associated with increased side effect burden. Methods: A retrospective chart review was performed of adult patients treated at the Sunnybrook Breast Cancer Survivorship Clinic from 6 July 2022, to 30 September 2023 (n = 435). Results: Most patients (72.6%) reported at least one side effect impacting their quality of life, and a smaller majority (55.4%) reported two or more side effects. The most common symptoms experienced were anxiety (29.4%), chronic pain (23.9%), hot flashes (21.4%), and fear of recurrence (19.8%). Older age was strongly correlated with a lower likelihood of experiencing greater side effect burden (p < 0.01). Patients who underwent chemotherapy were significantly more likely to experience higher side effect burden than patients who did not. Current smokers were more likely than nonsmokers or past smokers to have a higher burden, for both physical (p < 0.01) and psychological side effects (p < 0.01). The multivariate analysis demonstrated that younger age was strongly associated with greater side effect burden, higher likelihood of psychological and physical symptoms, and greater likelihood of requiring close follow-up. Conclusions: The results highlight the need for survivorship resources tailored to survivors under the age of 55 and the importance of referring smokers to smoking cessation programs. Additional research is required to explore the significant reluctance among patients regarding discharge. Future studies should examine the acute needs of younger breast cancer survivors and investigate the impact of smoking and treatment modalities on the side effect burden.

Alkhaifi M, et al. J Breast Cancer. 2022 Aug;25(4):278-287. https://doi.org/10.4048/jbc.2022.25.e23

The adjuvant treatment landscape for hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2–) early breast cancer (EBC) is rapidly evolving, with a diverse range of therapeutic options—including endocrine therapies, bisphosphonates, ovarian function suppression, olaparib, CDK4/6 inhibitors, and emerging agents such as immunotherapy. While these advances have markedly improved patient outcomes, they also introduce challenges related to implementation, monitoring, and resource allocation. Notably, therapies like CDK4/6 inhibitors require particularly close monitoring, creating logistical and capacity challenges for medical oncologists, whose workloads are already stretched due to rising cancer incidence and treatment complexities. These challenges underscore the need for innovative care delivery solutions to ensure patients with EBC continue to receive optimal care. This paper offers a comprehensive guide—a playbook—of multidisciplinary-team-based care models designed to optimize adjuvant treatment delivery in EBC. Drawing on real-world evidence and successful applications across Canadian centers, we explore models led by nurses, nurse practitioners (NPs), general practitioners in oncology (GPO), and pharmacists. Each model leverages the unique expertise of its team to manage treatment toxicities, facilitate adherence, and enhance patient education, thereby promoting effective and sustainable care delivery. Importantly, these models are not intended to compete with one another, but rather to serve as a flexible recipe book from which breast cancer care teams can draw strategies tailored to their local resources and patient needs. By detailing implementation strategies, benefits, and challenges—in many instances supported by quantitative metrics and economic evaluations—this work aims to inspire care teams nationwide to optimize the adjuvant management of patients with HR+, HER2– EBC.