The Use of Wearable Devices in Oncology Patients: A Systematic Review.

INTRODUCTION: The aim of this systematic review was to summarize the current literature on wearable technologies in oncology patients for the purpose of prognostication, treatment monitoring, and rehabilitation planning. METHODS: A search was conducted in Medline ALL, Cochrane Central Register of Controlled Trials, Embase, Emcare, CINAHL, Scopus, and Web of Science, up until February 2022. Articles were included if they reported on consumer grade and/or non-commercial wearable devices in the setting of either prognostication, treatment monitoring or rehabilitation. RESULTS: We found 199 studies reporting on 18 513 patients suitable for inclusion. One hundred and eleven studies used wearable device data primarily for the purposes of rehabilitation, 68 for treatment monitoring, and 20 for prognostication. The most commonly-reported brands of wearable devices were ActiGraph (71 studies; 36%), Fitbit (37 studies; 19%), Garmin (13 studies; 7%), and ActivPAL (11 studies; 6%). Daily minutes of physical activity were measured in 121 studies (61%), and daily step counts were measured in 93 studies (47%). Adherence was reported in 86 studies, and ranged from 40% to 100%; of these, 63 (74%) reported adherence in excess of 80%. CONCLUSION: Wearable devices may provide valuable data for the purposes of treatment monitoring, prognostication, and rehabilitation. Future studies should investigate live-time monitoring of collected data, which may facilitate directed interventions.

The impact of multidisciplinary cancer conferences on overall survival: a meta-analysis.

BACKGROUND: Multidisciplinary cancer conferences consist of regular meetings between diverse specialists working together to share clinical decision making in cancer care. The aim of this study was to systematically review and meta-analyze the effect of multidisciplinary cancer conference intervention on the overall survival of patients with cancer. METHODS: A systematic literature search was conducted on Ovid MEDLINE, EMBASE, and the Cochrane Controlled Register of Trials for studies published up to July 2023. Studies reporting on the impact of multidisciplinary cancer conferences on patient overall survival were included. A standard random-effects model with the inverse variance-weighted approach was used to estimate the pooled hazard ratio of mortality (multidisciplinary cancer conference vs non-multidisciplinary cancer conference) across studies, and the heterogeneity was assessed by I2. Publication bias was examined using funnel plots and the Egger test. RESULTS: A total of 134 287 patients with cancer from 59 studies were included in our analysis, with 48 467 managed by multidisciplinary cancer conferences and 85 820 in the control arm. Across all cancer types, patients managed by multidisciplinary cancer conferences had an increased overall survival compared with control patients (hazard ratio = 0.67, 95% confidence interval = 0.62 to 0.71, I2 = 84%). Median survival time was 30.2 months in the multidisciplinary cancer conference group and 19.0 months in the control group. In subgroup analysis, a positive effect of the multidisciplinary cancer conference intervention on overall survival was found in breast, colorectal, esophageal, hematologic, hepatocellular, lung, pancreatic, and head and neck cancer. CONCLUSIONS: Overall, our meta-analysis found a significant positive effect of multidisciplinary cancer conferences compared with controls. Further studies are needed to establish nuanced guidelines when optimizing multidisciplinary cancer conference integration for treating diverse patient populations.

Evaluation of clinical decision support systems in oncology: An updated systematic review.

With increasing reliance on technology in oncology, the impact of digital clinical decision support (CDS) tools needs to be examined. A systematic review update was conducted and peer-reviewed literature from 2016 to 2022 were included if CDS tools were used for live decision making and comparatively assessed quantitative outcomes. 3369 studies were screened and 19 were included in this updated review. Combined with a previous review of 24 studies, a total of 43 studies were analyzed. Improvements in outcomes were observed in 42 studies, and 34 of these were of statistical significance. Computerized physician order entry and clinical practice guideline systems comprise the greatest number of evaluated CDS tools (13 and 10 respectively), followed by those that utilize patient-reported outcomes (8), clinical pathway systems (8) and prescriber alerts for best-practice advisories (4). Our review indicates that CDS can improve guideline adherence, patient-centered care, and care delivery processes in oncology.

Recent advances in artificial intelligence applications for supportive and palliative care in cancer patients.

PURPOSE OF REVIEW: Artificial intelligence (AI) is a transformative technology that has the potential to improve and augment the clinical workflow in supportive and palliative care (SPC). The objective of this study was to provide an overview of the recent studies applying AI to SPC in cancer patients. RECENT FINDINGS: Between 2020 and 2022, 29 relevant studies were identified and categorized into two applications: predictive modeling and text screening. Predictive modeling uses machine learning and/or deep learning algorithms to make predictions regarding clinical outcomes. Most studies focused on predicting short-term mortality risk or survival within 6 months, while others used models to predict complications in patients receiving treatment and forecast the need for SPC services. Text screening typically uses natural language processing (NLP) to identify specific keywords, phrases, or documents from patient notes. Various applications of NLP were found, including the classification of symptom severity, identifying patients without documentation related to advance care planning, and monitoring online support group chat data. SUMMARY: This literature review indicates that AI tools can be used to support SPC clinicians in decision-making and reduce manual workload, leading to potentially improved care and outcomes for cancer patients. Emerging data from prospective studies supports the clinical benefit of these tools; however, more rigorous clinical validation is required before AI is routinely adopted in the SPC clinical workflow.