Inter-observer delineation variability has a relevant influence on radiomics analysis and is strongly influenced by tumor type. This leads to a reduced number of suitable imaging features.

Background: Unplanned readmissions or emergency visits (EVs) after discharge from hospital are frequent in patients in palliative care. Strategies to anticipate and prevent rapid deterioration of health are needed. Objective: Assessing feasibility and predictive ability of remote monitoring using wearables. Design: Prospective observational feasibility study in a single center. Setting/Subjects: Thirty cancer patients with an estimated life expectancy of >8 weeks to <12 months, aged >18 years and being discharged from inpatient to outpatient care were included. Measurements: Patients were provided with a smartphone, including the preinstalled ''Activity Monitoring'' application and a sensor-equipped bracelet. Follow-up was 12 weeks. Both devices recorded several features (e.g., vital signs). Visual analog scale (VAS) for pain and distress was reported once daily and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) once weekly. Statistical methods were applied to explore relationship between sensor data, self-reports, and EVs or readmissions or death. Results: Between February 2017 and May 2018, 30 patients were included. Twenty-five of 30 participants (83%) completed 12 weeks of follow-up. On average, bracelet was worn on 53% and smartphone on 85% of study days. Completion rate of daily digital questionnaires for subjective ratings was 73%. Eight unplanned hospital readmissions occurred. Ratings of pain, distress, and QLQ-C30 scores were not associated with readmission, whereas resting heart rate, resting heart rate variability, as well as speed of steps differed significantly in patients with and without readmission. Conclusions: Monitoring of palliative cancer patients using wearables is feasible. First results indicate that mobile health features might be promising biomarkers to predict unplanned readmissions.

Radiomics, tumor volume and blood biomarkers for early prediction of pseudoprogression in metastatic melanoma patients treated with immune checkpoint inhibition

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