Electronic patient-reported outcome monitoring system for sarcoma patients undergoing drug treatment: a development and feasibility study

BACKGROUND: Symptom and quality of life monitoring using electronic patient-reported outcomes has been widely adopted for common cancers. However, there are few such systems and studies for rare cancers such as sarcomas in Japan. We herein report a development and feasibility study of a novel system for monitoring electronic patient-reported outcomes. METHODS: Our study group, which included clinical physicians and system engineers as a collaboration between academia and industry, developed the system and conducted weekly electronic patient-reported outcome monitoring for sarcoma patients during the administration of anti-tumor agents. This prospective study was conducted from 2021 to 2023, with each patient monitored for 12 weeks to 1 year. RESULTS: Twenty-three patients were included in this study. The weekly response rate and missing rate of the electronic patient-reported outcome system were 95.7% and 0.12%, respectively. The median time required to answer the items for Performance Status, EuroQol 5-Dimension 5-Level, and 14 symptoms from the Patient-Reported Outcome-Common Terminology Criteria for Adverse Events was 11 s, 46 s, and 123 s, respectively. In a comparison between electronic and paper-based patient-reported outcomes, the intraclass correlation coefficient of the EuroQol index score was 0.92 (95%CI: 0.89-0.94) and the weighted kappa coefficient was > 0.6 for items in the weekly evaluations. The items that showed the highest rate of moderate or severe grade (at least once in each case) in the whole cohort were general pain (82.6%), fatigue (78.3%), decreased appetite (73.9%) and pain/discomfort (73.9%). CONCLUSIONS: The novel electronic patient-reported outcome monitoring system for Japanese sarcoma patients undergoing drug treatment is found to be feasible and showed excellent compliance. For the application of the system in clinical practice, an update to implement an alert function based on a precise predictive model, is warranted.