Validation of the Symptom Illustration Scale within an electronic Patient-Reported Outcomes Monitoring environment for metastatic breast cancer patients undergoing chemotherapy
摘要
To enhance patient outcomes, we previously developed “Hibilog”, an app that allows patients to report symptoms electronically. The paper-based Symptom Illustration Scale (SIS) was adapted using stickers and emojis to evaluate patient-reported outcomes (PROs). This study aimed to validate SIS within an electronic PRO monitoring environment for metastatic breast cancer patients undergoing chemotherapy.
MethodsThe patients used the Electronic Patient-Reported Outcomes Monitoring (ePROM) “Hibilog” application to answer a questionnaire consisting of 18 items selected from the Patient-Reported Outcome-Common Terminology Criteria for Adverse Events (PRO-CTCAE), focusing on symptoms related to breast cancer treatment, along with the corresponding SIS questionnaire. Symptom monitoring began upon registration and continued every two weeks until the completion of the study. The primary outcome was the criterion-related validity of the SIS against PRO-CTCA using the ePROM. The secondary endpoints included the response rate, response time, and missing rates for each item.
ResultsPatients (n = 75) were registered between September 2019 and March 2020. For criterion validity, the Spearman rank correlation coefficients between the PRO-CTCAE and SIS items showed high correlations (rs ≥ 0.41) for all 18 items. The κ correlation coefficient indicated a high correlation (κ > 0.41) in 11 of the 18 items (61.1%), unlike the correlation with continuous variables. In terms of response and missing rates, the SIS in ePROM demonstrated similarly high performance as our results. Additionally, the average response time was 3.0 min (SD 4.2) for SIS, with a substantially shorter response time.
ConclusionWe conclude that SIS is a useful tool in an ePROM environment for patients with MBC undergoing chemotherapy. The clinical utility of SIS in an ePRO environment needs to be validated to develop a more accurate scale for capturing patient symptoms.