Early detection of symptoms using electronic patient-reported outcomes and a Fitbit to optimise care in metastatic breast cancer: study protocol of the SYMPHA trial

Abstract Background Therapeutic strategies for patients with metastatic breast cancer (mBC) are aimed at prolonging survival while preserving health-related quality of life (HRQoL). Current systemic therapies, however, are frequently associated with severe toxicities that impair HRQoL. Early detection of symptoms related to treatment-induced toxicities or disease progression, followed by adequate timely intervention, is crucial. The SYMPHA trial is designed to examine the (cost-)effectiveness of electronic patient-reported (ePRO) symptom monitoring and to explore the use of Fitbit data for early symptom detection. Methods Three randomised controlled trials (RCTs) will be conducted parallel, one in each of the three main mBC subtypes (HR+HER2-, HER2 + and TNBC), preceded by a run-in phase to correct for potential contamination bias due to intervention awareness. In the intervention arm, patients regularly report their symptoms electronically for at least six months. When the severity of symptoms exceeds a predefined threshold, patients receive an alert to contact their healthcare professional (HCP). Patients in the control and run-in arm notify symptoms as usual in standard care. All participants complete monthly electronic study questionnaires and wear a Fitbit (optionally) for at least six months. A total of 454 women diagnosed with mBC receiving chemo(immuno)therapy will be recruited in 28 Dutch hospitals. Patient information will be made available in Dutch, English, Turkish and Arabic. The primary outcome is the effect of ePRO-symptom monitoring on HRQoL (summary score). Secondary outcomes include physical functioning, symptom burden, time to next treatment, treatment intensity, therapy adherence, healthcare resource use, patient empowerment, long-term HRQoL and overall survival. Additionally, interviews will be performed with patients ( n = 30) and HCPs ( n = 10–15) to identify barriers and facilitators for implementation. Moreover, we strive for a first step towards a machine learning model for early detection of symptoms through Fitbit data. Discussion The SYMPHA trial will provide insights into the (cost-)effectiveness of ePRO-symptom monitoring, which may guide clinical integration to optimise appropriate palliative care. Additionally, the trial will provide insights into the (potential) use of Fitbit data to early detect symptoms in a less obtrusive manner. Trial registration Prospectively registered at Overview of Medical Research in the Netherlands, December 2024: NL-OMON57204.