Background
Relapse is a significant concern for patients with lymphoma. Early detection can improve quality of life and survival rates. While tools to measure patient outcomes have helped lung cancer patients, similar evidence for lymphoma patients is lacking. This study investigates a web-based follow-up tool for high-risk lymphoma patients.
Objective
The aim is to show that using a web application for patient monitoring can identify at least 30% more significant health events between regular check-ups with specialists.
Methods
We conducted a randomized phase 3 trial comparing web-based follow-up (experimental group) to standard follow-up (control group). The trial was designed to detect a 30% improvement in identifying significant health events over a 24-month follow-up period after initial treatment or relapse. Patients aged 18 and older with high-risk lymphoma participated. The experimental group received a 16-symptom questionnaire via email every two weeks, and alerts were sent to the medical team based on responses.
Results
A total of 52 patients participated from July 2017 to April 2020. Most patients (27) were in the experimental group. The average follow-up time was 21.3 months, during which 121 health events were reported. The experimental group reported 69.7% of these events compared to 30.2% in the control group. On average, patients in the experimental group experienced 3.5 events, while those in the control group had 1.8 events. There were 19 relapses, with 6 in the experimental group and 13 in the control group. Statistical analysis showed no significant advantage of the web-based monitoring over the standard method, leading to the study’s early termination after enrolling 52 patients.
Conclusions
While the primary goal was not achieved, the study highlights the importance of patient-reported outcomes in identifying adverse events in cancer patients. Future studies should focus on enhancing the effectiveness of electronic monitoring methods while adhering to safety guidelines.
Opportunities for Improvement
- Define Measurable Outcomes: Establish clear goals for comparing electronic surveillance with routine monitoring.
- Select AI Tools: Choose AI solutions that meet specific clinical needs for better patient monitoring.
- Implement Step by Step: Start with pilot projects to track results and assess the real-world impact of AI solutions.
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