Health-related quality of life dynamics: modeling insights from immunotherapy

Abstract

Understanding how treatments affect patients’ quality of life over time is crucial, but capturing the complex interactions of health factors poses a challenge for clinical and observational research. To overcome this, we have turned to simulation modeling, a method that allows for a more thorough exploration of these dynamics. Our study focuses on cancer immunotherapy, a treatment that, despite its potential to prolong survival, also comes with life-threatening risks. We evaluated the effectiveness of two strategies aimed at improving quality of life: reducing the time to treatment infusion and enhancing social support. These strategies were assessed across three different patient scenarios: those not initially eligible for treatment, patients experiencing a relapse, and patients showing a complete response. By using simulation modeling, we demonstrated how this approach can help explore the dynamics and interactions of various health factors and the impact of specific strategies.