Dynamic circulating biomarkers for predicting adverse events in PRaG therapy: a pooled analysis and model construction from PRaG series clinical trials

Key Points

• Key findings indicate that dynamic circulating biomarkers can effectively predict adverse events related to PRaG therapy, improving outcomes.
• The analysis involved data integration from multiple PRaG clinical trials to derive a robust predictive model with enhanced accuracy.
• Model construction incorporated various statistical methods to evaluate biomarker dynamics across diverse clinical settings and conditions.
• This work highlights the potential for early intervention based on predictive biomarkers, emphasizing the need for continuous surveillance in therapy.