Advanced Clinical Biomarker Integration

Abstract

Clinical biomarkers -- measurable biological indicators that reflect normal physiology, pathological processes, or therapeutic responses -- have multiplied in number and diversity faster than clinical practice has developed frameworks for integrating them. A cardiologist managing a patient with heart failure now confronts NT-proBNP, troponin, soluble ST2, galectin-3, and emerging proteomic signatures alongside conventional haemodynamic and echocardiographic assessments; an oncologist treating NSCLC faces PD-L1 expression, TMB, EGFR mutation status, ALK rearrangement, ROS1 status, and ctDNA kinetics from liquid biopsy. The clinical value of each individual biomarker is variably established, but the evidence for how to combine them into clinical decision frameworks -- and which integration approaches most reliably improve patient outcomes -- remains fragmented. We evaluated five clinical biomarker integration frameworks applied across 68,284 patients at 20 European clinical centres in Madrid, Copenhagen, Milan, Warsaw, and Rotterdam between 2015 and 2023, covering heart failure, NSCLC, type 2 diabetes, and Alzheimer's disease. Frameworks ranged from single-biomarker-guided clinical decisions through ML-integrated multi-biomarker composite scoring with dynamic updates. Performance was assessed by our Biomarker Integration Clinical Value Score (BICVS), integrating diagnostic accuracy improvement, treatment decision improvement, outcome benefit, clinical utility, and equity of biomarker access. The ML multi-biomarker composite achieved the highest BICVS (0.924), improving 12-month outcome prediction accuracy by 22.4 percentage points over single-biomarker approaches and reducing inappropriate treatment assignments by 28.6% across all four disease areas. Liquid biopsy ctDNA integration in NSCLC and NT-proBNP trajectory modelling in heart failure were the domain-specific advances contributing most to outcome improvement.