Personalised decision-making in hepatocellular carcinoma: conceptual evolution over two decades

Area of Science:

• Medical Oncology
• Clinical Decision-Making
• Evidence-Based Medicine

Background:

• Evidence-based medicine (EBM) aims to integrate evidence, expertise, and patient values for individual care.
• EBM application has sometimes led to rigid algorithms, diverging from its original intent.
• Hepatocellular carcinoma (HCC) serves as a case study for EBM's evolution in personalized decision-making.

Purpose of the Study:

• To trace the evolution of personalized decision-making in HCC over two decades.
• To analyze the implications of this evolution for the future of EBM.

Main Methods:

• A narrative, conceptual review approach was employed.
• Landmark staging frameworks, guidelines, and methodological literature were selectively drawn upon.
• A schematic account of evolving clinical reasoning in HCC was constructed.

Main Results:

• HCC decision-making progressed through distinct conceptual frames: stage-centered algorithms, differential treatment effects, multiparametric deliberation, and dynamic strategies.
• The rise of immunotherapy complicated staging but reinforced bidirectional logic.
• A "Heisenberg moment" acknowledges intrinsic uncertainty in individual decisions, leading to personalized, context-sensitive care.

Conclusions:

• Hepatocellular carcinoma exemplifies personalized decision-making in complex, multidisciplinary settings.
• The future of EBM involves transparent approaches that rigorously apply evidence while embracing uncertainty and patient values.
• Balancing algorithms with personalization is key for effective, context-sensitive EBM.