PhD defence Andrea Fernández Coves

Keywords: HTA, Precision oncology, Uncertainty, MCDA

"Value Assessment in Precision Oncology: Methods for Decision Support along the Life cycle of Health Technologies"

Cancer treatment is becoming increasingly personalised, with diagnostic tests and treatments tailored to the molecular characteristics of each patient and their tumour. This approach, known as precision oncology, can improve survival and quality of life, but technologies are often expensive and supported by small, uncertain evidence bases. To ensure sustainable healthcare, these costs must be weighed against potential gains. This is challenging because precision oncology involves small patient groups, complex and evolving clinical pathways, and evidence that changes over time. Moreover, its value may extend beyond outcomes traditionally considered in healthcare decisions. This thesis addressed these challenges by characterising uncertainty, exploring how assessments can be updated as evidence evolves, and examining how stakeholder perspectives can inform value assessments. It also developed a practical tool to incorporate and communicate broader value criteria transparently and consistently. Together, these approaches support more adaptive and comprehensive decision-making throughout the life cycle of precision oncology technologies.

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