PRECISION MEDICINE IN PARKINSON’S DISEASE: A PALLIATIVE CARE APPROACH

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder characterized by complex motor, non-motor and cognitive manifestations. Although the value of palliative care (PC) in improving quality of life for people with PD (PwP) and their families is increasingly acknowledged, its implementation remains limited. A PC pillar is Advance Care Planning (ACP), a structured process that enables individuals to articulate their goals and preferences for future medical treatment and care. Although there is currently no international consensus on the optimal timing for initiating ACP discussions, clinical indicators of disease progression—particularly cognitive decline—are widely acknowledged as important triggers for introducing ACP in PD. However, several factors continue to hinder timely identification of PwPs who may benefit from ACP. Adopting a multi-method approach, this dissertation aims to enhance the accuracy of cognitive assessment in PD by defining more accurate normative cut-offs delineate clinically meaningful phenotypes and identify timely clinical indicators that may support the structured introduction of ACP and the broader integration of PC across the disease trajectory. Chapter 2’s results support the development of updated normative data for a comprehensive neuropsychological test battery tailored to PwPs cognition. These findings address a critical limitation in current neuropsychological practice and enhance the diagnostic precision required for early identification of cognitive decline, which is a key consideration in the initiation of person-centered care planning, including ACP discussions and timely referral to PC services. Chapter 3’s results support the refinement of cognitive screening in PD through two complementary efforts: (1) the identification of optimal cut-off scores for the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), and (2) the psychometric validation of the Italian version of the Parkinson’s Disease–Cognitive Functional Rating Scale (PD-CFRS). Together, these results offer validated instruments to support earlier and more reliable cognitive staging, contributing to timely ACP and supportive care interventions. Chapter 4’s results support the identification of distinct clinical phenotypes in PD, based on the integration of cognitive, motor, and neuropsychiatric features. Using data-driven clustering techniques, this study revealed heterogeneous subtypes that differed in symptom presentation, progression patterns, and associated risks for functional decline. The resulting phenotypic profiles provide a foundation for stratified models of care, allowing clinicians to tailor monitoring and intervention strategies according to projected needs. Chapter 5’s results support a deeper understanding of end-of-life (EoL) care preferences among PwPs and their caregivers across different European contexts. The findings revealed consistent variations in European countries influenced by regulations, education, cultural and systemic factors. These insights underscore the importance of educating about ACP early in the disease course and ensuring that care planning is responsive to individual values, cultural expectations, and contextual realities. Chapter 6’s results support the identification of timely clinical indicators for the integration of PC in PD. Through qualitative interviews with healthcare professionals and bereaved caregivers, this study identified a series of clinical signals that were recognized as PC referral criteria. The findings advocate for a continuum- based approach to PC, in which early identification of such indicators prompts proactive, rather than reactive, care planning. This chapter contributes foundational knowledge for the development of disease-specific referral criteria and the implementation of structured PC pathways in PD.