Treatment for Locally Advanced Pancreatic Cancer: Optimizing patient selection and response assessment

Pancreatic ductal adenocarcinoma (PDAC) remains a challenging disease with a
persistently poor prognosis despite small advances in oncological care. In the Netherlands, approximately 3000 new cases of pancreatic cancer are diagnosed each year of whom 30% of patients present with LAPC. Systemic chemotherapy is the cornerstone in the treatment for these patients and the best prospect for long-term survival lies in the combination of iinduction chemotherapy followed by surgical resection. However, the decision-making process regarding surgery is complex. Careful patient selection and response to induction chemotherapy are essential to achieve acceptable oncological outcomes. Especially response assessment plays an important role in guiding treatment strategy for LAPC.
This thesis focuses on LAPC, addressing its clinical challenges and emphasizing the necessity of improved patient selection to identify patients who most likely benefit oncologically from therapeutic interventions, particularly surgical resection. It further investigates strategies to enhance the evaluation of treatment response and explores innovative therapeutic approaches, including local ablative therapies. Part I of this thesis focuses on optimizing patient selection by reviewing current clinical guidelines and treatment strategies for borderline resectable pancreatic cancer (BRPC) and LAPC.
This section also considers quality of life measures and analyzes pre- and post-operative factors that influence long-term survival. Part II examines the role of local therapies, evaluating their potential to improve survival outcomes when compared with systemic chemotherapy alone. Finally, Part III presents a novel diagnostic approach, investigating phosphorus-31 magnetic resonance spectroscopy (31P MRS) as a non-invasive tool to predict treatment response in pancreatic cancer. This chapter provides a summary of the key findings discussed throughout this thesis.