A Retrospective Study to Evaluate Treatment Patterns and Outcomes for Gastric Cancer Patients in the Peri-operative Setting

Objectif(s) de la recherche et intérêt pour la santé publique

Finalité de l'étude

Objectifs poursuivis

Domaines médicaux investigués

Bénéfices attendus

This study aims to describe real-world data on the current standard of care (SoC) for gastric cancer (GC) and gastro-oesophageal (GEJ) cancer patients receiving peri-operative treatment in France, Germany, Italy, UK, Switzerland, Canada, and Israel. This will establish a comprehensive evidence base to characterise the real world patient population, treatment patterns and outcomes allowing for the contextualisation of the impact of future treatment options, including durvalumab, on patient care, outcomes and healthcare resource utilisation.

The following objectives will be analysed:

Primary objectives: To describe demographic and clinical characteristics, peri-operative treatment patterns (modality, regimen, timing, duration, surgical procedure, and outcome), and longitudinal treatment sequencing up to the third line of therapy in metastatic settings (including surgical resection, number of lines of therapy, duration, common regimens, and reasons for change)
Secondary objectives: To estimate survival outcomes from perioperative treatment (event-free, disease-free, and overall survival, time to recurrence, and time to next treatment), tumor response and control, and describe pre-identified adverse events and complications.
Exploratory objective: To describe healthcare resource utilization rate from the start of perioperative treatment, including hospital admissions, length of stay, emergency department admissions, and outpatient visits. The study will further assess feasibility of tech-enabled data extraction using natural language processing (NLP).

All study objectives are descriptive in nature. Continuous variables will be described by the mean, standard deviation (SD), median, 1st and 3rd quartiles (Q1 and Q3 to give the interquartile range [IQR]), and 5th and 95th percentiles. Categorical variables will be described by the number and percentage of patients in each category as defined in the variable tables above. Sankey plots will be generated for treatment sequencing analysis.