Healthcare resource use, comorbidity, treatment and clinical outcomes for patients with primary intracranial tumors: a Swedish population-based register study

Abstract

Background: Primary intracranial tumors are relatively uncommon and heterogeneous, which make them challenging to study. We coupled data from unique Swedish population-based registries in order to deeper analyze the most common intracranical tumor types. Patient characteristics (e.g. comorbidities), care process measures like adherence to national guidelines, healthcare resource use and clinical outcome was evaluated.Materials and methods: A register-based study including several population-based registries for all patients living in Stockholm-Gotland, diagnosed with primary intracranial tumor between 2001 and 2013 was performed. Patient characteristics were captured and investigated in relation to survival, healthcare resource use (inpatient-, outpatient- and primary care) and treatment process.Results: High-grade glioma and meningioma were the most common tumor types and most patients (76%) were above the age of 40 in the patient population (n = 3664). Older age, comorbidity (Elixhauser comorbidity index) and type of tumor (high-grade glioma) were associated with lower survival rate and increased use of healthcare resources, analyzed for patients living in Stockholm (n = 3031). The analyses of healthcare use and survival showed no differences between males and females, when stratifying by tumor types. Healthcare processes were not always consistent with existing national treatment recommendations for patients with high-grade gliomas (n = 474) with regard to specified lead times, analyzed in the Swedish Brain Tumor Registry, as also observed at the national level.Conclusions: Age, comorbidity and high-grade gliomas, but not sex, were associated with decreased survival and increased use of healthcare resources. Fewer patients than aimed for in national guidelines received care according to specified lead times. The analysis of comprehensive population-based register data can be used to improve future care processes and outcomes.