Geographic Distribution of Skull Base Malignancies: Using Spatial Epidemiology to Better Understand the Etiology Rare Cancers

Background Skull base malignancies (SBMs) come in many pathologic varieties. Although recent advances have led to better outcomes for certain SBMs, many pathologies are rare and poorly understood, thus portending a poor clinical prognosis. In an effort to better understand the etiology of rare cancers, it is important to consider tools outside the conventional biomedical arsenal. Spatial epidemiology involves the geographic mapping of health trends and outcomes to investigate environmental triggers of disease. In this study, we aimed to use the tools of spatial epidemiology to examine the incidence and etiology of rare skull base malignancies.

Methods Our institution houses a large, multidisciplinary skull base clinic, serving as a tertiary referral center for skull base malignancies. We queried our electronic medical record using ICD-9 and ICD-10 codes for adult patients with a specific list of skull base malignancies from 2000 to the present. Of primary interest was the patient’s zip code leading up to and at the time of diagnosis of their SBM. Data were coded and imported into the ArcGIS geospatial mapping software (ESRI, Redlands, California, United States). Geographic maps for all individual SBMs were generated, displaying the zip code distribution of each incident case of that malignancy. Maps were analyzed, looking for spatial trends in SBM incidence and any relationships to areas of environmental concern. These included but were not limited to, industrial or chemical plants, waste dump sites, and areas of known environmental contamination.

Results Preliminary analyses unsurprisingly demonstrated clustering of SBM cases around higher population areas, though there was clustering of SBM cases in certain nonpopulous areas as well. Additional analysis is currently being conducted to determine whether there is a correlation between the patient home zip code and proximity to industrial or chemical plants, waste dump sites, and areas of known environmental contamination.

Conclusion The etiologies of rare SBMs are often difficult to understand given the paucity of cases that present at any individual center. We demonstrate that the tools of spatial epidemiology may be powerful in the investigation of rare SBMs, as identification of spatial patterns of diagnosis may aid clinicians, public health professionals, and policy makers in developing strategies to effectively manage these difficult-to-treat diseases. Furthermore, this work presents an ideal opportunity for multi-institutional collaboration, alongside state and federal cancer registries. Larger sample sizes enable more comprehensive analyses of potential environmental factors underlying SBMs. We are undertaking these collaborative efforts now.