About this trial
Meningiomas are the most common primary brain tumor, and some groups are diagnosed with higher-grade tumors and have clinically worse outcomes. This study investigates social determinants of health and individual risk factors that may be associated with meningioma.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Adults ≥18 years of age
Able to speak and read English
Diagnosed with a meningioma
Disqualifiers
Active psychiatric issues (suicidality, active psychosis, grave disability, etc.)
Inability to consent secondary to severe neurologic deficit or psychiatric distress
Inability to complete survey secondary to severe neurologic deficit or psychiatric distress
Trial population
Adult participants receiving care at the University of California, San Francisco who have been diagnosed with meningioma.
Trial design
Case-only
Cross-sectional
Treatments tested in this trial
Questionnaire
BehavioralA questionnaire will be administered in person or online
Medical Record Review
Other interventionMedical records will be reviewed for study specific data collection
Treatment groups
Trial outcomes
Primary outcomes
Identifying potential social and structural determinants of health (SSDH)
The prevalence of SSDH factors such as race and ethnicity, birthplace, relationship status, sexual orientation/gender identity, education level, socio-economic status, access to care, reproductive/menstrual history, health factors and medication use, chemical and radiation exposure, smoking history, and perceived stress for participants with meningioma will be analyzed using multilevel logistic and linear models accounting for geographical clustering.
Distribution of social and structural determinants of health
The distribution of SSDH factors across racial groups will be analyzed using multilevel logistic and linear models accounting for geographical clustering.
Identify disparities in social and structural determinants of health (SSDH)
Disparities of SSDH factors across racial groups will be analyzed using multilevel logistic and linear models accounting for geographical clustering.
Sponsors and contacts
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University of California, San Francisco
Lead sponsor
National Cancer Institute (NCI)
Collaborator