Introduction: Cystic fibrosis (CF) is historically underdiagnosed in Black populations, in part due to symptom misattribution and diagnostic frameworks centered around White patient presentations. This disparity can lead to delayed diagnoses, mismanagement of symptoms, and poorer health outcomes in racially marginalized groups. Methods: This study investigates racial disparities in the diagnosis of CF using the TriNetX clinical informatics platform, with a focus on examining symptom differences, comorbid disease patterns, and treatment administration between Black and White patients. Our analysis compares CF symptoms across racial groups but also evaluates how co-occurring conditions and medication use differ between populations, offering a broader perspective on how systemic biases affect disease recognition and management.Using the TriNetX platform, we built two cohorts: Black patients with CF and White patients with CF, matched by age and sex where possible. We extracted and compared the prevalence of clinical symptoms (such as chronic cough, nasal polyps, and gastrointestinal issues), comorbidities (including asthma, diabetes, and malnutrition), and medication prescriptions (such as ivacaftor and tezacaftor). Risk differences and odds ratios were calculated to assess the magnitude of disparities, and a Kaplan-Meier survival analysis was conducted to explore potential differences in mortality outcomes. Results: Our analysis revealed marked differences and disparities between Black and White CF patients in several domains. Black patients were less likely to present with classic CF symptoms such as failure to thrive or nasal polyps and more likely to present with conditions like asthma, which may obscure a CF diagnosis. There were also significant differences in medication prescription rates, with Black patients receiving key CF treatments at lower rates. Mortality analyses showed potential differences in long-term outcomes, warranting further investigation. Discussion: By identifying population-specific clinical indicators and treatment trends, we aim to inform more inclusive diagnostic criteria and personalized care strategies. This research underscores the need for clinical frameworks that move beyond a one-size-fits-all model, contributing not only to more equitable healthcare delivery for underserved communities but also to the broader effort of advancing health equity in genetic and chronic disease management
