Browsing Theses and Dissertations School of Pharmacy by Author "Albarmawi, Husam"
Follicular Lymphoma Stage at Diagnosis: Determinants, Prediction from Administrative Claims Data and Impact on Healthcare CostsAlbarmawi, Husam; Onukwugha, Eberechukwu (2020)Introduction: Follicular lymphoma (FL) stage is an important determinant of survival, treatment options and treatment outcomes. However, the determinants of advanced FL, defined as Ann Arbor stages III and IV, and its impact on the economic burden of FL are unknown. Moreover, for studies that rely on administrative claims data, it is not clear if advanced FL can be accurately predicted from this data source. Methods: Using the linked Surveillance, Epidemiology, and End Results-Medicare database we identified patients newly diagnosed with FL. We estimated a modified Poisson regression to explore the effect of pre-diagnosis healthcare resource utilization patterns and baseline county-level factors on FL stage. We estimated the 1-year and 5-year incremental costs of stages II-IV compared to stage I using generalized linear models. To predict FL stage from claims data, we developed and tested two random forests models. Results: We identified 11,078 patients diagnosed in 2000-2013. Half of the sample had advanced FL. Higher counts of specialist physician visits in the 3 years pre-diagnosis were associated with lower risk of advanced FL (4th quartile vs. 1st quartile: Relative Risk [RR]=0.92; 95% CI=0.86–0.99). The risk of advanced FL was 8% lower among women receiving screening mammography compared to men (RR=0.92; 95% CI=0.88–0.97). Living in counties designated as health professional shortage areas (HPSA) was associated with 7% increased risk of advanced FL (RR=1.07; 95% CI=1.00–1.14, p=0.049). In 2004-2009, FL patients with stages II, III and IV had statistically higher 1-year ($14,911; $15,106; $24,639, respectively, p<0.01) and 5-year costs ($21,590; $23,599; $34,968, respectively, p<0.01) compared to stage I patients. The random forests models exhibited poor accuracy of classifying limited and advanced FL from Medicare claims data (accuracy: ≤64%; sensitivity: ≤72%; specificity: ≤57%). Conclusions: Higher frequencies of specialist physician visits and living in counties with no HPSA can reduce the risk of presenting with advanced FL. Patients with stages II-IV incur significantly higher costs compared to stage I patients. The incremental cost increases with higher FL stage. Predicting advanced FL from claims data may not be feasible and researchers may need to rely on datasets with existing clinical information.