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Q. Cathy Zhang



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Megan Ullman

University of Texas



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Althea Grant

CDC



353 – Contributed Oral Poster Presentations: Section on Statistics in Epidemiology

Estimating the Prevalence of Prophylaxis Use Among U.S. Hemophilia Patients

Sponsor: Section on Statistics in Epidemiology
Keywords: Prevlence, logistic regression, splines

Q. Cathy Zhang

Megan Ullman

University of Texas

Althea Grant

CDC

Prevalence (PR) trend estimation is essential for public health surveillance in order to understand disease burden and uptake of interventions. This paper demonstrates three approaches for estimating PR trends: (1) LOESS smoothing (2) restricted cubic splines and (3) quartic polynomial logistic regression models. Using a national dataset of approximately 8,000 hemophilia males aged 2-79 seen at 135 federally-funded US hemophilia treatment centers, we estimated the prevalence of prophylaxis use in order to demonstrate the unique features of each method of PR estimation. (Prophylaxis is the regularly scheduled administration of clotting factor concentrate to prevent bleeding into muscles, joints and tissue.) We will illustrate similarities and differences of the three methods, which can be applied to estimate indicators for other public health conditions.

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