Grant: CIHR Clinician Scientist - Phase 2

Studies of uncommon diseases are challenged by small numbers of patients available for recruitment, and studies are often too small to detect important treatment effects. The Bayesian paradigm allows us to draw inferences with the data at hand, and has the ability to incorporate previous knowledge into estimates of treatment effects. This paradigm is useful in the study of uncommon diseases. An example of an uncommon disease is scleroderma. SSc is a disease that can affect the skin, joints and lungs. There is no cure. The leading cause of death for Canadians with SSc is high pressure in the lungs called pulmonary arterial hypertension (PAH). Lung transplant may help those with end-stage lung disease. But lung transplant also has risks. Using a novel research approach, this series of studies will evaluate if lung transplant improves survival in Scleroderma-PAH. We will develop innovative research methods for all researchers who study uncommon diseases.