Bayesian Analysis Of Tpo Levels In Immune Thrombocytopenia

Introduction: Thrombopoietin (TPO) is a haematopoietic growth factor that has a primary function in promoting the differentiation and maturation of megakaryocytes and the subsequent production of platelets. In patients with immune thrombocytopenia (ITP) TPO levels have been shown to be inappropriately low. The exact reasons for this are not well understood and are highly debated. The predominant hypothesis is that higher rates of platelet turnover in active ITP lead to an increased consumption of TPO through its binding to high-affinity receptors on the platelet cell membrane (the ‘sponge theory‘). To better understand the relationship between TPO and platelets in ITP we measured TPO levels in 67 patients with chronic ITP with a range of different platelet counts. For comparison we also measured TPO levels in 5 patients with aplastic anaemia as these patients are thrombocytopenic but lack direct immune-mediated platelet destruction. We used a Bayesian regression model to analyse the association between TPO and platelet counts, which has been shown to be more accurate with smaller sample sizes than classical gaussian regression models. We used this model to infer the probability distribution of TPO over a range of different platelet counts.