The interpretation of platelet counts has to be revaluated in the light of caplacizumab. By effectively blocking platelet binding sites on VWF-multimers, the nanobody leads to a rapid normalization of the platelet count within 3 to 4 days. Most importantly, caplacizumab uncouples platelet counts from ADAMTS13 activity and thereby launches unprecedented thrombocyte dynamics, with potential pitfalls for over- and undertreatment. A relevant number of patients responds to caplacizumab with a brisk increase in platelet count, followed by a marked dip of platelets (patient on the left). This may mislead treating physicians into re-intensifying therapy, with a respective risk for adverse side-effects and complications. Taken together, these observations call for reliable descriptions and the identification of predictive parameters to predict the platelet response upon administration of caplacizumab in a large patient cohort. Here, PREDICT-2020 is designed as a retrospective study to specifically address the following aspects: * Identifying and describing clusters of platelet responses to caplacizumab * Identifying potential pitfalls for treating physicians * Predicting the individual thrombocyte response * Correlating platelet responses with individual patient outcome
Study Type
OBSERVATIONAL
Enrollment
223
Patients with immune Thrombotic Thrombocytopenic Purpura, who have been treated with caplacizumab (Cablivi®)
University Hospital of Cologne
Cologne, Germany
Reliable description and prediction of platelet responses to caplacizumab
Reliable description and prediction of platelet responses to caplacizumab employing mathematic modelling algorithms
Time frame: Enrollment
Determination of different clusters of platelet responses to caplacizumab
It will be hypothesized the existence of different clusters of caplacizumab responders during the first weeks of therapy, when ADAMTS13 activity typically is still \<10%. A detailed cluster analysis and description of thrombocyte responses to caplacizumab in a large cohort will reliably identify these different responders
Time frame: Enrollment
Correlation of platelet responses to caplacizumab with patient outcome
It will be hypothesized the existence of different clusters of caplacizumab responders during the first weeks of therapy, when ADAMTS13 activity typically is still \<10%. A detailed cluster analysis and description of thrombocyte responses to caplacizumab in a large cohort will reliably identify these different responders
Time frame: Enrollment
Risk stratification of iTTP patients based on their platelet response to caplacizumab
Description: Predicting the individual thrombocyte response to caplacizumab improves risk stratification of iTTP patients after initiation of caplacizumab therapy. An early risk stratification allows an optimal timing of monitoring intervals during the first weeks after diagnosis, which are often critical
Time frame: Enrollment
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