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Rotational thromboelastometry can predict the probability of bleeding events in a translational rat model of haemophilia A following gene‐based FVIIa prophylaxis
Author(s) -
Larsen Malte Selch,
Vestergaard Juul Rasmus,
Zintner Shan M.,
T. Kristensen Annemarie,
Margaritis Paris,
KjelgaardHansen Mads,
Wiinberg Bo,
Simonsson Ulrika S. H.,
Kreilgaard Mads
Publication year - 2020
Publication title -
haemophilia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.213
H-Index - 92
eISSN - 1365-2516
pISSN - 1351-8216
DOI - 10.1111/hae.13899
Subject(s) - thromboelastometry , medicine , haemophilia a , haemophilia , gene , genetics , platelet , surgery , biology
Monitoring of clinical effectiveness of bypassing agents in haemophilia patients is hampered by the lack of validated laboratory assays. Thromboelastography (TEG) and rotational thromboelastometry (ROTEM) have been evaluated for predicting clinical effectiveness of bypassing agents, however, with limited success. Aim Application of a longitudinal model‐based approach may allow for a quantitative characterization of the link between ROTEM parameters and the probability of bleeding events. Methods We analyse longitudinal data from haemophilia A rats receiving gene‐based FVIIa prophylaxis in terms of total circulatory levels of FVII/FVIIa, clotting time (CT) measured using ROTEM and the probability of bleeding events. Results Using population pharmacokinetic‐pharmacodynamic (PKPD) modelling, a PK‐CT‐repeated time‐to‐event (RTTE) model was developed composed of three submodels (a) a FVII/FVIIa PK model, (b) a PK‐CT model describing the relationship between predicted FVIIa expression and CT and (c) a RTTE model describing the probability of bleeding events as a function of CT. The developed PK‐CT‐RTTE model accurately described the vector dose‐dependent plasma concentration‐time profile of total FVII/FVIIa and the exposure‐response relationship between AAV‐derived FVIIa expression and CT. Importantly, the developed model accurately described the occurrence of bleeding events over time in a quantitative manner, revealing a linear relationship between predicted change from baseline CT and the probability of bleeding events. Conclusion Using PK‐CT‐RTTE modelling, we demonstrated that ROTEM parameters can accurately predict the probability of bleeding events in a translational animal model of haemophilia A.