Michaela Stemberger1,2, Felix Kallenbach2, Elisabeth Schmit2, Alanna McEneny-King3, Federico Germini4,5, Cindy H T Yeung4, Andrea N Edginton3, Sylvia von Mackensen6, Karin Kurnik7, Alfonso Iorio4,8. 1. Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, Munich, Germany. 2. Abteilung für Transfusionsmedizin, Zelltherapeutika und Hämostaseologie, Klinikum der Universität München, Munich, Germany. 3. School of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada. 4. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada. 5. Department of Health Sciences, Università degli Studi di Milano, Milan, Italy. 6. Institut und Poliklinik für Medizinische Psychologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany. 7. Zentrum für Pädiatrische Hämostaseologie, Dr. von Haunersches Kinderspital, Klinikum der Universität München, Munich, Germany. 8. McMaster-Bayer Chair for Clinical Epidemiology Research in Bleeding Disorders, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
Abstract
BACKGROUND: Performing individual pharmacokinetics (PK) studies in clinical practice can be simplified by adopting population PK-based profiling on limited post-infusion samples. The objective of this study was to assess the impact of population PK in tailoring prophylaxis in patients with haemophilia A. PATIENTS AND METHODS: Individual weekly treatment plans were developed considering predicted plasma factor activity levels and patients' lifestyle. Patients were trained using a visual traffic-light scheme to help modulate their level of physical activity with respect to factor infusions timing. Annualized joint bleeding rate (ABJR), haemophilia-specific quality of life questionnaire for adults (Haemo-QoL-A) and factor utilization were measured for 12 months before and after tailoring, compared within patients and analysed separately for those previously on prophylaxis (P), situational prophylaxis (SP) or on-demand (OD). RESULTS: Sixteen patients previously on P, 10 on SP and 10 on OD were enrolled in the study. The median (lower, upper quartile) ABJR changed from 2.0 (0, 4.0) to 0 (0, 1.6) for P (p = 0.003), from 2.0 (2.0, 13.6) to 3.0 (1.4, 7.2) for SP (p = 0.183) and from 16.0 (13.0, 25.0) to 2.3 (0, 5.0) for OD (p = 0.003). The Haemo-QoL-A total score improved for 58% of P, 50% of SP and 29% of OD patients. Factor utilization (IU/kg/patient/year) increased by 2,400 (121; 2,586) for P, 1,052 (308; 1,578) for SP and 2,086 (1,498; 2,576) for OD. One of 138 measurements demonstrated a factor activity level below the critical threshold of 0.03 IU/mL while the predicted level was above the threshold. CONCLUSION: Implementing tailored prophylaxis using a Bayesian forecasting approach in a routine clinical practice setting may improve haemophilia clinical outcomes. Georg Thieme Verlag KG Stuttgart · New York.
BACKGROUND: Performing individual pharmacokinetics (PK) studies in clinical practice can be simplified by adopting population PK-based profiling on limited post-infusion samples. The objective of this study was to assess the impact of population PK in tailoring prophylaxis in patients with haemophilia A. PATIENTS AND METHODS: Individual weekly treatment plans were developed considering predicted plasma factor activity levels and patients' lifestyle. Patients were trained using a visual traffic-light scheme to help modulate their level of physical activity with respect to factor infusions timing. Annualized joint bleeding rate (ABJR), haemophilia-specific quality of life questionnaire for adults (Haemo-QoL-A) and factor utilization were measured for 12 months before and after tailoring, compared within patients and analysed separately for those previously on prophylaxis (P), situational prophylaxis (SP) or on-demand (OD). RESULTS: Sixteen patients previously on P, 10 on SP and 10 on OD were enrolled in the study. The median (lower, upper quartile) ABJR changed from 2.0 (0, 4.0) to 0 (0, 1.6) for P (p = 0.003), from 2.0 (2.0, 13.6) to 3.0 (1.4, 7.2) for SP (p = 0.183) and from 16.0 (13.0, 25.0) to 2.3 (0, 5.0) for OD (p = 0.003). The Haemo-QoL-A total score improved for 58% of P, 50% of SP and 29% of OD patients. Factor utilization (IU/kg/patient/year) increased by 2,400 (121; 2,586) for P, 1,052 (308; 1,578) for SP and 2,086 (1,498; 2,576) for OD. One of 138 measurements demonstrated a factor activity level below the critical threshold of 0.03 IU/mL while the predicted level was above the threshold. CONCLUSION: Implementing tailored prophylaxis using a Bayesian forecasting approach in a routine clinical practice setting may improve haemophilia clinical outcomes. Georg Thieme Verlag KG Stuttgart · New York.
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