| 1. |
- Abrantes, João A., et al.
(författare)
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Bayesian Forecasting Utilizing Bleeding Information to Support Dose Individualization of Factor VIII
- 2019
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Ingår i: CPT. - : Wiley. - 2163-8306. ; 8:12, s. 894-903
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Tidskriftsartikel (refereegranskat)abstract
- Bayesian forecasting for dose individualization of prophylactic factor VIII replacement therapy using pharmacokinetic samples is challenged by large interindividual variability in the bleeding risk. A pharmacokinetic‐repeated time‐to‐event model‐based forecasting approach was developed to contrast the ability to predict the future occurrence of bleeds based on individual (i) pharmacokinetic, (ii) bleeding, and (iii) pharmacokinetic, bleeding and covariate information using observed data from the Long‐Term Efficacy Open‐Label Program in Severe Hemophilia A Disease (LEOPOLD) clinical trials (172 severe hemophilia A patients taking prophylactic treatment). The predictive performance assessed by the area under receiver operating characteristic (ROC) curves was 0.67 (95% confidence interval (CI), 0.65–0.69), 0.78 (95% CI, 0.76–0.80), and 0.79 (95% CI, 0.77–0.81) for patients ≥ 12 years when using pharmacokinetics, bleeds, and all data, respectively, suggesting that individual bleed information adds value to the optimization of prophylactic dosing regimens in severe hemophilia A. Further steps to optimize the proposed tool for factor VIII dose adaptation in the clinic are required.
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| 2. |
- Abrantes, João A., et al.
(författare)
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Elucidation of Factor VIII Activity Pharmacokinetics : A Pooled Population Analysis in Patients With Hemophilia A Treated With Moroctocog Alfa
- 2017
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Ingår i: Clinical Pharmacology and Therapeutics. - : Wiley. - 0009-9236 .- 1532-6535. ; 102:6, s. 977-988
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Tidskriftsartikel (refereegranskat)abstract
- This study investigated the disposition of coagulation factor VIII activity in 754 patients with moderate to severe hemophilia A following the administration of moroctocog alfa, a B-domain deleted recombinant factor VIII. Data analyzed included patients aged 1 day to 73 years enrolled in 13 studies conducted over a period of 20 years in 25 countries. A two-compartment population pharmacokinetic model with a baseline model described the pooled data well. Body size, age, inhibitors, race, and analytical assay were identified as significant predictors of factor VIII disposition. In addition, simulations of prophylactic dosing schedules in several pediatric cohorts showed large variability and suggest that younger patients would require higher weight-adjusted doses than adolescents to achieve target factor VIII trough activity when receiving every other day or twice weekly dosing.
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| 3. |
- Abrantes, João A., et al.
(författare)
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Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data
- 2019
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Ingår i: British Journal of Clinical Pharmacology. - : John Wiley & Sons. - 0306-5251 .- 1365-2125. ; 85:6, s. 1326-1336
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Tidskriftsartikel (refereegranskat)abstract
- AIMS: This study aims to assess approaches to handle interoccasion variability (IOV) in a model-based therapeutic drug monitoring (TDM) context, using a population pharmacokinetic model of coagulation factor VIII as example.METHODS: We assessed five model-based TDM approaches: empirical Bayes estimates (EBEs) from a model including IOV, with individualized doses calculated based on individual parameters either (i) including or (ii) excluding variability related to IOV; and EBEs from a model excluding IOV by (iii) setting IOV to zero, (iv) summing variances of interindividual variability (IIV) and IOV into a single IIV term, or (v) re-estimating the model without IOV. The impact of varying IOV magnitudes (0-50%) and number of occasions/observations was explored. The approaches were compared with conventional weight-based dosing. Predictive performance was assessed with the prediction error (PE) percentiles.RESULTS: When IOV was lower than IIV, the accuracy was good for all approaches (50th percentile of the PE [P50] <7.4%), but the precision varied substantially between IOV magnitudes (P97.5 61-528%). Approach (ii) was the most precise forecasting method across a wide range of scenarios, particularly in case of sparse sampling or high magnitudes of IOV. Weight-based dosing led to less precise predictions than the model-based TDM approaches in most scenarios.CONCLUSIONS: Based on the studied scenarios and theoretical expectations, the best approach to handle IOV in model-based dose individualisation is to include IOV in the generation of the EBEs, but exclude the portion of unexplained variability related to IOV in the individual parameters used to calculate the future dose.
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| 4. |
- Abrantes, João A.
(författare)
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Pharmacometric Approaches to Improve Dose Individualization Methods in Hemophilia A
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Hemophilia A is a bleeding disorder caused by the lack of functional coagulation factor VIII (FVIII). The overall aim of this thesis was to improve dose individualization of FVIII replacement therapy in hemophilia A using pharmacometric approaches.A population pharmacokinetic (PK) model of FVIII activity following the administration of moroctocog alfa was developed based on data from a large heterogeneous cohort of moderate to severe hemophilia A patients. Body weight, age, neutralizing anti-FVIII inhibitors, race, and analytical assay were found to be significant predictors of FVIII activity PK. In addition, large inter-individual variability (IIV) and inter-occasion variability (IOV) was identified highlighting the need for dose individualization.High magnitudes of IOV are known to impair model-based therapeutic drug monitoring. Using a population PK model of FVIII activity, several approaches to handle IOV in Bayesian forecasting of individual PK parameters were assessed across a wide range of features. Considering IOV in Bayesian forecasting, but ignoring IOV in dose calculation, led to the most precise individualized doses, in particular, when sparse data was used.The dose-exposure-response relationship of FVIII replacement therapy remains unclear. A parametric repeated time-to-categorical event (RTTCE) model was developed to characterize the relationship between the dose of octocog alfa, plasma FVIII activity, bleeding frequency and severity, and covariates, using data from clinical trials. The bleeding hazard was found to decrease throughout time and to be affected by plasma FVIII activity and number of previous bleeds. Unexplained IIV in the bleeding hazard was found to be large.Bayesian forecasting based on the RTTCE model was used to predict the future occurrence of bleeds, and to contrast the predicted outcome using individual i) PK, ii) bleeding, and iii) PK, bleeding and covariate information, from data collected in clinical trials. The results support that individual bleed information can inform the optimization of prophylactic dosing regimens in severe hemophilia A patients.In summary, the pharmacometric approaches presented provide a valuable quantitative framework to improve dose individualization in hemophilia A. Furthermore, enhanced dosing has the potential to reduce bleeding frequency and to lower the high costs associated to treatment.
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| 5. |
- Abrantes, João A., et al.
(författare)
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Relationship between factor VIII activity, bleeds and individual characteristics in severe hemophilia A patients
- 2020
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Ingår i: Haematologica. - : Ferrata Storti Foundation. - 0390-6078 .- 1592-8721. ; 105:5, s. 1443-1453
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Tidskriftsartikel (refereegranskat)abstract
- Pharmacokinetic-based prophylaxis of replacement factor VIII products has been encouraged in the past years, but the exposure (factor VIII activity)-response (bleeding frequency) relationship remains unclear. The aim of this study was to characterize the relationship between factor VIII dose, plasma factor VIII activity, bleeding patterns and individual characteristics in severe hemophilia A patients. Pooled pharmacokinetic and bleeding data during prophylactic treatment with BAY 81-8973 (octocog alfa) were obtained from the three LEOPOLD trials. The population pharmacokinetics of factor VIII activity and longitudinal bleeding frequency, as well as bleeding severity, were described using nonlinear mixed effects modelling in NONMEM. In total, 183 patients (median age 22 years [range, 1-61]; weight 60 kg [11-124]) contributed with 1535 plasma factor VIII activity observations, 633 bleeds and 11 patient/study characteristics (median observation period 12 months [3.1-13.1]). A parametric repeated time-to-categorical bleed model, guided by plasma factor VIII activity from a 2-compartment population pharmacokinetic model, described the time to the occurrence of bleeds and their severity. Bleeding probability decreased with time of study, and a bleed was not found to affect the time of the next bleed. Several covariate effects were identified, including the bleeding history in the 12-month pre-study period increasing the bleeding hazard. However, unexplained inter-patient variability for the phenotypic bleeding pattern remained large (111%CV). Further studies to translate the model into a tool for dose individualization that considers the individual bleeding risk are required. Research based on a post-hoc analysis of the LEOPOLD studies (ClinicalTrials.gov identifiers NCT01029340, NCT01233258 and NCT01311648).
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| 6. |
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| 7. |
- Björkman, Sven, et al.
(författare)
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Pharmacokinetics and dose requirements of factor VIII over the age range 3-74 years : a population analysis based on 50 patients with long-term prophylactic treatment for haemophilia A
- 2009
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Ingår i: European Journal of Clinical Pharmacology. - : Springer Science and Business Media LLC. - 0031-6970 .- 1432-1041. ; 65:10, s. 989-998
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: The three aims of this investigation were (1) to develop a population pharmacokinetic (PK) model for factor VIII (FVIII) in haemophilia A patients, with estimates of inter-occasion and inter-individual variance, (2) to investigate whether appropriate dosing of FVIII for regular prophylaxis can be calculated according to patient characteristics, and (3) to present dosing recommendations for initiating prophylactic treatment. METHODS: A population PK model was developed using data from four PK studies on patients aged 7-74 years. The model was tested on sparse FVIII data from 42 outpatient visits by haemophilia prophylaxis patients aged 3-66 years. Dose requirements for prophylaxis were calculated both according to the population model and from empirical Bayesian estimates of FVIII PK in the individual patients. RESULTS: The study data were well characterised by a two-compartment PK model. Body weight, age and type of FVIII preparation (plasma-derived or recombinant) were identified as significant covariates. Inter-occasion variance was lower than inter-individual variance for both clearance and volume of the central compartment. The model could reasonably predict FVIII PK in the sparse clinical data. Model-predicted doses (based on age and body weight) to maintain a recommended 0.01 U/mL trough level of FVIII with administration on alternate days started at around 60 U/kg in the small children, decreasing to 10 U/kg or less in middle age. However, "true" dose requirements, as estimated from individual PK parameter data, showed a much greater variation. CONCLUSION: Appropriate dosing of FVIII for prophylactic treatment cannot be calculated only from body weight and/or age. However, plausible starting doses for most patients would be 1,000 U every other day. FVIII levels should then be checked for dose adjustment.
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| 8. |
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| 9. |
- Brekkan, Ari, et al.
(författare)
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Handling underlying discrete variables with bivariate mixed hidden Markov models in NONMEM
- 2019
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 46:6, s. 591-604
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Tidskriftsartikel (refereegranskat)abstract
- Non-linear mixed effects models typically deal with stochasticity in observed processes but models accounting for only observed processes may not be the most appropriate for all data. Hidden Markov models (HMMs) characterize the relationship between observed and hidden variables where the hidden variables can represent an underlying and unmeasurable disease status for example. Adding stochasticity to HMMs results in mixed HMMs (MHMMs) which potentially allow for the characterization of variability in unobservable processes. Further, HMMs can be extended to include more than one observation source and are then multivariate HMMs. In this work MHMMs were developed and applied in a chronic obstructive pulmonary disease example. The two hidden states included in the model were remission and exacerbation and two observation sources were considered, patient reported outcomes (PROs) and forced expiratory volume (FEV1). Estimation properties in the software NONMEM of model parameters were investigated with and without random and covariate effect parameters. The influence of including random and covariate effects of varying magnitudes on the parameters in the model was quantified and a power analysis was performed to compare the power of a single bivariate MHMM with two separate univariate MHMMs. A bivariate MHMM was developed for simulating and analysing hypothetical COPD data consisting of PRO and FEV1 measurements collected every week for 60 weeks. Parameter precision was high for all parameters with the exception of the variance of the transition rate dictating the transition from remission to exacerbation (relative root mean squared error [RRMSE] > 150%). Parameter precision was better with higher magnitudes of the transition probability parameters. A drug effect was included on the transition rate probability and the precision of the drug effect parameter improved with increasing magnitude of the parameter. The power to detect the drug effect was improved by utilizing a bivariate MHMM model over the univariate MHMM models where the number of subject required for 80% power was 25 with the bivariate MHMM model versus 63 in the univariate MHMM FEV1 model and > 100 in the univariate MHMM PRO model. The results advocates for the use of bivariate MHMM models when implementation is possible.
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| 10. |
- Brekkan, Ari, et al.
(författare)
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Model-based evaluation of low dose factor VIII prophylaxis in haemophilia A
- 2019
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Ingår i: Haemophilia. - : John Wiley & Sons. - 1351-8216 .- 1365-2516. ; 25:3, s. 408-415
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Tidskriftsartikel (refereegranskat)abstract
- Introduction The optimal treatment modality for haemophilia A is lifelong prophylaxis which is expensive and may not be implementable everywhere where factor VIII (FVIII) availability is limited. A less costly alternative to prophylaxis is low-dose prophylaxis (LDP) which was compared to conventional prophylaxis in this model-based simulation study. Aim To explore whether LDP is motivated where standard prophylaxis is not implementable, including evaluating LDP efficacy compared to high-dose prophylaxis and investigating the potential economic benefit of individualized dosing. Methods For a virtual adult haemophilia A population, FVIII activity levels were simulated following alternative treatment regimens, based on a published population PK model. The regimens included very LDP, LDP and conventional prophylaxis twice and thrice weekly. The annual probability of bleeding was predicted based on the weekly time spent below 1 IU/dL, using a previously published relationship. Additionally, PK-based dose individualization was evaluated to determine FVIII savings using Bayesian forecasting. Results A treatment regimen of 10 IU/kg administered thrice weekly cost 75% less than a standard high-dose regimen and was predicted to have a 5% higher median probability of annual bleeds. PK-based dose individualization may result in further cost-savings, but implementation needs benefit versus feasibility consideration. Conclusion Based on simulations, a promising LDP regimen was identified that decreased treatment costs compared with standard high-dose prophylaxis at a small increase in bleeding risk. The results indicate that LDP is advocated where the standard-of-care is on-demand treatment; however, the results should be considered in the context of any limitations of the applied models.
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