| 1. |
- Karlsson, Kristin E, 1975-
(författare)
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Benefits of Pharmacometric Model-Based Design and Analysis of Clinical Trials
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Quantitative pharmacokinetic-pharmacodynamic and disease progression models are the core of the science of pharmacometrics which has been identified as one of the strategies that can make drug development more effective. To adequately develop and utilize these models one needs to carefully consider the nature of the data, choice of appropriate estimation methods, model evaluation strategies, and, most importantly, the intended use of the model. The general aim of this thesis was to investigate how the use of pharmacometric models can improve the design and analysis of clinical trials within drug development. The development of pharmacometric models for clinical assessment scales in stroke and graded severity events, in this thesis, show the benefit of describing data as close to its true nature as possible, as it increases the predictive abilities and allows for mechanistic interpretations of the models. Performance of three estimation methods implemented in the mixed-effects modeling software NONMEM; 1) Laplace, 2) SAEM, and 3) Importance sampling, applied when modeling repeated time-to-event data, was investigated. The two latter methods are to be preferred if less than approximately half of the individuals experience events. In addition, predictive performance of two validation procedures, internal and external validation, was explored, with internal validation being preferred in most cases. Model-based analysis was compared to conventional methods by the use of clinical trial simulations and the power to detect a drug effect was improved with a pharmacometric design and analysis. Throughout this thesis several examples have shown the possibility of significantly reducing sample sizes in clinical trials with a pharmacometric model-based analysis. This approach will reduce time and costs spent in the development of new drug therapies, but foremost reduce the number of healthy volunteers and patients exposed to experimental drugs.
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| 2. |
- Karlsson, Kristin E, et al.
(författare)
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Comparisons of Analysis Methods for Proof-of-Concept Trials
- 2013
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Ingår i: CPT. - : Wiley. - 2163-8306. ; 2, s. e23-
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Tidskriftsartikel (refereegranskat)abstract
- Drug development struggles with high costs and time consuming processes. Hence, a need for new strategies has been accentuated by many stakeholders in drug development. This study proposes the use of pharmacometric models to rationalize drug development. Two simulated examples, within the therapeutic areas of acute stroke and type 2 diabetes, are utilized to compare a pharmacometric model–based analysis to a t-test with respect to study power of proof-of-concept (POC) trials. In all investigated examples and scenarios, the conventional statistical analysis resulted in several fold larger study sizes to achieve 80% power. For a scenario with a parallel design of one placebo group and one active dose arm, the difference between the conventional and pharmacometric approach was 4.3- and 8.4-fold, for the stroke and diabetes example, respectively. Although the model-based power depend on the model assumptions, in these scenarios, the pharmacometric model–based approach was demonstrated to permit drastic streamlining of POC trials.
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| 3. |
- Karlsson, Kristin E., et al.
(författare)
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Modeling Disease Progression in Acute Stroke Using Clinical Assessment Scales
- 2010
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 12:4, s. 683-691
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Tidskriftsartikel (refereegranskat)abstract
- This article demonstrates techniques for describing and predicting disease progression in acute stroke by modeling scores measured using clinical assessment scales, accommodating dropout as an additional source of information. Scores assessed using the National Institutes of Health Stroke Scale and the Barthel Index in acute stroke patients were used to model the time course of disease progression. Simultaneous continuous and probabilistic models for describing the nature and magnitude of score changes were developed, and used to model the trajectory of disease progression using scale scores. The models described the observed data well, and exhibited good simulation properties. Applications include longitudinal analysis of stroke scale data, clinical trial simulation, and prognostic forecasting. Based upon experience in other areas, it is likely that application of this modeling methodology will enable reductions in the number of patients needed to carry out clinical studies of treatments for acute stroke.
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| 4. |
- Karlsson, Kristin E., et al.
(författare)
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Randomized exposure-controlled trials : Impact of randomization and analysis strategies
- 2007
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Ingår i: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 64:3, s. 266-277
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Tidskriftsartikel (refereegranskat)abstract
- Aims: In the literature, five potential benefits of randomizing clinical trials on concentration levels, rather than dose, have been proposed: (i) statistical study power will increase; (ii) study power will be less sensitive to high variability in the pharmacokinetics (PK); (iii) the power of establishing an exposure-response relationship will be robust to correlations between PK and pharmacodynamics (PD); (iv) estimates of the exposure-response relationship are likely to be less biased; and (v) studies will provide a better control of exposure in situations with toxicity issues. The main aim of this study was to investigate if these five statements are valid when the trial results are evaluated using a model-based analysis. Methods: Quantitative relationships between drug dose, concentration, biomarker and clinical end-point were defined using pharmacometric models. Three randomization schemes for exposure-controlled trials, dose-controlled (RDCT), concentration-controlled (RCCT) and biomarker-controlled (RBCT), were simulated and analysed according to the models. Results: (i) The RCCT and RBCT had lower statistical power than RDCT in a model-based analysis; (ii) with a model-based analysis the power for an RDCT increased with increasing PK variability; (iii) the statistical power in a model-based analysis was robust to correlations between CL and EC 50 or Emax; (iv) under all conditions the bias was negligible (<3%); and (v) for studies with equal power RCCT could produce either more or fewer adverse events compared with an RDCT. Conclusion: Alternative randomization schemes may not have the proposed advantages if a model-based analysis is employed.
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| 5. |
- Vandenput, Liesbeth, et al.
(författare)
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A meta-analysis of previous falls and subsequent fracture risk in cohort studies
- 2024
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Ingår i: Osteoporosis International. - : Springer. - 0937-941X .- 1433-2965. ; 35:3, s. 469-494
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Tidskriftsartikel (refereegranskat)abstract
- SummaryThe relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm.IntroductionPrevious falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD).MethodsThe resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients.ResultsFalls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33–1.51) and men (HR 1.53, 95% CI 1.41–1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27–1.84) in men vs. HR 1.32 (95% CI 1.20–1.45) in women, P for interaction = 0.013). The HRs associated with previous falls decreased with age in women and with duration of follow-up in men and women for most fracture outcomes. There was no evidence of an interaction between falls and BMD for fracture risk. Subsequent risk for a major osteoporotic fracture increased with each additional previous fall in women and men.ConclusionsA previous self-reported fall confers an increased risk of fracture that is largely independent of BMD. Previous falls should be considered as an additional risk factor in future iterations of FRAX to improve fracture risk prediction.
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| 6. |
- Andersson, M. L. E., et al.
(författare)
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Diurnal variation in serum levels of cartilage oligomeric matrix protein in patients with knee osteoarthritis or rheumatoid arthritis
- 2006
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 65:11, s. 1490-1494
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To monitor changes in serum concentrations of cartilage oligomeric matrix protein (COMP) during a 24-h period to determine any diurnal variation, and to estimate the half life of COMP in the circulation in patients with symptomatic knee osteoarthritis and in those with rheumatoid arthritis. Methods: Serum samples were drawn every 4 h (7 samples/patient over 24 h) in 10 patients with knee osteoarthritis and 14 patients with rheumatoid arthritis. Osteoarthritis was defined radiographically and clinically (American College of Rheumatology (ACR) criteria) and rheumatoid arthritis according to the 1987 ACR criteria. Serum COMP was measured by sandwich ELISA. A statistical model for the diurnal variation in the COMP levels was developed using the computer program NONMEM. Results: No considerable changes in COMP levels were observed during the day between 08:00 and 21:00 in either group. A significant decrease in serum COMP was apparent during bed rest at night, reaching the lowest levels between 04:00 and 05:00 (p < 0.03 or better v all other time points) in patients with osteoarthritis and in those with rheumatoid arthritis. From the rate of decreasing serum COMP levels, a putative half life of COMP in the circulation was estimated to be 7.4 h. Conclusion: During normal daytime activities, serum COMP levels are constant. The decrease during the night indicates a rapid elimination of COMP once it has reached the circulation. The stable COMP levels during the day suggest that it is not necessary to further standardise the time of serum sampling in clinical practice.
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| 7. |
- Baverel, Paul G, et al.
(författare)
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Predictive performance of internal and external validation procedures
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Purpose: To compare estimates of predictive performance between internal (IV) and external data-splitting (EV) validation procedures. Methods: Datasets of different study size (n=6, 12, 24, 48, 96, 192, or 384 individuals) were simulated from a one compartment, first-order absorption, pharmacokinetic model and both parametric (FOCE), and nonparametric (NONP) parameter estimates were obtained in NONMEM. From these, three different validation procedures (IV, EV, and a population validation (PV)) were undertaken by means of numerical predictive checks (NPCs) to provide estimates of predictive performance, the PV procedure serving as a reference to assess performance of IV and EV. The predictive performance of NONP versus FOCE estimates was further assessed. Results: Estimates of predictive performance for predicting the median of the population distribution had in general significantly lower imprecision for IV than EV, with little bias for both procedures. For small study sizes, n=6-12 (FOCE) or n=6-24 (NONP), the tails of the population distribution were significantly more biased with IV than EV, but similar imprecision was obtained. The predictive performance for FOCE was similar or superior to that of NONP. Conclusions: Data-splitting is inferior to IV when evaluating predictive models to retain sufficient precision both in predictions and in estimates of predictive performance.
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| 8. |
- Estrada, Karol, et al.
(författare)
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Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.
- 2012
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Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 44:5, s. 491-501
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Tidskriftsartikel (refereegranskat)abstract
- Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10(-4), Bonferroni corrected), of which six reached P < 5 × 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.
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| 9. |
- Karlsson, Kristin E., et al.
(författare)
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Performance of three estimation methods in repeated time-to-event modeling
- 2011
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 13:1, s. 83-91
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Tidskriftsartikel (refereegranskat)abstract
- It is not uncommon that the outcome measurements, symptoms or side effects, of a clinical trial belong to the family of event type data, e.g., bleeding episodes or emesis events. Event data is often low in information content and the mixed-effects modeling software NONMEM has previously been shown to perform poorly with low information ordered categorical data. The aim of this investigation was to assess the performance of the Laplace method, the stochastic approximation expectation-maximization (SAEM) method, and the importance sampling method when modeling repeated time-to-event data. The Laplace method already existed, whereas the two latter methods have recently become available in NONMEM 7. A stochastic simulation and estimation study was performed to assess the performance of the three estimation methods when applied to a repeated time-to-event model with a constant hazard associated with an exponential interindividual variability. Various conditions were investigated, ranging from rare to frequent events and from low to high interindividual variability. The method performance was assessed by parameter bias and precision. Due to the lack of information content under conditions where very few events were observed, all three methods exhibit parameter bias and imprecision, however most pronounced by the Laplace method. The performance of the SAEM and importance sampling were generally higher than Laplace when the frequency of individuals with events was less than 43%, while at frequencies above that all methods were equal in performance.
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| 10. |
- Krekels, Elke H. J., et al.
(författare)
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Population Pharmacokinetics of Edoxaban in Patients with Non-Valvular Atrial Fibrillation in the ENGAGE AF-TIMI 48 Study, a Phase III Clinical Trial
- 2016
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Ingår i: Clinical Pharmacokinetics. - : Springer Science and Business Media LLC. - 0312-5963 .- 1179-1926. ; 55:9, s. 1079-1090
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Edoxaban is a novel factor Xa inhibitor. This study characterizes the population pharmacokinetics of edoxaban in patients with non-valvular atrial fibrillation (NVAF) included in the phase III ENGAGE AF-TIMI 48 study, evaluates covariates for the dose-exposure relationship in this population, and assesses the impact of protocol-specified dose reductions on exposure using simulations.Methods: Model development was performed using NONMEMA (R) and based on sparse data from the ENGAGE AF-TIMI 48 study augmented with dense data from 13 phase I studies to inform and stabilize the model. The influence of body weight (WT), creatinine clearance (CLCR), concomitant P-glycoprotein (P-gp) inhibitors, age, sex, race, and NVAF on pharmacokinetic parameters was evaluated based on statistical significance and clinical relevance.Results: A two-compartment model with first-order elimination and first-order absorption after an absorption lag-time best described the data. Apparent volume and clearance terms increased with increasing WT. Apparent renal clearance increased with increasing CLCR. Apparent non-renal, renal, and inter-compartmental clearance terms differed between phase I volunteers and NVAF patients. Asian patients were found to have increased apparent central volume of distribution, bioavailability, and total apparent clearance. Concomitant P-gp inhibitors increased the bioavailability statistically significantly, but this did not reach clinical relevance.Conclusion: Edoxaban disposition and the variability in this disposition, including influence of covariates, after oral administration were adequately characterized in patients with NVAF. The 50 % dose reduction in patients with low WT (aecurrency sign60 kg), moderate renal impairment (CLCR aecurrency sign50 mL/min), or concomitant P-gp inhibitors led to 30 % lower exposure than in the other patients.
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