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- Savic, Radojka M., et al.
(author)
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Implementation of a Transit Compartment Model for Describing Drug Absorption in Pharmacokinetic Studies
- 2007
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In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 34:5, s. 711-726
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Journal article (peer-reviewed)abstract
- Purpose: To compare the performance of the standard lag time model (LAG model) with the performance of an analytical solution of the transit compartment model (TRANSIT model) in the evaluation of four pharmacokinetic studies with four different compounds. Methods: The population pharmacokinetic analyses were performed using NONMEM on concentration–time data of glibenclamide, furosemide, amiloride, and moxonidine. In the TRANSIT model, the optimal number of transit compartments was estimated from the data. This was based on an analytical solution for the change in drug concentration arising from a series of transit compartments with the same first-order transfer rate between each compartment. Goodness-of-fit was assessed by the decrease in objective function value (OFV) and by inspection of diagnostic graphs. Results: With the TRANSIT model, the OFV was significantly lower and the goodness-of-fit was markedly improved in the absorption phase compared with the LAG model for all drugs. The parameter estimates related to the absorption differed between the two models while the estimates of the pharmacokinetic disposition parameters were similar. Conclusion: Based on these results, the TRANSIT model is an attractive alternative for modeling drug absorption delay, especially when a LAG model poorly describes the drug absorption phase or is numerically unstable.
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- van den Kommer, Tessa N, et al.
(author)
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Classification models for early identification of persons at risk for dementia in primary care: an evaluation in a sample aged 80 years and older.
- 2009
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In: Dementia and geriatric cognitive disorders. - : S. Karger AG. - 1421-9824 .- 1420-8008. ; 28:6, s. 567-577
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Journal article (peer-reviewed)abstract
- AIM: To evaluate previously developed classification models to make implementation in primary care possible and aid early identification of persons at risk for dementia. METHODS: Data were drawn from the OCTO-Twin study. At baseline, 521 persons >or= 80 years of age were nondemented, and for 387 a blood sample was available. Predictors of dementia were collected and analyzed in initially nondemented persons using generalized estimating equations and Cox survival analyses. RESULTS: In the basic model using predictors already known or easily obtained (basic set), the mean 2-year predictive value increased from 6.9 to 28.8% in persons with memory complaints and an MMSE score
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- Lyauk, Yassine Kamal, et al.
(author)
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Bounded Integer Modeling of Symptom Scales Specific to Lower Urinary Tract Symptoms Secondary to Benign Prostatic Hyperplasia
- 2021
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In: AAPS Journal. - : Springer. - 1550-7416. ; 23:2
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Journal article (peer-reviewed)abstract
- The International Prostate Symptom Score (IPSS), the quality of life (QoL) score, and the benign prostatic hyperplasia impact index (BII) are three different scales commonly used to assess the severity of lower urinary tract symptoms associated with benign prostatic hyperplasia (BPH-LUTS). Based on a phase II clinical trial including 403 patients with moderate to severe BPH-LUTS, the objectives of this study were to (i) develop traditional pharmacometric and bounded integer (BI) models for the IPSS, QoL score, and BII endpoints, respectively; (ii) compare the power and type I error in detecting drug effects of BI modeling with traditional methods through simulation; and (iii) obtain quantitative translation between scores on the three abovementioned scales using a BI modeling framework. All developed models described the data adequately. Pharmacometric modeling using a continuous variable (CV) approach was overall found to be the most robust in terms of type I error and power to detect a drug effect. In most cases, BI modeling showed similar performance to the CV approach, yet severely inflated type I error was generally observed when inter-individual variability (IIV) was incorporated in the BI variance function (g()). BI modeling without IIV in g() showed greater type I error control compared to the ordered categorical approach. Lastly, a multiple-scale BI model was developed and estimated the relationship between scores on the three BPH-LUTS scales with overall low uncertainty. The current study yields greater understanding of the operating characteristics of the novel BI modeling approach and highlights areas potentially requiring further improvement.
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- Lyauk, Yassine Kamal, et al.
(author)
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Integrated Item Response Theory Modeling of Multiple Patient-Reported Outcomes Assessing Lower Urinary Tract Symptoms Associated with Benign Prostatic Hyperplasia
- 2020
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In: AAPS Journal. - : SPRINGER. - 1550-7416. ; 22:5
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Journal article (peer-reviewed)abstract
- In clinical trials within lower urinary tract symptoms due to benign prostatic hyperplasia (BPH-LUTS), the International Prostate Symptom Score (IPSS) is commonly the primary efficacy outcome while the Quality of Life (QoL) score and the BPH Impact Index (BII) are common secondary efficacy markers. The current study aimed to characterize BPH-LUTS progression using responses to the IPSS, the QoL, and the BII in an integrated item response theory (IRT) framework and assess the Fisher information of each scale. The power of this approach to detect a drug effect was compared with an IRT approach considering only IPSS responses. A unidimensional and a bidimensional pharmacometric IRT model, based on item-level IPSS responses in a clinical trial with 403 patients, were extended by incorporating patients' QoL and summary BII scores over the 6-month trial period. In the developed unidimensional integrated model, the QoL score was found to be the most informative, representing 17% of the total Fisher information, while the combined information content of the seven IPSS items represented 70.6%. In the bidimensional model, "storage" and both storage and "voiding" disability drove QoL and summary BII responses, respectively. Sample size reduction of 16% to detect a drug effect at 80% power was obtained with the unidimensional integrated IRT model compared with its counterpart IPSS IRT model. This study shows that utilizing the information content across the IPSS, QoL, and BII scales in an integrated IRT framework results in a modest but meaningful increase in power to detect a drug effect.
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- Lyauk, Yassine Kamal, et al.
(author)
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Item Response Theory Modeling of the International Prostate Symptom Score in Patients with Lower Urinary Tract Symptoms Associated with Benign Prostatic Hyperplasia
- 2020
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In: AAPS Journal. - : SPRINGER. - 1550-7416. ; 22:5
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Journal article (peer-reviewed)abstract
- Item response theory (IRT) was used to characterize the time course of lower urinary tract symptoms due to benign prostatic hyperplasia (BPH-LUTS) measured by item-level International Prostate Symptom Scores (IPSS). The Fisher information content of IPSS items was determined and the power to detect a drug effect using the IRT approach was examined. Data from 403 patients with moderate-to-severe BPH-LUTS in a placebo-controlled phase II trial studying the effect of degarelix over 6 months were used for modeling. Three pharmacometric models were developed: a model for total IPSS, a unidimensional IRT model, and a bidimensional IRT model, the latter separating voiding and storage items. The population-level time course of BPH-LUTS in all models was described by initial improvement followed by worsening. In the unidimensional IRT model, the combined information content of IPSS voiding items represented 72% of the total information content, indicating that the voiding subscore may be more sensitive to changes in BPH-LUTS compared with the storage subscore. The pharmacometric models showed considerably higher power to detect a drug effect compared with a cross-sectional and while-on-treatment analysis of covariance, respectively. Compared with the sample size required to detect a drug effect at 80% power with the total IPSS model, a reduction of 5.9% and 11.7% was obtained with the unidimensional and bidimensional IPSS IRT model, respectively. Pharmacometric IRT analysis of the IPSS within BPH-LUTS may increase the precision and efficiency of treatment effect assessment, albeit to a more limited extent compared with applications in other therapeutic areas.
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