| 1. |
- Dorlo, Thomas P C, et al.
(författare)
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[Concomitant use of proton pump inhibitors and systemic corticosteroids].
- 2013
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Ingår i: Nederlandsch tijdschrift voor geneeskunde. - 0028-2162 .- 1876-8784. ; 157:19, s. A5540-
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To provide an overview of the incidence of peptic ulcer in patients who use systemic corticosteroids and of the underlying mechanism of action, in order to determine whether there is a need for gastric protection using proton pump inhibitors in these patients.DESIGN: Systematic literature review of published meta-analyses and case-control studies, supported by relevant literature on the effects of corticosteroids in relation to the development of ulcers.METHOD: Analysis of literature was performed using the PubMed database with the search terms 'adrenal cortex hormones', 'peptic ulcer' and their synonyms. Meta-analyses and case-control studies with more than 1000 patients were included.RESULTS: The literature search resulted in 970 articles, of which 3 were classified as relevant meta-analyses and 3 as relevant case-control studies. All meta-analyses indicated that peptic ulcer is, at the most, a rare complication of systemic corticosteroid therapy occurring in less than 0.4-1.8% of patients. As the incidence is low, there is no indication for routine prophylaxis with proton pump inhibitors in combination with systemic corticosteroids. There is convincing evidence showing an increased risk of ulcers and a poorer recovery from these when NSAIDs and systemic corticosteroids are used concomitantly; this is a combination for which a proton pump inhibitor should be prescribed.CONCLUSION: Systemic corticosteroid therapy only rarely causes a peptic ulcer. Routine prophylaxis with proton pump inhibitors is therefore not indicated for short-term systemic corticosteroid use.
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| 2. |
- Keizer, Ron J., et al.
(författare)
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A model of hypertension and proteinuria in cancer patients treated with the anti-angiogenic drug E7080
- 2010
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 37:4, s. 347-363
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Tidskriftsartikel (refereegranskat)abstract
- Hypertension and proteinuria are commonly observed side-effects for anti-angiogenic drugs targeting the VEGF pathway. In most cases, hypertension can be controlled by prescription of anti-hypertensive (AH) therapy, while proteinuria often requires dose reductions or dose delays. We aimed to construct a pharmacokinetic-pharmacodynamic (PK-PD) model for hypertension and proteinuria following treatment with the experimental VEGF-inhibitor E7080, which would allow optimization of treatment, by assessing the influence of anti-hypertensive medication and dose reduction or dose delays in treating and avoiding toxicity. Data was collected from a phase I study of E7080 (n = 67), an inhibitor of multiple tyrosine kinases, among which VEGF. Blood pressure and urinalysis data were recorded weekly. Modeling was performed in NONMEM, and direct and indirect response PK-PD models were evaluated. A previously developed PK model was used. An indirect response PK-PD model described the increase in BP best, while the probability of developing proteinuria toxicity in response to exposure to E7080, was best described by a Markov transition model. This model may guide clinical interventions and provide treatment recommendations for E7080, and may serve as a template model for other drugs in this class.
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| 3. |
- Keizer, Ron J., et al.
(författare)
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Performance of Methods for Handling Missing Categorical Covariate Data in Population Pharmacokinetic Analyses
- 2012
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 14:3, s. 601-611
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Tidskriftsartikel (refereegranskat)abstract
- In population pharmacokinetic analyses, missing categorical data are often encountered. We evaluated several methods of performing covariate analyses with partially missing categorical covariate data. Missing data methods consisted of discarding data (DROP), additional effect parameter for the group with missing data (EXTRA), and mixture methods in which the mixing probability was fixed to the observed fraction of categories (MIXobs), based on the likelihood of the concentration data (MIXconc), or combined likelihood of observed covariate data and concentration data (MIXjoint). Simulations were implemented to study bias and imprecision of the methods in datasets with equal-sized and unbalanced category ratios for a binary covariate as well as datasets with non-random missingness (MNAR). Additionally, the performance and feasibility of implementation was assessed in two real datasets. At either low (10%) or high (50%) levels of missingness, all methods performed similarly well. Performance was similar for situations with unbalanced datasets (3:1 covariate distribution) and balanced datasets. In the MNAR scenario, the MIX methods showed a higher bias in the estimation of CL and covariate effect than EXTRA. All methods could be applied to real datasets, except DROP. All methods perform similarly at the studied levels of missingness, but the DROP and EXTRA methods provided less bias than the mixture methods in the case of MNAR. However, EXTRA was associated with inflated type I error rates of covariate selection, while DROP handled data inefficiently.
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| 4. |
- Keizer, Ron J., et al.
(författare)
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Two-stage model-based design of cancer phase I dose escalation trials : evaluation using the phase I program of barasertib (AZD1152)
- 2012
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Ingår i: Investigational new drugs. - : Springer Science and Business Media LLC. - 0167-6997 .- 1573-0646. ; 30:4, s. 1519-1530
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Modeling and simulation of pharmacokinetics and pharmacodynamics has previously been shown to be potentially useful in designing Phase I programs of novel anti-cancer agents that show hematological toxicity. In this analysis, a two-stage model-based trial design was evaluated retrospectively using data from the Phase I program with the aurora kinase inhibitor barasertib. Methods Data from two Phase I trials and four regimens were used (n = 79). Using barasertib-hydroxy QPA plasma concentrations and neutrophil count data from only study 1A, a PKPD model was developed and subsequently used to predict the MTD and a safe starting dose for the other trials. Results The PKPD model based on data from the first study adequately described the time course of neutrophil count fluctuation. The two-stage model-based design provided safe starting doses for subsequent phase I trials for barasertib. Predicted safe starting dose levels were higher than those used in two subsequent trials, but lower than used in the other trial. Discussion The two-stage approach could have been applied safely to define starting doses for alternative dosing strategies with barasertib. The limited improvement in efficiency for the phase I program of barasertib may have been due to the fact that starting doses for the studied phase I trials were already nearly optimal. Conclusion Application of the two-stage model-based trial design in Phase I programs with novel anti-cancer drugs that cause haematological toxicity is feasible, safe, and may lead to a reduction in the number of patient treated at sub-therapeutic dose-levels.
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| 5. |
- Soto, Elena, et al.
(författare)
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Predictive ability of a semi-mechanistic model for neutropenia in the development of novel anti-cancer agents : two case studies
- 2011
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Ingår i: Investigational new drugs. - : Springer Science and Business Media LLC. - 0167-6997 .- 1573-0646. ; 29:5, s. 984-995
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Tidskriftsartikel (refereegranskat)abstract
- In cancer chemotherapy neutropenia is a common dose-limiting toxicity. An ability to predict the neutropenic effects of cytotoxic agents based on proposed trial designs and models conditioned on previous studies would be valuable. The aim of this study was to evaluate the ability of a semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model for myelosuppression to predict the neutropenia observed in Phase I clinical studies, based on parameter estimates obtained from prior trials. Pharmacokinetic and neutropenia data from 5 clinical trials for diflomotecan and from 4 clinical trials for indisulam were used. Data were analyzed and simulations were performed using the population approach with NONMEM VI. Parameter sets were estimated under the following scenarios: (a) data from each trial independently, (b) pooled data from all clinical trials and (c) pooled data from trials performed before the tested trial. Model performance in each of the scenarios was evaluated by means of predictive (visual and numerical) checks. The semi-mechanistic PK/PD model for neutropenia showed adequate predictive ability for both anti-cancer agents. For diflomotecan, similar predictions were obtained for the three scenarios. For indisulam predictions were better when based on data from the specific study, however when the model parameters were conditioned on data from trials performed prior to a specific study, similar predictions of the drug related-neutropenia profiles and descriptors were obtained as when all data were used. This work provides further indication that modeling and simulation tools can be applied in the early stages of drug development to optimize future trials.
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| 6. |
- Zandvliet, Anthe S., et al.
(författare)
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Two-stage model-based clinical trial design to optimize phase I development of novel anticancer agents
- 2010
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Ingår i: Investigational new drugs. - : Springer Science and Business Media LLC. - 0167-6997 .- 1573-0646. ; 28:1, s. 61-75
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Tidskriftsartikel (refereegranskat)abstract
- Background The phase I program of anticancer agents usually consists of multiple dose escalation studies to select a safe dose for various administration schedules. We hypothesized that pharmacokinetic and pharmacodynamic (PK-PD) modeling of an initial phase I study (stage 1) can be used for selection of an optimal starting dose for subsequent studies (stage 2) and that a post-hoc PK-PD analysis enhances the selection of a recommended dose for phase II evaluation. The aim of this analysis was to demonstrate that this two-stage model-based design, which does not interfere in the conduct of trials, is safe, efficient and effective. Methods PK and PD data of dose escalation studies were simulated for nine compounds and for five administration regimens (stage 1) for drugs with neutropenia as dose-limiting toxicity. PK-PD models were developed for each simulated study and were used to determine a starting dose for additional phase I studies (stage 2). The model-based design was compared to a conventional study design regarding safety (number of dose-limiting toxicities (DLTs)), efficiency (number of patients treated with a dose below the recommended dose) and effectiveness (precision of dose selection). Retrospective data of the investigational anticancer drug indisulam were used to show the applicability of the model-based design. Results The model-based design was as safe as the conventional design (median number of DLTs = 3) and resulted in a reduction of the number of patients who were treated with a dose below the recommended dose (-27%, power 89%). A post-hoc model-based determination of the recommended dose for future phase II studies was more precise than the conventional selection of the recommended dose (root mean squared error 8.3% versus 30%). Conclusions A two-stage model-based phase I design is safe for anticancer agents with dose-limiting myelosuppression and may enhance the efficiency of dose escalation studies by reducing the number of patients treated with a dose below the recommended dose and by increasing the precision of dose selection for phase II evaluation.
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