Removing the physician from the equation: Patient-controlled, home-based therapeutic drug self-monitoring of tacrolimus.

The dosing of tacrolimus, which forms the backbone of immunosuppressive therapy after kidney transplantation, is complex. This is due to its variable pharmacokinetics (both between and within individual patients), narrow therapeutic index, and the severe consequences of over- and underexposure, which may cause toxicity and rejection, respectively. Tacrolimus is, therefore, routinely dosed by means of therapeutic drug monitoring (TDM). TDM is performed for as long as the transplant functions and frequent and often lifelong sampling is therefore the rule. This puts a significant burden on patients and transplant professionals and is associated with high healthcare-associated costs. Furthermore, by its very nature, TDM is reactive and has no predictive power. Finally, the current practice of TDM does not foresee in an active role for patients themselves. Rather, the physician or pharmacist prescribes the next tacrolimus dose after obtaining the concentration measurement test results. In this article, we propose a strategy of patient-controlled, home-based, self-TDM of the immunosuppressant tacrolimus after transplantation. We argue that with the combined use of population tacrolimus pharmacokinetic models, home-based sampling by means of dried blood spotting and implementation of telemedicine, this may become a feasible approach in the near future.

Intraperitoneal pharmacokinetics of systemic oxaliplatin, 5-fluorouracil and bevacizumab in patients with colorectal peritoneal metastases.

BACKGROUND: Peritoneal metastases (PM) commonly occur in colorectal cancer patients. Systemic chemotherapy yields poor outcomes for these patients. It is hypothesised that traditional systemic chemotherapy is not very effective for this patient population. This study investigates to what extent systemic anti-cancer therapy crosses the peritoneal barrier. METHODS: In a Phase I study, eighteen patients received systemic oxaliplatin, 5-FU, and bevacizumab. Plasma and peritoneal fluid samples were collected to measure drug concentrations. A non-compartmental analysis determined the Area Under the Curve (AUC) for oxaliplatin and 5-FU in both matrices. Intraperitoneal (IP) and intravenous (IV) exposure ratios were calculated, along with the bevacizumab concentration IP/IV ratio. The relationship between tumour load and IP/IV ratios and the correlation between the IP/IV ratios of different treatments were assessed statistically. RESULTS: A total of 438 5-FU samples and 578 oxaliplatin samples were analysed in plasma and peritoneal fluid. Bevacizumab was quantified with 17 measurements in plasma and 15 measurements IP. Median IP/IV ratios were 0.143, 0.352 and 0.085 for 5-FU, oxaliplatin and bevacizumab, respectively. Oxaliplatin exhibited a longer IP half-life than 5-FU. A correlation was found between oxaliplatin and bevacizumab IP/IV ratios (R=0.69, p=0.01). No statistical correlations were found between the other investigated drugs. CONCLUSIONS: Our findings indicate that only a small percentage of systemically administered anti-cancer treatment reaches the IP cavity, questioning their efficacy against PM. This strengthens the hypothesis for repeated intraperitoneal chemotherapy to reach adequate anti-cancer drug levels.

Population pharmacokinetics of intraperitoneal irinotecan and SN-38 in patients with peritoneal metastases from colorectal origin.

Peritoneal metastases (PM) are common in patients with colorectal cancer. Patients with PM have a poor prognosis, and for those who are not eligible for cytoreductive surgery (CRS) with or without hyperthermic intraperitoneal chemotherapy (HIPEC), palliative chemotherapy is currently the only option. Recently, we conducted a phase I trial (INTERACT) in which irinotecan was administered intraperitoneally (IP) to 18 patients ineligible for CRS-HIPEC. The primary objective was to evaluate covariates influencing the PK profile of irinotecan and SN-38 after IP administration. Secondly, a population PK model was developed to support the further development of IP irinotecan by improving dosing in patients with PM. Patients were treated with IP irinotecan every 2 weeks in combination with systemic FOLFOX-bevacizumab. Irinotecan and SN-38 were measured in plasma (588 samples) and SN-38 was measured in peritoneal fluid (267 samples). Concentration-Time data were log-transformed and analyzed using NONMEM version 7.5 using FOCE+I estimation. An additive error model described the residual error, with inter-individual variability in PK parameters modeled exponentially. The final structural model consisted of five compartments. Weight was identified as a covariate influencing the SN-38 plasma volume of distribution and GGT was found to influence the SN-38 plasma clearance. This population PK model adequately described the irinotecan and SN-38 in plasma after IP administration, with weight and GGT as predictive factors. Irinotecan is converted intraperitoneal to SN-38 by carboxylesterases and the plasma bioavailability of irinotecan is low. This model will be used for the further clinical development of IP irinotecan by providing dosing strategies.

Early Identification of Patients at Risk of Cabazitaxel-induced Severe Neutropenia.

BACKGROUND: Cabazitaxel frequently causes severe neutropenia. A higher cabazitaxel systemic exposure is related to a lower nadir absolute neutrophil count (ANC). OBJECTIVE: To describe the effect of cabazitaxel systemic exposure on ANC by a population pharmacokinetic/pharmacodynamic (POP-PK/PD) model, and to identify patients at risk of severe neutropenia early in their treatment course using a PK threshold. DESIGN, SETTING, AND PARTICIPANTS: Data from five clinical studies were pooled to develop a POP-PK/PD model using NONMEM, linking both patient characteristics and cabazitaxel systemic exposure directly to ANC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A PK threshold, predictive of severe neutropenia (grade ≥3), was determined using a receiver operating characteristic curve. RESULTS AND LIMITATIONS: Ninety-six patients were included with a total of 1726 PK samples and 1081 ANCs. The POP-PK/PD model described both cabazitaxel PK and ANC accurately. A cabazitaxel plasma concentration of >4.96 ng/ml at 6 h after the start of infusion was found to be predictive of severe neutropenia, with a sensitivity of 76% and a specificity of 65%. CONCLUSIONS: Early cabazitaxel plasma levels are predictive of severe neutropenia. Implementation of the proposed PK threshold results in early identification of almost 76% of all severe neutropenias. If prospectively validated, patients at risk could benefit from prophylactic administration of granulocyte colony stimulating factors, preventing severe neutropenia in an early phase of treatment. Implementation of this threshold permits a less restricted use of the 25 mg/m2 dose, potentially increasing the therapeutic benefit. PATIENT SUMMARY: Treatment with cabazitaxel chemotherapy often causes neutropenia, leading to susceptibility to infections, which might be life threatening. We found that a systemic cabazitaxel concentration above 4.96 ng/ml 6 h after the start of infusion is predictive of the occurrence of severe neutropenia. Measurement of systemic cabazitaxel levels provides clinicians with the opportunity to prophylactically stimulate neutrophil growth.

Individualized dosing algorithms for tacrolimus in kidney transplant recipients: current status and unmet needs.

INTRODUCTION: Tacrolimus is a potent immunosuppressive drug with many side effects including nephrotoxicity and post-transplant diabetes mellitus. To limit its toxicity, therapeutic drug monitoring (TDM) is performed. However, tacrolimus' pharmacokinetics are highly variable within and between individuals, which complicates their clinical management. Despite TDM, many kidney transplant recipients will experience under- or overexposure to tacrolimus. Therefore, dosing algorithms have been developed to limit the time a patient is exposed to off-target concentrations. AREAS COVERED: Tacrolimus starting dose algorithms and models for follow-up doses developed and/or tested since 2015, encompassing both adult and pediatric populations. Literature was searched in different databases, i.e. Embase, PubMed, Web of Science, Cochrane Register, and Google Scholar, from inception to February 2023. EXPERT OPINION: Many algorithms have been developed, but few have been prospectively evaluated. These performed better than bodyweight-based starting doses, regarding the time a patient is exposed to off-target tacrolimus concentrations. No benefit in reduced tacrolimus toxicity has yet been observed. Most algorithms were developed from small datasets, contained only a few tacrolimus concentrations per person, and were not externally validated. Moreover, other matrices should be considered which might better correlate with tacrolimus toxicity than the whole-blood concentration, e.g. unbound plasma or intra-lymphocytic tacrolimus concentrations.

Towards precision dosing of aripiprazole in children and adolescents with autism spectrum disorder: Linking blood levels to weight gain and effectiveness.

AIMS: Aripiprazole is one of the most commonly prescribed antipsychotic drugs to children and adolescents worldwide, but it is associated with serious side-effects, including weight gain. This study assessed the population pharmacokinetics of aripiprazole and its active metabolite and investigated the relationship between pharmacokinetic parameters and body mass index (BMI) in children and adolescents with autism spectrum disorder (ASD) and behavioural problems. Secondary outcomes were metabolic, endocrine, extrapyramidal and cardiac side-effects and drug effectiveness. METHODS: Twenty-four children and adolescents (15 males, 9 females) aged 6-18 years were included in a 24-week prospective observational trial. Drug plasma concentrations, side-effects and drug effectiveness were measured at several time points during follow-up. Relevant pharmacokinetic covariates, including CYP2D6, CYP3A4, CYP3A5 and P-glycoprotein (ABCB1) genotypes, were determined. Nonlinear mixed-effects modelling (NONMEM®) was used for a population pharmacokinetic analysis with 92 aripiprazole and 91 dehydro-aripiprazole concentrations. Subsequently, model-based trough concentrations, maximum concentrations and 24-h area under the curves (AUCs) were analysed to predict outcomes using generalized and linear mixed-effects models. RESULTS: For both aripiprazole and dehydro-aripiprazole, one-compartment models best described the measured concentrations, with albumin and BMI as significant covariates. Of all the pharmacokinetic parameters, higher sum (aripiprazole plus dehydro-aripiprazole) trough concentrations best predicted higher BMI z-scores (P < .001) and higher Hb1Ac levels (P = .03) during follow-up. No significant association was found between sum concentrations and effectiveness. CONCLUSIONS: Our results indicate a threshold with regard to safety, which suggests that therapeutic drug monitoring of aripiprazole could potentially increase safety in children and adolescents with ASD and behavioural problems.

Population plasma and urine pharmacokinetics and the probability of target attainment of fosfomycin in healthy male volunteers.

PURPOSE: A population pharmacokinetic model of fosfomycin was developed in healthy volunteers after intravenous administration, and different dosing regimens were evaluated in terms of the probability of target attainment for Escherichia coli using both plasma and urinary pharmacokinetic/pharmacodynamic targets. METHODS: Eight healthy men received fosfomycin as both intermittent 8 g q8h and continuous infusion 1 g/h with a loading dose of 8 g in a crossover study design. Dense sampling was conducted during both regimens. Population pharmacokinetic modelling was performed using NONMEM. Monte Carlo simulations were conducted to evaluate the Probability of Target Attainment (PTA) of different dosing regimens using bactericidal (AUC24h/MIC of 83 and 75%T>MIC) and bacteriostatic (AUC24h/MIC of 25) plasma targets and bacteriostatic (AUC24h/MIC of 3994) urine target. RESULTS: A total of 176 plasma and 86 urine samples were available for PK analysis. A two-compartment model with a urine compartment best described the data. Glomerular filtration rate (GFR) showed a significant correlation with renal clearance and was implemented in the final model. Simulation results show that the dose of 4 g q8h reached 100% of PTA using bactericidal and bacteriostatic targets for MIC up to 16 mg/L. CONCLUSION: For the clinical breakpoint of 32 mg/L, the standard dosing regimen (4 g q8h) might not be sufficient to reach the bactericidal target. Higher dosing of 8 g q8h as an intermittent infusion or 0.75 g/h as a continuous infusion might be required. Continuous infusion resulted in better attainment of the %T>MIC target than intermittent infusion.

Meropenem Model-Informed Precision Dosing in the Treatment of Critically Ill Patients: Can We Use It?

The number of pharmacokinetic (PK) models of meropenem is increasing. However, the daily role of these PK models in the clinic remains unclear, especially for critically ill patients. Therefore, we evaluated the published meropenem models on real-world ICU data to assess their suitability for use in clinical practice. All models were built in NONMEM and evaluated using prediction and simulation-based diagnostics for the ability to predict the subsequent meropenem concentrations without plasma concentrations (a priori), and with plasma concentrations (a posteriori), for use in therapeutic drug monitoring (TDM). Eighteen PopPK models were included for evaluation. The a priori fit of the models, without the use of plasma concentrations, was poor, with a prediction error (PE)% of the interquartile range (IQR) exceeding the ±30% threshold. The fit improved when one to three concentrations were used to improve model predictions for TDM purposes. Two models were in the acceptable range with an IQR PE% within ±30%, when two or three concentrations were used. The role of PK models to determine the starting dose of meropenem in this population seems limited. However, certain models might be suitable for TDM-based dose adjustment using two to three plasma concentrations.

Toward model-informed precision dosing for tamoxifen: A population-pharmacokinetic model with a continuous CYP2D6 activity scale.

BACKGROUND: Tamoxifen is important in the adjuvant treatment of breast cancer. A plasma concentration of the active metabolite endoxifen of > 16 nM is associated with a lower risk of breast cancer-recurrence. Since inter-individual variability is high and > 20 % of patients do not reach endoxifen levels > 16 nM with the standard dose tamoxifen, therapeutic drug monitoring is advised. However, ideally, the correct tamoxifen dose should be known prior to start of therapy. Our aim is to develop a population pharmacokinetic (POP-PK) model incorporating a continuous CYP2D6 activity scale to support model informed precision dosing (MIPD) of tamoxifen to determine the optimal tamoxifen starting dose. METHODS: Data from eight different clinical studies were pooled (539 patients, 3661 samples) and used to develop a POP-PK model. In this model, CYP2D6 activity per allele was estimated on a continuous scale. After inclusion of covariates, the model was subsequently validated using an independent external dataset (378 patients). Thereafter, dosing cut-off values for MIPD were determined. RESULTS: A joint tamoxifen/endoxifen POP-PK model was developed describing the endoxifen formation rate. Using a continuous CYP2D6 activity scale, variability in predicting endoxifen levels was decreased by 37 % compared to using standard CYP2D6 genotype predicted phenotyping. After external validation and determination of dosing cut-off points, MIPD could reduce the proportion of patients with subtherapeutic endoxifen levels at from 22.1 % toward 4.8 %. CONCLUSION: Implementing MIPD from the start of tamoxifen treatment with this POP-PK model can reduce the proportion of patients with subtherapeutic endoxifen levels at steady-state to less than 5 %.

Population Pharmacokinetic Modelling of Intravenous Immunoglobulin Treatment in Patients with Guillain-Barré Syndrome.

BACKGROUND AND OBJECTIVE: Intravenous immunoglobulin (IVIg) at a standard dosage is the treatment of choice for Guillain-Barré syndrome. The pharmacokinetics, however, is highly variable between patients, and a rapid clearance of IVIg is associated with poor recovery. We aimed to develop a model to predict the pharmacokinetics of a standard 5-day IVIg course (0.4 g/kg/day) in patients with Guillain-Barré syndrome. METHODS: Non-linear mixed-effects modelling software (NONMEM®) was used to construct a pharmacokinetic model based on a model-building cohort of 177 patients with Guillain-Barré syndrome, with a total of 589 sequential serum samples tested for total immunoglobulin G (IgG) levels, and evaluated on an independent validation cohort that consisted of 177 patients with Guillain-Barré syndrome with 689 sequential serum samples. RESULTS: The final two-compartment model accurately described the daily increment in serum IgG levels during a standard IVIg course; the initial rapid fall and then a gradual decline to steady-state levels thereafter. The covariates that increased IgG clearance were a more severe disease (as indicated by the Guillain-Barré syndrome disability score) and concomitant methylprednisolone treatment. When the current dosing regimen was simulated, the percentage of patients who reached a target ∆IgG > 7.3 g/L at 2 weeks decreased from 74% in mildly affected patients to only 33% in the most severely affected and mechanically ventilated patients (Guillain-Barré syndrome disability score of 5). CONCLUSIONS: This is the first population-pharmacokinetic model for standard IVIg treatment in Guillain-Barré syndrome. The model provides a new tool to predict the pharmacokinetics of alternative regimens of IVIg in Guillain-Barré syndrome to design future trials and personalise treatment.

Pharmacokinetics of Haloperidol in Critically Ill Patients: Is There an Association with Inflammation?

Haloperidol is considered the first-line treatment for delirium in critically ill patients. However, clinical evidence of efficacy is lacking and no pharmacokinetic studies have been performed in intensive care unit (ICU) patients. The aim of this study was to establish a pharmacokinetic model to describe the PK in this population to improve insight into dosing. One hundred and thirty-nine samples from 22 patients were collected in a single-center study in adults with ICU delirium who were treated with low-dose intravenous haloperidol (3-6 mg per day). We conducted a population pharmacokinetic analysis using Nonlinear Mixed Effects Modelling (NONMEM). A one-compartment model best described the data. The mean population estimates were 51.7 L/h (IIV 42.1%) for clearance and 1490 L for the volume of distribution. The calculated half-life was around 22 h (12.3-29.73 h) for an average patient. A negative correlation between C-Reactive Protein (CRP) and haloperidol clearance was observed, where clearance decreased significantly with increasing CRP up to a CRP concentration of 100 mg/L. This is the first step towards haloperidol precision dosing in ICU patients and our results indicate a possible role of inflammation.

Population Pharmacokinetics of Oxycodone and Metabolites in Patients with Cancer-Related Pain.

Oxycodone is frequently used for treating cancer-related pain, while not much is known about the factors that influence treatment outcomes in these patients. We aim to unravel these factors by developing a population-pharmacokinetic model to assess the pharmacokinetics of oxycodone and its metabolites in cancer patients, and to associate this with pain scores, and adverse events. Hospitalized patients with cancer-related pain, who were treated with oral oxycodone, could participate. Pharmacokinetic samples and patient-reported pain scores and occurrence and severity of nine adverse events were taken every 12 h. In 28 patients, 302 pharmacokinetic samples were collected. A one-compartment model for oxycodone and each metabolite best described oxycodone, nor-oxycodone, and nor-oxymorphone pharmacokinetics. Furthermore, oxycodone exposure was not associated with average and maximal pain scores, and oxycodone, nor-oxycodone, and nor-oxymorphone exposure were not associated with adverse events (all p > 0.05). This is the first model to describe the pharmacokinetics of oxycodone including the metabolites nor-oxycodone and nor-oxymorphone in hospitalized patients with cancer pain. Additional research, including more patients and a more timely collection of pharmacodynamic data, is needed to further elucidate oxycodone (metabolite) pharmacokinetic/pharmacodynamic relationships. This model is an important starting point for further studies to optimize oxycodone dosing regiments in patients with cancer-related pain.

Prospective real-world study on the pharmacokinetics of pembrolizumab in patients with solid tumors.

BACKGROUND: Dosing schemes of pembrolizumab (anti-programmed cell death protein 1 monoclonal antibody) are solely based on pharmacokinetic (PK) modelling derived from phase I-III trials. The current study aimed to determine factors affecting PK and its relationship with clinical outcome in the real-world setting. METHODS: Advanced-stage cancer patients, who were treated with pembrolizumab monotherapy (2 mg/kg Q3W or 200 mg flat Q3W), were prospectively included for serial sampling to obtain trough concentrations. A PK model was generated, covariate effects assessed and internally validated by a bootstrap procedure. PK parameters were related to overall survival (OS) and the occurrence of immune-related adverse events (irAEs). RESULTS: 588 serum samples derived from 122 patients with (non-)small-cell lung cancer ([N]SCLC), malignant pleural mesothelioma (MPM), melanoma and urothelial cell cancer (UCC) were analyzed. Median follow-up was 2.2 years. A one-compartment PK model was generated: body surface area (BSA) and serum albumin had a significant effect on drug clearance (CL; covariate estimate 1.46 and -1.43, respectively), and serum lactate dehydrogenase (LDH) on the distribution volume(Vd; 0.34). A significant inverse CL-OS relationship was determined for NSCLC (HR:1.69; 95%CI1.07-2.68; p=0.024) and MPM (HR: 3.29; 95% CI 1.08 to 10.09; p=0.037), after correction for prognostic factors, which could not confirmed for melanoma (p=0.22) or UCC (p=0.34). No relationship could be determined between CL and grade >3 irAEs (p=0.70). CONCLUSIONS: High interpatient variability of pembrolizumab PK is determined by BSA and serum albumin (on CL) and LDH (on Vd). A strong inverse CL-OS relationship was demonstrated for NSCLC and MPM, which could not be observed for melanoma and UCC. The findings suggest that personalized dosing should be prospectively explored.

Evaluation of the pharmacokinetics of prednisolone in paediatric patients with acute lymphoblastic leukaemia treated according to Dutch Childhood Oncology Group protocols and its relation to treatment response.

Glucocorticoids form the backbone of paediatric acute lymphoblastic leukaemia (ALL) treatment. Many studies have been performed on steroid resistance; however, few studies have addressed the relationship between dose, concentration and clinical response. The aim of the present study was to evaluate the pharmacokinetics of prednisolone in the treatment of paediatric ALL and the correlation with clinical parameters. A total of 1028 bound and unbound prednisolone plasma concentrations were available from 124 children (aged 0-18 years) with newly diagnosed ALL enrolled in the Dutch Childhood Oncology Group studies. A population pharmacokinetic model was developed and post hoc area under the curve (AUC) was tested against treatment outcome parameters. The pharmacokinetics of unbound prednisolone in plasma was best described with allometric scaling and saturable binding to proteins. Plasma protein binding decreased with age. The AUC of unbound prednisolone was not associated with any of the disease parameters or treatment outcomes. Unbound prednisolone plasma concentrations correlated with age. No effect of exposure on clinical treatment outcome parameters was observed and does not substantiate individualised dosing. Poor responders, high-risk and relapsed patients showed a trend towards lower exposure compared to good responders. However, the group of poor responders was small and requires further research.

Pharmacokinetics and population pharmacokinetics in pediatric oncology.

Pharmacokinetic research has become increasingly important in pediatric oncology as it can have direct clinical implications and is a crucial component in individualized medicine. Population pharmacokinetics has become a popular method especially in children, due to the potential for sparse sampling, flexible sampling times, computing of heterogeneous data, and identification of variability sources. However, population pharmacokinetic reports can be complex and difficult to interpret. The aim of this article is to provide a basic explanation of population pharmacokinetics, using clinical examples from the field of pediatric oncology, to facilitate the translation of pharmacokinetic research into the daily clinic.

Population pharmacokinetics of intravenous Erwinia asparaginase in pediatric acute lymphoblastic leukemia patients.

Erwinia asparaginase is an important component in the treatment of pediatric acute lymphoblastic leukemia. A large variability in serum concentrations has been observed after intravenous Erwinia asparaginase. Currently, Dutch Childhood Oncology Group protocols dose alterations are based on trough concentrations to ensure adequate asparaginase activity (≥100 IU/L). The aim of this study was to describe the population pharmacokinetics of intravenous Erwinia asparaginase to quantify and gather insight into inter-individual and inter-occasion variability. The starting dose was evaluated on the basis of the derived population pharmacokinetic parameters. In a multicenter prospective observational study, a total of 714 blood samples were collected from 51 children (age 1-17 years) with acute lymphoblastic leukemia. The starting dose was 20,000 IU/m2 three times a week and adjusted according to trough levels from week three onwards. A population pharmacokinetic model was developed using NONMEM® A 2-compartment linear model with allometric scaling best described the data. Inter-individual and inter-occasion variability of clearance were 33% and 13%, respectively. Clearance in the first month of treatment was 14% higher (P<0.01). Monte Carlo simulations with our pharmacokinetic model demonstrated that patients with a low weight might require higher doses to achieve similar concentrations compared to patients with high weight. The current starting dose of 20,000 IU/m2 might result in inadequate concentrations, especially for smaller, lower weight patients, hence dose adjustments based on individual clearance are recommended. The protocols were approved by the institutional review boards. (Registered at NTR 3379 Dutch Trial Register; www.trialregister.nl).

Predicting the neurobehavioral side effects of dexamethasone in pediatric acute lymphoblastic leukemia.

Although dexamethasone is an effective treatment for acute lymphoblastic leukemia (ALL), it can induce a variety of serious neurobehavioral side effects. We hypothesized that these side effects are influenced by glucocorticoid sensitivity at the tissue level. We therefore prospectively studied whether we could predict the occurrence of these side effects using the very low-dose dexamethasone suppression test (DST) or by measuring trough levels of dexamethasone. Fifty pediatric patients (3-16 years of age) with acute lymphoblastic leukemia (ALL) were initially included during the maintenance phase (with dexamethasone) of the Dutch ALL treatment protocol. As a marker of glucocorticoid sensitivity, the salivary very low-dose DST was used. A post-dexamethasone cortisol level <2.0nmol/L was considered a hypersensitive response. The neurobehavioral endpoints consisted of questionnaires regarding psychosocial and sleeping problems administered before and during the course of dexamethasone (6mg/m(2)), and dexamethasone trough levels were measured during dexamethasone treatment. Patients with a hypersensitive response to dexamethasone had more behavioral problems (N=11), sleeping problems, and/or somnolence (N=12) (P<0.05 for all three endpoints). The positive predictive values of the DST for psychosocial problems and sleeping problems were 50% and 30%, respectively. Dexamethasone levels were not associated with neurobehavioral side effects. We conclude that neither the very low-dose DST nor measuring dexamethasone trough levels can accurately predict dexamethasone-induced neurobehavioral side effects. However, patients with glucocorticoid hypersensitivity experienced significantly more symptoms associated with dexamethasone-induced depression. Future studies should elucidate further the mechanisms by which neurobehavioral side effects are influenced by glucocorticoid sensitivity.

Acute Activation of Metabolic Syndrome Components in Pediatric Acute Lymphoblastic Leukemia Patients Treated with Dexamethasone.

Although dexamethasone is highly effective in the treatment of pediatric acute lymphoblastic leukemia (ALL), it can cause serious metabolic side effects. Because studies regarding the effects of dexamethasone are limited by their small scale, we prospectively studied the direct effects of treating pediatric ALL with dexamethasone administration with respect to activation of components of metabolic syndrome (MetS); in addition, we investigated whether these side effects were correlated with the level of dexamethasone. Fifty pediatric patients (3-16 years of age) with ALL were studied during a 5-day dexamethasone course during the maintenance phase of the Dutch Childhood Oncology Group ALL-10 and ALL-11 protocols. Fasting insulin, glucose, total cholesterol, HDL, LDL, and triglycerides levels were measured at baseline (before the start of dexamethasone; T1) and on the fifth day of treatment (T2). Dexamethasone trough levels were measured at T2. We found that dexamethasone treatment significantly increased the following fasting serum levels (P<0.05): HDL, LDL, total cholesterol, triglycerides, glucose, and insulin. In addition, dexamethasone increased insulin resistance (HOMA-IR>3.4) from 8% to 85% (P<0.01). Dexamethasone treatment also significantly increased the diastolic and systolic blood pressure. Lastly, dexamethasone trough levels (N = 24) were directly correlated with high glucose levels at T2, but not with other parameters. These results indicate that dexamethasone treatment acutely induces three components of the MetS. Together with the weight gain typically associated with dexamethasone treatment, these factors may contribute to the higher prevalence of MetS and cardiovascular risk among survivors of childhood leukemia who received dexamethasone treatment.

Pramipexole effects on startle gating in rats and normal men.

BACKGROUND: Dopamine D3 receptors regulate sensorimotor gating in rats, as evidenced by changes in prepulse inhibition (PPI) of startle after acute administration of D3 agonists and antagonists. In this study, we tested the effects of the D3-preferential agonist, pramipexole, on PPI in normal men and Sprague-Dawley rats. MATERIALS AND METHODS: Acoustic startle and PPI were tested in clinically normal men, comparing the effects of placebo vs. 0.125 mg (n = 20) or placebo vs. 0.1875 mg (n = 20) pramipexole, in double blind, crossover designs. These measures were also tested in male Sprague-Dawley rats using a parallel design [vehicle vs. 0.1 mg/kg (n = 8), vehicle vs. 0.3 mg/kg (n = 8) or vehicle vs. 1.0 mg/kg pramipexole (n = 8)]. Autonomic and subjective measures of pramipexole effects and several personality instruments were also measured in humans. RESULTS: Pramipexole increased drowsiness and significantly increased PPI at 120-ms intervals in humans; the latter effect was not moderated by baseline PPI or personality scale scores. In rats, pramipexole causes a dose-dependent reduction in long-interval (120 ms) PPI, while low doses actually increased short-interval (10-20 ms) PPI. Effects of pramipexole on PPI in rats were independent of baseline PPI and changes in startle magnitude. CONCLUSION: The preferential D3 agonist pramipexole modifies PPI in humans and rats. Unlike indirect DA agonists and mixed D2/D3 agonists, pramipexole increases long-interval PPI in humans, in a manner that is independent of baseline PPI and personality measures. These findings are consistent with preclinical evidence for differences in the D2- and D3-mediated regulation of sensorimotor gating.