Biomedical subjects

Susan E Tett

Publications and source records attributed to Susan E Tett.

35 records · Page 2Linked to original sources

PubMed2004

Free mycophenolic acid should be monitored in renal transplant recipients with hypoalbuminemia.

The current approach for therapeutic drug monitoring in renal transplant recipients receiving mycophenolate mofetil (MMF) is measurement of total mycophenolic acid (MPA) concentration. Because MPA is highly bound, during hypoalbuminemia the total concentration no longer reflects the free (pharmacologically active) concentration. The authors investigated what degree of hypoalbuminemia causes a significant change in protein binding and thus percentage free MPA. Forty-two renal transplant recipients were recruited for the study. Free and total concentrations of MPA (predose, and 1, 3, and 6 hours post-MMF dose samples) and plasma albumin concentrations were determined on day 5 posttransplantation. Six-hour area under the concentration-time curve (AUC(0-6)) values were calculated for free and total MPA, and percentage free MPA was determined for each patient. The authors found a significant relationship between low albumin concentrations and increased percentage free MPA (Spearman correlation = -0.54, P < 0.0001). Receiver operating characteristic (ROC) curve analysis was performed on the albumin versus percentage free MPA data. The cutoff value of albumin determined from the ROC analysis that differentiated normal from elevated percentage free MPA (defined as > or = 3%) in this patient population was 31 g/L. At this cutoff value albumin was found to be a good predictor of altered free MPA percentage, with a sensitivity and specificity of 0.75 and 0.80, respectively, and an area under the ROC curve of 0.79. To rationalize MMF dosing regimens in hypoalbuminemic patients (plasma albumin < or = 31 g/L), clinicians should consider monitoring the free MPA concentration.

Adult↗

PubMed2004

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients.

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

Adult↗

PubMed2004

Vancomycin pharmacokinetics in critically ill patients receiving continuous venovenous haemodiafiltration.

AIMS: To investigate the pharmacokinetics of vancomycin in critically ill patients on continuous venovenous haemodiafiltration (CVVHDF), a continuous renal replacement therapy (CRRT) and to see if routine measures approximate vancomycin clearance. METHODS: Pharmacokinetic profiles (15) of initial and steady-state doses of 750 mg twice daily intravenous vancomycin were obtained from blood and ultrafiltrate samples from 10 critically ill patients in the intensive care unit, with acute renal failure on CVVHDF (1 l h(-1) dialysate plus 2 l h(-1) filtration solution; 3 l h(-1) effluent; extracorporeal blood flow 200 ml min(-1)). RESULTS: CVVHDF clearance of vancomycin was 1.8 +/- 0.4 l h(-1) (30 +/- 6.7 ml min(-1)). This was 1.3-7.2 times that reported previously for vancomycin using other forms of CRRT. Total vancomycin body clearance was 2.5 +/- 0.7 l h(-1) (41.7 +/- 11.7 ml min(-1)). The clearance of vancomycin by CVVHDF was 76 +/- 16.5% of the total body clearance. CVVHDF removed approximately half the vancomycin dose during the 12-h period (A(CVVHDF) = 413 mg). The fraction eliminated by all routes was 60%. The sieving coefficient for vancomycin was 0.7 +/- 0.1 and for urea was 0.8 +/- 0.06. CONCLUSIONS: Vancomycin is cleared effectively by CVVHDF. Clearance was faster than other forms of CRRT, therefore doses need to be relatively high. Urea clearance slightly overestimates vancomycin clearance. The administered doses of 750 mg every 12 h were too high and accumulation occurred, as only approximately 60% of a dose was cleared over this period. The maintenance dose required to achieve a target average steady-state plasma concentration of 15 mg l(-1) can be calculated as 450 mg every 12 h.

Adult↗

PubMed2004

Perceptions around concordance--focus groups and semi-structured interviews conducted with consumers, pharmacists and general practitioners.

BACKGROUND: Achieving concordance by identifying beliefs about illness, treatment and medicine-taking should impact positively on behaviour and consumer satisfaction with respect to treatment, and health outcomes may be improved. OBJECTIVE: To explore, in the Australian context, beliefs and expectations of general practitioners (GPs), consumers and pharmacists in relation to concordance to allow further exploration of the implementation of principles of concordance in Australia. DESIGN: Qualitative analysis of focus group and semi-structured interview data. SETTING AND PARTICIPANTS: Focus groups were held with seven consumers and nine pharmacists and, in-depth, semi-structured interviews were held with 10 GPs between February and May 2003, in Brisbane (Australia). RESULTS: This explorative study identified a variety of issues. Consumers expressed the need for more input from health professionals - being given more information on their treatments and conditions, more time spent in discussion, and establishing a system where harmonious relationships between health professionals could take place, which would result in a more consumer-friendly health care system. The main issues voiced by the pharmacists were about the idea of organizing the health care system in a way that would accommodate more quality information sharing between all partners. GPs' issues included better and unlimited information-sharing, having more time to promote quality in health care and receiving remuneration for increased verbal contact with other health care professionals. Suggestions were made about ways to achieve concordance by improved information-sharing and shared decision-making. CONCLUSION: The data from this study will lead to the development of models to explore and attempt to incorporate principles of concordance in Australian pharmacy and medical practice.

Aged↗

PubMed2004

Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation.

The aim of this review is to analyse critically the recent literature on the clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplant recipients. Dosage and target concentration recommendations for tacrolimus vary from centre to centre, and large pharmacokinetic variability makes it difficult to predict what concentration will be achieved with a particular dose or dosage change. Therapeutic ranges have not been based on statistical approaches. The majority of pharmacokinetic studies have involved intense blood sampling in small homogeneous groups in the immediate post-transplant period. Most have used nonspecific immunoassays and provide little information on pharmacokinetic variability. Demographic investigations seeking correlations between pharmacokinetic parameters and patient factors have generally looked at one covariate at a time and have involved small patient numbers. Factors reported to influence the pharmacokinetics of tacrolimus include the patient group studied, hepatic dysfunction, hepatitis C status, time after transplantation, patient age, donor liver characteristics, recipient race, haematocrit and albumin concentrations, diurnal rhythm, food administration, corticosteroid dosage, diarrhoea and cytochrome P450 (CYP) isoenzyme and P-glycoprotein expression. Population analyses are adding to our understanding of the pharmacokinetics of tacrolimus, but such investigations are still in their infancy. A significant proportion of model variability remains unexplained. Population modelling and Bayesian forecasting may be improved if CYP isoenzymes and/or P-glycoprotein expression could be considered as covariates. Reports have been conflicting as to whether low tacrolimus trough concentrations are related to rejection. Several studies have demonstrated a correlation between high trough concentrations and toxicity, particularly nephrotoxicity. The best predictor of pharmacological effect may be drug concentrations in the transplanted organ itself. Researchers have started to question current reliance on trough measurement during therapeutic drug monitoring, with instances of toxicity and rejection occurring when trough concentrations are within 'acceptable' ranges. The correlation between blood concentration and drug exposure can be improved by use of non-trough timepoints. However, controversy exists as to whether this will provide any great benefit, given the added complexity in monitoring. Investigators are now attempting to quantify the pharmacological effects of tacrolimus on immune cells through assays that measure in vivo calcineurin inhibition and markers of immunosuppression such as cytokine concentration. To date, no studies have correlated pharmacodynamic marker assay results with immunosuppressive efficacy, as determined by allograft outcome, or investigated the relationship between calcineurin inhibition and drug adverse effects. Little is known about the magnitude of the pharmacodynamic variability of tacrolimus.

Drug Interactions↗

PubMed2004

A perspective on Australia's National Medicines Policy.

There is international interest in Australia's health care system for prescription medicines. The issue is particularly topical in Canada with the debate following publication of the Romanow Report into the future of health care in Canada. This Report recommended a new National Drug Agency. Australia has a National Medicines Policy with four arms-quality, safety and efficacy of medicines; equity of access; a viable and responsible pharmaceutical industry; quality use of medicines. The four arms of the Policy are interlinked and interdependent for optimal functioning. In this paper, an overview of how the prescription drug system in Australia works is presented. The manuscript focuses upon specific aspects of the Policy, describing how it functions and some of the processes integral to success, from the viewpoint of the author. The discussion includes some of the advantages of Australia's system for pharmaceuticals as well as some of the problems, as these present opportunities for development and change.

Australia↗

PubMed2003

Doctors perceptions of the influences on their prescribing: a comparison of general practitioners based in rural and urban Australia.

OBJECTIVES: To compare and contrast the influences on prescribing perceived by general practitioners in an urban area of Queensland, Australia, to those perceived by general practitioners in rural Queensland. METHOD: An investigation was undertaken with a group of general practitioners in urban and rural locations of Australia. A self-administered questionnaire requested the doctors' demographic details and their opinions on statements about prescribing. They also reported their prescribing of six recently marketed drugs. RESULTS: One hundred and forty-two general practitioners from rural areas of Queensland (55% of the eligible population of these doctors) and one hundred and thirty-seven from the urban area (54% response) returned the surveys. The urban group were older and had more experience as general practitioners. Similarities and differences were detected between the two groups. The urban group considered that continuing medical education had a lesser influence on their prescribing than the rural group. The rural general practitioners were more likely than the urban doctors to agree that their information needs on prescribing were not being met in their practice, that their practice location had an effect on their prescribing (and also an effect on their prescribing of new drugs) as well as the remoteness of the patient's address having an effect. The rural doctors agreed more than the urban doctors that they try to avoid drugs requiring a significant amount of monitoring, reinforced by their agreement that they would be more likely to prescribe a newly marketed drug requiring less monitoring. When relating to whether the doctors in the two groups had reported initiating a supply of specific newly marketed drugs, independent of a specialist, rural general practitioners had initiated fewer of these selected new medicines. CONCLUSION: This study has highlighted some of the differences in perceptions of doctors on the influences on prescribing in rural relative to urban areas of Australia. An understanding of these perceptions will allow targeting and development of location-relevant prescribing interventions and messages.

Adult↗

PubMed2003

Toward better outcomes with tacrolimus therapy: population pharmacokinetics and individualized dosage prediction in adult liver transplantation.

Patient outcomes in transplantation would improve if dosing of immunosuppressive agents was individualized. The aim of this study is to develop a population pharmacokinetic model of tacrolimus in adult liver transplant recipients and test this model in individualizing therapy. Population analysis was performed on data from 68 patients. Estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F) using the nonlinear mixed effects model program (NONMEM). Factors screened for influence on these parameters were weight, age, sex, transplant type, biliary reconstructive procedure, postoperative day, days of therapy, liver function test results, creatinine clearance, hematocrit, corticosteroid dose, and interacting drugs. The predictive performance of the developed model was evaluated through Bayesian forecasting in an independent cohort of 36 patients. No linear correlation existed between tacrolimus dosage and trough concentration (r(2) = 0.005). Mean individual Bayesian estimates for CL/F and V/F were 26.5 +/- 8.2 (SD) L/hr and 399 +/- 185 L, respectively. CL/F was greater in patients with normal liver function. V/F increased with patient weight. CL/F decreased with increasing hematocrit. Based on the derived model, a 70-kg patient with an aspartate aminotransferase (AST) level less than 70 U/L would require a tacrolimus dose of 4.7 mg twice daily to achieve a steady-state trough concentration of 10 ng/mL. A 50-kg patient with an AST level greater than 70 U/L would require a dose of 2.6 mg. Marked interindividual variability (43% to 93%) and residual random error (3.3 ng/mL) were observed. Predictions made using the final model were reasonably nonbiased (0.56 ng/mL), but imprecise (4.8 ng/mL). Pharmacokinetic information obtained will assist in tacrolimus dosing; however, further investigation into reasons for the pharmacokinetic variability of tacrolimus is required.

Adult↗

PubMed2003

Bayesian forecasting and prediction of tacrolimus concentrations in pediatric liver and adult renal transplant recipients.

AIM: To test the predictive capacity of two recently derived population pharmacokinetic models and the usefulness of Bayesian forecasting to predict tacrolimus blood concentrations in pediatric liver and adult kidney transplant recipients. MATERIALS AND METHODS: New databases were added to the Abbottbase PKS (Bayesian dosage prediction) program to incorporate the population pharmacokinetic models developed for tacrolimus. Two independent populations of transplant recipients were used to predict tacrolimus trough concentrations. Pharmacokinetic, demographic, and covariate data were collected from patient records. Different time weighting factors were tested (1, 1.005, 1.01) and the influence of excluding data collected in the first 5 days post-transplant examined. Concentrations were predicted until the 10th tacrolimus measurement. Actual tacrolimus concentrations were compared with those predicted by the PKS program and bias and precision determined. RESULTS: Tacrolimus concentrations predicted by the PKS program were, on average, unbiased for the pediatric liver population, but were over-predicted (9%) for the adult renal population. In both populations predictions were not precise (imprecision ranged from 39 to 50%). CONCLUSIONS: Due to the imprecision seen in this study, these models could not be used in clinical practice in the immediate post-transplant period. Poor precision may be due to reliance on routine drug monitoring data alone, difficulties with expression of covariates in continuous modeling relationships in the PKS program, lack of accurate quantitative measures of liver function, or large, random intraindividual variability in the bioavailability of tacrolimus.

Adolescent↗

PubMed2003

Population pharmacokinetics of hydroxychloroquine in patients with rheumatoid arthritis.

SUMMARY: Hydroxychloroquine (HCQ) is an antimalarial drug that is also used as a second-line treatment of rheumatoid arthritis (RA). Clinically, the use of HCQ is characterized by a long delay in the onset of action, and withdrawal of treatment is often a result of inefficacy rather than from toxicity. The slow onset of action can be attributed to the pharmacokinetics (PK) of HCQ, and wide interpatient variability is evident. Tentative relationships between concentration and effect have been made, but to date, no population PK model has been developed for HCQ. This study aimed to develop a population PK model including an estimation of the oral bioavailability of HCQ. In addition, the effects of the coadministration of methotrexate on the PK of HCQ were examined. Hydroxychloroquine blood concentration data were combined from previous pharmacokinetic studies in patients with rheumatoid arthritis. A total of 123 patients were studied, giving the data cohort from four previously published studies. Two groups of patients were included: 74 received hydroxychloroquine (HCQ) alone, and 49 received HCQ and methotrexate (MTX). All data analyses were carried out using the NONMEM program. A one-compartment PK model was supported, rather than a three-compartment model as previously published, probably because of the clustering of concentrations taken at the end of a dosing interval. The population estimate of bioavailability of 0.75 (0.07), n = 9, was consistent with literature values. The parameter values from the final model were: Cl = 9.9 +/- 0.4 L/h, V = 605 +/- 91 L, ka = 0.77 +/- 0.22 hours(-1), t(tag) = 0.44 +/- 0.02 hours. Clearance was not affected by the presence of MTX, and, hence, steady-state drug concentrations and maintenance dosage requirements were similar. A population PK model was successfully developed for HCQ.

Adult↗

PubMed2003

Principles and clinical application of assessing alterations in renal elimination pathways.

Drugs and metabolites are eliminated from the body by metabolism and excretion. The kidney makes the major contribution to excretion of unchanged drug and also to excretion of metabolites. Net renal excretion is a combination of three processes - glomerular filtration, tubular secretion and tubular reabsorption. Renal function has traditionally been determined by measuring plasma creatinine and estimating creatinine clearance. However, estimated creatinine clearance measures only glomerular filtration with a small contribution from active secretion. There is accumulating evidence of poor correlation between estimated creatinine clearance and renal drug clearance in different clinical settings, challenging the 'intact nephron hypothesis' and suggesting that renal drug handling pathways may not decline in parallel. Furthermore, it is evident that renal drug handling is altered to a clinically significant extent in a number of disease states, necessitating dosage adjustment not just based on filtration. These observations suggest that a re-evaluation of markers of renal function is required. Methods that measure all renal handling pathways would allow informed dosage individualisation using an understanding of renal excretion pathways and patient characteristics. Methodologies have been described to determine individually each of the renal elimination pathways. However, their simultaneous assessment has only recently been investigated. A cocktail of markers to measure simultaneously the individual renal handling pathways have now been developed, and evaluated in healthy volunteers. This review outlines the different renal elimination pathways and the possible markers that can be used for their measurement. Diseases and other physiological conditions causing altered renal drug elimination are presented, and the potential application of a cocktail of markers for the simultaneous measurement of drug handling is evaluated. Further investigation of the effects of disease processes on renal drug handling should include people with HIV infection, transplant recipients (renal and liver) and people with rheumatoid arthritis. Furthermore, changes in renal function in the elderly, the effect of sex on renal function, assessment of living kidney donors prior to transplantation and the investigation of renal drug interactions would also be potential applications. Once renal drug handling pathways are characterised in a patient population, the implications for accurate dosage individualisation can be assessed. The simultaneous measurement of renal function elimination pathways of drugs and metabolites has the potential to assist in understanding how renal function changes with different disease states or physiological conditions. In addition, it will further our understanding of fundamental aspects of the renal elimination of drugs.

Age Factors↗

PubMed2003

Influences on doctors' prescribing: is geographical remoteness a factor?

OBJECTIVE: To identify factors influencing the prescribing of medicines by general practitioners in rural and remote Australia. DESIGN: A qualitative study using a questionnaire to determine attitudes about prescribing, specific prescribing habits and comments on prescribing in 'rural practice'. SETTING: General practice in rural and remote Queensland. SUBJECTS: General practitioners practising in rural and remote settings in Queensland (n = 258). MAIN OUTCOME MEASURES: The factors perceived to influence the prescribing of medicines by medical practitioners in rural environments. RESULTS: A 58% response rate (n = 142) was achieved. Most respondents agreed that they prescribe differently in rural compared with city practice. The majority of respondents agreed that their prescribing was influenced by practice location, isolation of patient home location, limited diagnostic testing and increased drug monitoring. Location issues and other issues were more likely to be identified as 'influential' by the more isolated practitioners. Factors such as access to continuing medical education and specialists were confirmed as having an influence on prescribing. The prescribing of recently marketed drugs was more likely by doctors practising in less remote rural areas. CONCLUSION: Practising in rural and remote locations is perceived to have an effect on prescribing. These influences need to be considered when developing quality use of medicines policies and initiatives for these locations.

Adult↗

PubMed2002

Comparison of two population pharmacokinetic programs, NONMEM and P-PHARM, for tacrolimus.

OBJECTIVES: To compare the population modelling programs NONMEM and P-PHARM during investigation of the pharmacokinetics of tacrolimus in paediatric liver-transplant recipients. METHODS: Population pharmacokinetic analysis was performed using NONMEM and P-PHARM on retrospective data from 35 paediatric liver-transplant patients receiving tacrolimus therapy. The same data were presented to both programs. Maximum likelihood estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F). Covariates screened for influence on these parameters were weight, age, gender, post-operative day, days of tacrolimus therapy, transplant type, biliary reconstructive procedure, liver function tests, creatinine clearance, haematocrit, corticosteroid dose, and potential interacting drugs. RESULTS: A satisfactory model was developed in both programs with a single categorical covariate--transplant type--providing stable parameter estimates and small, normally distributed (weighted) residuals. In NONMEM, the continuous covariates--age and liver function tests--improved modelling further. Mean parameter estimates were CL/F (whole liver) = 16.3 l/h, CL/F (cut-down liver) = 8.5 l/h and V/F = 565 l in NONMEM, and CL/F = 8.3 l/h and V/F = 155 l in P-PHARM. Individual Bayesian parameter estimates were CL/F (whole liver) = 17.9 +/- 8.8 l/h, CL/F (cut-down liver) = 11.6 +/- 8.8 l/h and V/F = 712 +/- 792 l in NONMEM, and CL/F (whole liver) = 12.8 +/- 3.5 l/h, CL/F (cut-down liver) = 8.2 +/- 3.4 l/h and V/F = 221 +/- 164 l in P-PHARM. Marked interindividual kinetic variability (38-108%) and residual random error (approximately 3 ng/ml) were observed. P-PHARM was more user friendly and readily provided informative graphical presentation of results. NONMEM allowed a wider choice of errors for statistical modelling and coped better with complex covariate data sets. CONCLUSION: Results from parametric modelling programs can vary due to different algorithms employed to estimate parameters, alternative methods of covariate analysis and variations and limitations in the software itself.

Adolescent↗

PubMed2002

Population pharmacokinetics of tacrolimus in adult kidney transplant recipients.

OBJECTIVES: The aims of this study were to investigate the population pharmacokinetics of tacrolimus in adult kidney transplant recipients and to identify factors that explain variability. METHODS: Population analysis was performed on retrospective data from 70 patients who received oral tacrolimus twice daily. Morning blood trough concentrations were measured by liquid chromatography-tandem mass spectrometry. Maximum likelihood estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F), with the use of NONMEM (GloboMax LLC, Hanover, Md). Factors screened for influence on these parameters were weight, age, gender, postoperative day, days of tacrolimus therapy, liver function tests, creatinine clearance, hematocrit fraction, corticosteroid dose, and potential interacting drugs. RESULTS: CL/F was greater in patients with abnormally low hematocrit fraction (data from 21 patients only), and it decreased with increasing days of therapy and AST concentrations (P <.01). Average parameter estimates were as follows: CL/F = 31.8 L/h (hematocrit <0.33), CL/F = 24.2 L/h (hematocrit >0.33), and V/F = 2080 L. Marked interindividual variability (42% to 111%) and residual random error (3.7 ng/mL) were observed. On the basis of the derived model, a patient with normal AST (20 U/L) or high AST (200 U/L) concentrations 7 days after commencement of therapy would require a tacrolimus dose of 4.6 mg or 4.0 mg, respectively, to achieve a steady-state trough concentration of 10 ng/mL. CONCLUSIONS: The population pharmacokinetics of tacrolimus in adult kidney transplant recipients showed wide variability. Thus it is not possible to use a standard tacrolimus dose as an empiric predictor of concentration in this population. An understanding of factors that influence the pharmacokinetics of tacrolimus may assist in drug dosage decisions.

Administration, Oral↗

PubMed2002

Comparison of an ELISA and an LC/MS/MS method for measuring tacrolimus concentrations and making dosage decisions in transplant recipients.

This study compared an enzyme-linked immunosorbent assay (ELISA) to a liquid chromatography-tandem mass spectrometry (LC/MS/MS) technique for measurement of tacrolimus concentrations in adult kidney and liver transplant recipients, and investigated how assay choice influenced pharmacokinetic parameter estimates and drug dosage decisions. Tacrolimus concentrations measured by both ELISA and LC/MS/MS from 29 kidney (n = 98 samples) and 27 liver (n = 97 samples) transplant recipients were used to evaluate the performance of these methods in the clinical setting. Tacrolimus concentrations measured by the two techniques were compared via regression analysis. Population pharmacokinetic models were developed independently using ELISA and LC/MS/MS data from 76 kidney recipients. Derived kinetic parameters were used to formulate "typical dosing" regimens for concentration targeting. Dosage recommendations for the two assays were compared. The relation between LC/MS/MS and ELISA measurements was best described by the regression equation ELISA = 1.02. (LC/MS/MS) + 0.14 in kidney recipients, and ELISA = 1.12. (LC/MS/MS) - 0.87 in liver recipients. ELISA displayed less accuracy than LC/MS/MS at lower tacrolimus concentrations. Population pharmacokinetic models based on ELISA and LC/MS/MS data were similar with residual random errors of 4.1 ng/mL and 3.7 ng/mL, respectively. Assay choice gave rise to dosage prediction differences ranging from 0% to 30%. ELISA measurements of tacrolimus are not automatically interchangeable with LC/MS/MS values. Assay differences were greatest in adult liver recipients, probably reflecting periods of liver dysfunction and impaired biliary secretion of metabolites. While the majority of data collected in this study suggested assay differences in adult kidney recipients were minimal, findings of ELISA dosage underpredictions of up to 25% in the long term must be investigated further.

Chromatography, Liquid↗

PubMed2002

Cyclosporin monitoring in Australasia: 2002 update of consensus guidelines.

Therapeutic drug monitoring of cyclosporin (CsA) has been established as part of the routine clinical treatment of patients following organ transplantation for more than 20 years, and based on contemporary knowledge, many consensus guidelines have been published to assist clinics and laboratories attain optimal strategies for patient care. This article addresses the newer directions in CsA monitoring, with particular reference to the Australasian situation that has evolved since the 1993 Australasian guideline. These changes have included the introduction of alternative assay methodologies, changed CsA formulation from Sandimmun to Neoral throughout Australasia, and alternatives to trough concentration (C0) monitoring, especially 2-hour concentration (C2) monitoring and associated validated dilution protocols to accurately quantitate the higher whole blood CsA concentrations. The revision was prepared following a recent survey of all Australasian CsA-monitoring laboratories where discordant practices were evident.

Area Under Curve↗

PubMed2002

Combination therapy with methotrexate and hydroxychloroquine for rheumatoid arthritis increases exposure to methotrexate.

OBJECTIVE: To examine the bioavailability of methotrexate (MTX) in the presence of hydroxychloroquine (HCQ), and vice versa, to determine a possible pharmacokinetic explanation for the observation that combination treatment of rheumatoid arthritis with MTX and HCQ has been shown, clinically, to be more potent than MTX used alone. METHODS: In a randomized crossover study, 10 healthy subjects received, on each of 5 dosing occasions, MTX alone as tablets or intravenous solution, HCQ alone as a tablet or oral solution, or a coadministered dose of MTX tablets with an HCQ tablet. The area under the concentration-time curve (AUC) was determined for each subject, on each dosing occasion, for each compound. RESULTS: The mean AUC for MTX was increased (p = 0.005) and the maximum MTX concentration (Cmax) decreased (p = 0.025) when MTX was coadministered with HCQ, compared to MTX administered alone. The time to reach Cmax for MTX administration, tmax, was also increased during the coadministration with HCQ (p = 0.072). The AUC of HCQ showed no significant difference (p = 0.957) between any of the dosing occasions. CONCLUSION: These results may explain the increased potency of the MTX-HCQ combination over MTX as a single agent and also the sustained effects of MTX when administered with HCQ. In addition, the reduced Cmax of MTX observed during the coadministration may explain diminution of acute liver adverse effects. Extra vigilance for MTX adverse effects during combination therapy with HCQ is recommended, especially if renal function is known to be decreased.

Administration, Oral↗