The experiences and perspectives of people with gout on urate self-monitoring

INTRODUCTION

Gout management remains suboptimal despite safe and effective urate-lowering therapy. Self-monitoring of urate may improve gout management, however, the acceptability of urate self-monitoring by people with gout is unknown. The aim of this study was to explore the experiences of urate self-monitoring in people with gout.

METHODS

Semistructured interviews were conducted with people taking urate-lowering therapy (N = 30) in a 12-month trial of urate self-monitoring in rural and urban Australia. Interviews covered the experience of monitoring and its effect on gout self-management. Deidentified transcripts were analysed thematically.

RESULTS

Participants valued the ability to self-monitor and gain more understanding of urate control compared with the annual monitoring ordered by their doctors. Participants indicated that self-monitoring at home was easy, convenient and informed gout self-management behaviours such as dietary modifications, hydration, exercise and medication routines. Many participants self-monitored to understand urate concentration changes in response to feeling a gout flare was imminent or whether their behaviours, for example, alcohol intake, increased the risk of a gout flare. Urate concentrations were shared with doctors mainly when they were above target to seek management support, and this led to allopurinol dose increases in some cases.

CONCLUSION

Urate self-monitoring was viewed by people with gout as convenient and useful for independent management of gout. They believed self-monitoring achieved better gout control with a less restricted lifestyle. Urate data was shared with doctors at the patient's discretion and helped inform clinical decisions, such as allopurinol dose changes. Further research on implementing urate self-monitoring in routine care would enable an evaluation of its impact on medication adherence and clinical outcomes, as well as inform gout management guidelines.

PATIENT OR PUBLIC CONTRIBUTION

One person with gout, who was not a participant, was involved in the study design by providing feedback and pilot testing the semistructured interview guide. In response to their feedback, subsequent modifications to the interview guide were made to improve the understandability of the questions from a patient perspective. No additional questions were suggested.

The development and evaluation of dose-prediction tools for allopurinol therapy (Easy-Allo tools)

AIMS

Dose escalation at the initiation of allopurinol therapy can be protracted and resource intensive. Tools to predict the allopurinol doses required to achieve target serum urate concentrations would facilitate the implementation of more efficient dose-escalation strategies. The aim of this research was to develop and externally evaluate allopurinol dosing tools, one for use when the pre-urate-lowering therapy serum urate is known (Easy-Allo1) and one for when it is not known (Easy-Allo2).

METHODS

A revised population pharmacokinetic-pharmacodynamic model was developed using data from 653 people with gout. Maintenance doses to achieve the serum urate target of <0.36 mmol L-1 in >80% of individuals were simulated and evaluated against external data. The predicted and observed allopurinol doses were compared using the mean prediction error (MPE) and root mean square error (RMSE). The proportion of Easy-Allo predicted doses within 100 mg of the observed was quantified.

RESULTS

Allopurinol doses were predicted by total body weight, baseline urate, ethnicity and creatinine clearance. Easy-Allo1 produced unbiased and suitably precise dose predictions (MPE 2 mg day-1 95% confidence interval [CI] -13-17, RMSE 91%, 90% within 100 mg of the observed dose). Easy-Allo2 was positively biased by about 70 mg day-1 and slightly less precise (MPE 70 mg day-1 95% CI 52-88, RMSE 131%, 71% within 100 mg of the observed dose).

CONCLUSIONS

The Easy-Allo tools provide a guide to the allopurinol maintenance dose requirement to achieve the serum urate target of <0.36 mmol L-1 and will aid in the development of novel dose-escalation strategies for allopurinol therapy.

Estimation of adherence to urate-lowering therapy in people living with gout using Australia's Pharmaceutical Benefits Scheme and patient-reported dosing

AIMS

The aim of this study was to estimate adherence to urate-lowering therapy (ULT), predominately allopurinol, from Australia's Pharmaceutical Benefits Scheme (PBS) claims database in association with (1) patient-reported doses and (2) World Health Organization's (WHO) defined daily doses (DDD), namely, allopurinol (400 mg/day) or febuxostat (80 mg/day).

METHODS

Proportion of days covered (PDC) was calculated in 108 Gout App (Gout APP) trial participants with at least two recorded ULT dispensings in an approximately 12-month period before provision of intervention or control apps. Adherence was defined as PDC ≥80%. We measured the correlation between the two methods of calculating PDC using a Wilcoxon signed rank test. Agreement between ULT-taking status (self-reports) and ULT-dispensed status (PBS records) was tested with Cohen's kappa (κ), and positive and negative percent agreement.

RESULTS

Allopurinol was prescribed in 93.5% of participants taking ULT. Their self-reported mean daily dose (SD) was 291 (167) mg/day. Mean PDC (SD) for allopurinol was 83% (21%) calculated using self-reported dose, and 63% (24%) using WHO's DDD. Sixty-three percent of allopurinol users were identified as adherent (PDC ≥80%) using self-reported dose. There was good agreement between self-reported ULT use and PBS dispensing claims (κ = 0.708, P < .001; positive percent agreement = 90%, negative percent agreement = 82%).

CONCLUSIONS

Participant-reported allopurinol daily doses, in addition to PBS dispensing claims, may enhance confidence in estimating PDC and adherence compared to using DDD. This approach improves adherence estimations from pharmaceutical claims datasets for medications where daily doses vary between individuals or where there is a wide therapeutic dose range.

Patient-Led Urate Self-Monitoring to Improve Clinical Outcomes in People With Gout: A Feasibility Study

OBJECTIVE

Self-monitored point-of-care urate-measuring devices are an underexplored strategy to improve adherence to urate-lowering therapy and clinical outcomes in gout. This study observed patient-led urate self-monitoring practice and assessed its influence on allopurinol adherence, urate control, and health-related quality of life.

METHODS

People with gout (n = 31) and prescribed allopurinol self-monitored their urate concentrations (HumaSens2.0plus) at baseline and thereafter monthly for 12 months (3 months per quarter). Adherence to allopurinol was measured using medication event monitoring technology (Medication Event Monitoring System cap). Time spent below the target urate concentration (<0.36 mmol/L) was determined. Health-related quality of life was measured using a survey (EuroQoL EQ-5D-5L). Gout flares were recorded. Two-tailed Spearman correlation and the Wilcoxon matched-pairs signed-rank test (P < 0.05) were used for statistical comparisons.

RESULTS

Most participants were male (94%) and had urate concentrations below the target (74%) at baseline. Overall, seven participants demonstrated repeated periods of "missed doses" (two or fewer allopurinol doses missed consecutively) and "drug holidays" (three or more missed doses). Most participants (94%) persisted with allopurinol. Time spent within the target urate concentration increased 1.3-fold (from 79% to 100%; P = 0.346), and the incidence of gout flares decreased 1.6-fold (from 8 to 5; P = 0.25) in the final quarter compared to that in the first quarter of the study. Health-related quality of life was reduced for participants reporting at least one gout flare (median utility values 0.9309 vs 0.9563, P = 0.04).

CONCLUSION

Patient-led urate self-monitoring may support the maintenance of allopurinol adherence and improve urate control, thus reducing the incidence of gout flares. Further research on patient-led urate self-monitoring in a randomized controlled study is warranted.

A framework for understanding sources of bias in medication adherence research

The sources of bias in medication adherence research have not been comprehensively explored. We aimed to identify biases expected to affect adherence research and to develop a framework for mapping these onto the phases of adherence (initiation, implementation and discontinuation). A literature search was conducted, key papers were reviewed and a Catalogue of Bias was consulted. The specific biases related to adherence measurement and metrics were mapped onto the phases of adherence using a tabular matrix. Twenty-three biases were identified, of which 11 were specifically relevant to adherence measures and metrics. The mapping framework showed differences in the numbers and types of biases associated with each measure and metric while highlighting those common to many adherence study designs (e.g., unacceptability bias and apprehension bias). The framework will inform the design of adherence studies and the development of risk of bias tools for adherence research.

The impact of genetic variability in urate transporters on oxypurinol pharmacokinetics

The genetic determinants of the allopurinol dose-concentration relationship have not been extensively studied. We aimed to clarify what factors, including genetic variation in urate transporters, influence oxypurinol pharmacokinetics (PKs). A population PK model for oxypurinol was developed with NONMEM (version 7.3). The influence of urate transporter genetic variants for ABCG2 (rs2231142 and rs10011796), SLC2A9/GLUT9 (rs11942223), SLC17A1/NPT1 (rs1183201), SLC22A12/URAT1 (rs3825018), SLC22A11/OAT4 (rs17300741), and ABCC4/MRP4 (rs4148500), as well as other participant factors on oxypurinol PKs was assessed. Data from 325 people with gout were available. The presence of the T allele for ABCG2 (rs2231142) and SLC17A1/NPT1 (rs1183201) was associated with a 24% and 22% increase in oxypurinol clearance, respectively, in univariate analysis. This effect was not significant in the multivariate analysis. In the final model, oxypurinol PKs were predicted by creatinine clearance, diuretic use, ethnicity, and body weight. We have found that genetic variability in the transporters examined does not appear to influence oxypurinol PKs.

An allopurinol adherence tool using plasma oxypurinol concentrations

AIMS

This study aimed to develop and evaluate an allopurinol adherence tool based on steady-state oxypurinol plasma concentrations, allopurinol's active metabolite.

METHODS

Plasma oxypurinol concentration were simulated stochastically from an oxypurinol pharmacokinetic model for allopurinol doses of 100-800 mg daily, accounting for differences in renal function, diuretic use, and ethnicity. For each scenario, the 20^th percentile for peak and trough concentrations defined the adherence threshold, below which imperfect adherence was assumed. Predictive performance was evaluated using both simulated low adherence and against data from 146 individuals with paired oxypurinol plasma concentrations and adherence measures. Sensitivity and specificity (S&S), negative and positive predictive values (NPV, PPV) and receiver operating characteristic (ROC) area under the curve (AUC) were determined. The predictive performance of the tool was evaluated externally using RESULTS: The allopurinol adherence tool produced S&S values for trough thresholds of 89-98% and 76-84%, respectively, and 90%-98% and 76-83% for peak thresholds. PPV and NPV were 79-84% and 88-94% respectively for trough and 80-85% and 89-98% for peak concentrations. The ROC AUC values ranged from 0.84-0.88 and 0.86-0.89 for trough and peak concentrations, respectively. S&S values for the external evaluation were found to be 75.8% and 86.5%, respectively, producing a ROC AUC of 0.8113.

CONCLUSION

A tool to identify people with gout who require additional support to maintain adherence using plasma oxypurinol concentrations was developed and evaluated. The predictive performance of the tool is suitable for adherence screening in clinical trials and may have utility in some clinical practice settings.

Does the intact nephron hypothesis provide a reasonable model for metformin dosing in chronic kidney disease?

This research explored the intact nephron hypothesis (INH) as a model for metformin dosing in patients with chronic kidney disease (CKD). The INH assumes that glomerular filtration rate (GFR) will account for all kidney drug handling even for drugs eliminated by tubular secretion like metformin. We conducted two studies: (1) a regression analysis to explore the relationship between metformin clearance and eGFR metrics, and (2) a joint population pharmacokinetic analysis to test the relationship between metformin renal clearance and gentamicin clearance. The relationship between metformin renal clearance and eGFR metrics and gentamicin clearance was found to be linear, suggesting that a proportional dose reduction based on GFR in patients with CKD is reasonable.

Metformin doses to ensure efficacy and safety in patients with reduced kidney function

We aimed to develop a metformin dosing strategy to optimise efficacy and safety in patients with reduced kidney function. Metformin data from two studies stratified by kidney function were analysed. The relationship between metformin clearance and kidney function estimates was explored using a regression analysis. The maintenance dose range was predicted at different bands of kidney function to achieve an efficacy target of 1 mg/L for steady-state plasma concentrations. The dosing strategy was evaluated using simulations from a published metformin pharmacokinetic model to determine the probability of concentrations exceeding those associated with lactic acidosis risk, i.e. a steady-state average concentration of 3 mg/L and a maximum (peak) concentration of 5 mg/L. A strong relationship between metformin clearance and estimated kidney function using the Cockcroft and Gault (r2 = 0.699), MDRD (r2 = 0.717) and CKD-Epi (r2 = 0.735) equations was found. The probability of exceeding the safety targets for plasma metformin concentration was <5% for most doses and kidney function levels. The lower dose of 500 mg daily was required to maintain concentrations below the safety limits for patients with an eGFR of 15-29 mL/min. Our analysis suggests that a maximum daily dose of 2250, 1700, 1250, 1000, and 500 in patients with normal kidney function, CKD stage 2, 3a, 3b and 4, respectively, will provide a reasonable probability of achieving efficacy and safety. Our results support the cautious of use metformin at appropriate doses in patients with impaired kidney function.

Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

The Association between Metformin Therapy and Lactic Acidosis

INTRODUCTION AND OBJECTIVES

There is increasing evidence to suggest that therapeutic doses of metformin are unlikely to cause lactic acidosis. The aims of this research were (1) to formally evaluate the association between metformin therapy and lactic acidosis in published case reports using two causality scoring systems, (2) to determine the frequency of pre-existing independent risk factors in published metformin-associated lactic acidosis cases, (3) to investigate the association between risk factors and mortality in metformin-associated lactic acidosis cases, and (4) to explore the relationship between prescribed metformin doses, elevated metformin plasma concentrations and the development of lactic acidosis in cases with chronic renal impairment.

METHODS

A systematic review was conducted to identify metformin-associated lactic acidosis cases. Causality was assessed using the World Health Organisation-Uppsala Monitoring Centre system and the Naranjo adverse drug reaction probability scale. Compliance to dosing guidelines was investigated for cases with chronic renal impairment as well as the association between steady-state plasma metformin concentrations prior to admission.

RESULTS

We identified 559 metformin-associated lactic acidosis cases. Almost all cases reviewed (97%) presented with independent risk factors for lactic acidosis. The prescribed metformin dose exceeded published guidelines in 60% of cases in patients with impaired kidney function. Metformin steady-state plasma concentrations prior to admission were predicted to be below the proposed upper limit of the therapeutic range of 5 mg/L.

CONCLUSIONS

Almost all cases of metformin-associated lactic acidosis reviewed presented with independent risk factors for lactic acidosis, supporting the suggestion that metformin plays a contributory role. The prescribed metformin dose, on average, exceeded the dosing recommendations by 1000 mg/day in patients with varying degrees of renal impairment but the predicted pre-admission plasma concentrations did not exceed the therapeutic range.

Measuring the Development of Therapeutic-Decision-Making Skills by Practicing Pharmacists Undertaking a University-Based Postgraduate Clinical Qualification at Distance

(1) Background: The processes and skills required to make decisions about drug therapy have been termed "therapeutic decision-making" in pharmacy practice. The aim of this study was to evaluate a tool constructed to measure the development of therapeutic-decision-making skills by practicing pharmacists undertaking a university-based continuing professional development program. (2) Methods: A pre- and post-intervention crossover study design was used to investigate the qualitative and quantitative features of practicing pharmacists' responses to two clinical vignettes designed to measure the development of therapeutic-decision-making skills. The vignettes were assigned a score using a five-point scale and compared pre- and post-intervention. (3) Results: There was a median increase in score of 2 units on the five-point scale in the post-intervention scores compared to pre-intervention (p < 0.0001). (4) Conclusions: The results were interpreted to suggest that the participants' responses to the vignettes are a reasonable measure of student learning. Therefore, we infer that the teaching and learning intervention successfully enabled the development of therapeutic-decision-making skills by practicing pharmacists.

The pharmacokinetics of metformin in patients receiving intermittent haemodialysis

The aims of this study were to characterise the population pharmacokinetics of metformin in patients receiving haemodialysis, and to determine the doses that will maintain median metformin plasma concentrations below 5 mg L^-1 for a typical individual. Metformin plasma concentrations from 5 patients receiving thrice weekly intermittent haemodialysis followed by metformin 500 mg postdialysis were fitted to a published pharmacokinetic model. Additional models to describe the dialytic pharmacokinetics of metformin were explored. Doses of 250 and 500 postdialysis were simulated from the model for a typical haemodialysis patient. The published 2-compartment pharmacokinetic model with an additional parameter to describe haemodialysis clearance provided a reasonable fit to the data. Deterministic simulations from the model for a typical individual suggest that metformin doses of 250-500 mg postdialysis and 250 mg given once daily should maintain median metformin plasma concentrations below 5 mg L^-1 .

How do pharmacy students describe decision-making about drug therapy?

This article was migrated. The article was not marked as recommended. Introduction: Therapeutic decision-making is offered as a term to describe the responsibility that pharmacists have as medicines experts for making decisions about drug therapy for individual patients. There is a lack of research describing how pharmacy students learn to make therapeutic decisions. Methods: Qualitative methods were used to interview twelve final-year undergraduate pharmacy students. Data were analysed inductively to identify the steps in the process, the definition, and attitudes students learned about therapeutic decision-making. Results: According to these pharmacy students, the process and definition involve four steps; identifying medicines related problems via differential diagnosis, exploring treatment options, weighing up the options, and making a recommendation. Attitudes were confidence, open-mindedness, and bias awareness. Discussion: These findings align with a proposed model for therapeutic decision-making in pharmacy practice, however, this study did not determine if the students could apply the model in practice. Conclusion: These findings can be used as a benchmark for enhancing the pharmacy curriculum to include decision-making skills about drug therapy for future practice settings.

Relationships Between Allopurinol Dose, Oxypurinol Concentration and Urate-Lowering Response-In Search of a Minimum Effective Oxypurinol Concentration

The aims of this study were to determine factors that predict serum urate (SU) lowering response to allopurinol and the conversion of allopurinol to oxypurinol, and to determine a minimum therapeutic oxypurinol concentration. Data from 129 participants in a 24-month open, randomized, controlled, parallel-group, comparative clinical trial were analyzed. Allopurinol dose, SU, and plasma oxypurinol concentrations were available at multiple time points. The slope for the association between allopurinol dose and SU was calculated as a measure of sensitivity to allopurinol. The slope for the association between allopurinol dose and oxypurinol was calculated as a measure of allopurinol metabolism. Receiver operating characteristic (ROC) curves were used to identify a minimum oxypurinol concentration predictive of SU < 6 mg/dL. There was a wide range of SU concentrations for each allopurinol dose. The relationship between sensitivity to allopurinol and allopurinol metabolism for each 100 mg allopurinol dose increase varied between individuals. Body mass index (P = 0.023), creatinine clearance (CrCL; P = 0.037), ABCG2 Q141K (P = 0.019), and SU (P = 0.004) were associated with sensitivity to allopurinol. The minimum oxypurinol concentration for achieving the urate target was found to be about 104 μmol/L, but predictive accuracy was poor (ROC curve area under the curve (AUC) 0.65). The minimum therapeutic oxypurinol concentration was found to increase with decreasing renal function. Although there is a positive relationship between change in oxypurinol and change in SU concentration, a minimum therapeutic oxypurinol is dependent on CrCL and cannot reliably predict SU target. Other variables, including ABCG2 Q141K genotype, impact on sensitivity to allopurinol (ACTRN12611000845932).

Evaluation of Assumptions Underpinning Pharmacometric Models

Assumptions inherent to pharmacometric model development and use are not routinely acknowledged, described, or evaluated. The aim of this work is to present a framework for systematic evaluation of assumptions. To aid identification of assumptions, we categorise assumptions into two types: implicit and explicit assumptions. Implicit assumptions are inherent in a method or model and underpin its derivation and use. Explicit assumptions arise from heuristic principles and are typically defined by the user to enable the application of a method or model. A flowchart was developed for systematic evaluation of assumptions. For each assumption, the impact of assumption violation ('significant', 'insignificant', 'unknown') and the probability of assumption violation ('likely', 'unlikely', 'unknown') will be evaluated based on prior knowledge or the result of an additional bespoke study to arrive at a decision ('go', 'no-go') for both model building and model use. A table of assumptions with standardised headings has been proposed to facilitate the documentation of assumptions and evaluation of results. The utility of the proposed framework was illustrated using four assumptions underpinning a top-down model describing the warfarin-coagulation proteins' relationship. The next step of this work is to apply the framework to a series of other settings to fully assess its practicality and its value in identifying and making inferences from assumptions.

Understanding the process of clinical judgement for pharmacists when making clinical decisions

Clinical decision-making is arguably the most important and underappreciated skill in pharmacy. It can be described as four discrete steps: information gathering, clinical reasoning and judgement and, the decision process. The information gathering and decision negotiation steps and to some extent clinical reasoning are addressed either implicitly or explicitly by practitioners and educators. Clinical judgement, however, remains a largely unexplored concept for clinical decision-making in healthcare therapeutics. It defines how practitioners arrive at a favourable treatment strategy and, due to the often complicated benefit:risk evaluations, is often linked with concepts relating to ambiguity. In this article, we use game theory to explore the judgement stage of clinical decision-making. Game theory allows us to provide a quantitative evaluation of clinical judgement and explore concepts such as ambiguity and its sources in healthcare. Clarifying the elements involved in the judgement stage of clinical decision-making will enable a better understanding of how pharmacists contribute patient care in healthcare teams.

A factor VII-based method for the prediction of anticoagulant response to warfarin

Warfarin dosing methods based on existing models for warfarin and the international normalised ratio (INR) give biased maintenance dose predictions at the upper and lower quantiles of dose requirements. The aim of this work is to propose a conceptually different approach to predict INR after warfarin dosing. Factor VII concentration was proposed as the principal driving force for the INR. The time to steady-state INR (t_SS,INR) was determined based on the INR response to changes in factor VII concentrations following warfarin initiation, and from this the steady-state INR (INR_SS) was derived. The proposed method requires timed, paired blood samples of INR and factor VII. At different simulated warfarin dose rates, the prediction error associated with the proposed method was shown to be within clinically acceptable limits for both the t_SS,INR (±2 days) and INR_SS (±0.2). The use of the method was demonstrated in two patients who were initiated with 5 mg of warfarin daily. The difference in predicted versus actual steady-state INR were 0.0 and −0.4. The proposed method represents a unique approach to predict the INR. It considers factor VII as the main driver for INR and provides valuable information about the time to steady state INR.

A Joint Model for Vitamin K-Dependent Clotting Factors and Anticoagulation Proteins

BACKGROUND

Warfarin acts by inhibiting the reduction of vitamin K (VK) to its active form, thereby decreasing the production of VK-dependent coagulation proteins. The aim of this research is to develop a joint model for the VK-dependent clotting factors II, VII, IX and X, and the anticoagulation proteins, proteins C and S, during warfarin initiation.

METHODS

Data from 18 patients with atrial fibrillation who had warfarin therapy initiated were available for analysis. Nine blood samples were collected from each subject at baseline, and at 1-5, 8, 15 and 29 days after warfarin initiation and assayed for factors II, VII, IX and X, and proteins C and S. Warfarin concentration-time data were not available. The coagulation proteins data were modelled in a stepwise manner using NONMEM^® Version 7.2. In the first stage, each of the coagulation proteins was modelled independently using a kinetic-pharmacodynamic model. In the subsequent step, the six kinetic-pharmacodynamic models were combined into a single joint model.

RESULTS

One patient was administered VK and was excluded from the analysis. Each kinetic-pharmacodynamic model consisted of two parts: (1) a common one-compartment pharmacokinetic model with first-order absorption and elimination for warfarin; and (2) an inhibitory E _max model linked to a turnover model for coagulation proteins. In the joint model, an unexpected pharmacodynamic lag was identified and the estimated degradation half-life of VK-dependent coagulation proteins were in agreement with previously published values. The model provided an adequate fit to the observed data.

CONCLUSION

The joint model represents the first work to quantify the influence of warfarin on all six VK-dependent coagulation proteins simultaneously. Future work will expand the model to predict the influence of exogenously administered VK on the time course of clotting factor concentrations after warfarin overdose and during perioperative warfarin reversal procedures.

'Massive' metformin overdose

Massive metformin overdose can cause metabolic acidosis with hyperlactatemia. A 55-year-old woman presented 5 h after multidrug overdose, including 132 g extended-release metformin. Continuous venovenous haemodiafiltration (CVVHDF) and noradrenaline were commenced due to metabolic acidosis (pH 7.0, lactate 17 mmol l^-1 ) and shock. Despite 3 h of CVVHDF, her acidosis worsened (pH 6.83, lactate 24 mmol l^-1 ). Intermittent haemodialysis (IHD) improved acidosis (pH 7.13, lactate 26 mmol l^-1 ) but again worsened (pH 6.91, lactate 30 mmol l^-1 ) with CVVHDF recommencement. IHD (12 h), CVVHDF (26 h) and vasopressor support for 7 days resulted in survival. Measured metformin concentrations were extremely high with a peak of 292 μg ml^-1 at 8 h postingestion. IHD, but not CVVHDF in this case, was associated with improvement in metabolic acidosis and hyperlactataemia. Pharmacokinetic analysis of metformin concentrations found a reduced apparent oral clearance of 8.2 l h^-1 and a half-life of approximately 30 h. During IHD, the apparent oral clearance increased to 22.2 l h^-1 with an approximate half-life of 10 h. The impact of prolonged oral absorption from a pharmacobezoar and redistribution of metformin from peripheral sites (including erythrocytes) on the pharmacokinetic profile cannot be determined from the data available.

The impact of diuretic use and ABCG2 genotype on the predictive performance of a published allopurinol dosing tool

AIM

This research aims to evaluate the predictive performance of a published allopurinol dosing tool.

METHODS

Allopurinol dose predictions were compared to the actual dose required to achieve serum urate (SU) <0.36 mmol l^-1 using mean prediction error. The influence of patient factors on dose predictions was explored using multilinear regression.

RESULTS

Allopurinol doses were overpredicted by the dosing tool; however, this was minimal in patients without diuretic therapy (MPE 63 mg day^-1 , 95% CI 40-87) compared to those receiving diuretics (MPE 295 mg day^-1 , 95% CI 260-330, P < 0.0001). ABCG2 genotype (rs2231142, G>T) had an important impact on the dose predictions (MPE 201, 107, 15 mg day^-1 for GG, GT and TT, respectively, P < 0.0001). Diuretic use and ABCG2 genotype explained 53% of the variability in prediction error (R²  = 0.53, P = 0.0004).

CONCLUSIONS

The dosing tool produced acceptable maintenance dose predictions for patients not taking diuretics. Inclusion of ABCG2 genotype and a revised adjustment for diuretics would further improve the performance of the dosing tool.

Deterministic identifiability of population pharmacokinetic and pharmacokinetic-pharmacodynamic models

Identifiability is an important component of pharmacokinetic-pharmacodynamic (PKPD) model development. Structural identifiability is concerned with the uniqueness of the model parameters for a set of perfect input-output data and deterministic identifiability with the precision of parameter estimation given imperfect input-output data. We introduce two subcategories of deterministic identifiability, external and internal, and consider factors that distinguish between these forms. We define external deterministic identifiability as a function of externally controllable variables, i.e., the design, and internal deterministic identifiability as a function of the model and its parameter values. The concepts are explored using three common PK and PKPD models, and verified for their precision for the selected set of parameter values under optimal design.

Individualising the dose of allopurinol in patients with gout

AIMS

The aims of the study were to: 1) determine if a plasma oxypurinol concentration-response relationship or an allopurinol dose-response relationship best predicts the dose requirements of allopurinol in the treatment of gout; and 2) to construct a nomogram for calculating the optimum maintenance dose of allopurinol to achieve target serum urate (SU) concentrations.

METHODS

A nonlinear regression analysis was used to examine the plasma oxypurinol concentration- and allopurinol dose-response relationships with serum urate. In 81 patients (205 samples), creatinine clearance (CL_CR ), concomitant diuretic use and SU concentrations before (U_P ) and during (U_T ) treatment were monitored across a range of allopurinol doses (D, 50-700 mg daily). Plasma concentrations of oxypurinol (C) were measured in 47 patients (98 samples). Models (n = 47 patients) and predictions from each relationship were compared using F-tests, r² values and paired t-tests. The best model was used to construct a nomogram.

RESULTS

The final plasma oxypurinol concentration-response relationship (U_T  = U_P  - C*(U_P  - U_R )/(ID₅₀  + C), r²  = 0.64) and allopurinol dose-response relationship (U_T  = U_P  - D^* (U_P  - U_R )/(ID₅₀  + D), r²  = 0.60) did not include CL_CR or diuretic use as covariates. There was no difference (P = 0.87) between the predicted SU concentrations derived from the oxypurinol concentration- and allopurinol dose-response relationships. The nomogram constructed using the allopurinol dose-response relationship for all recruited patients (n = 81 patients) required pretreatment SU as the predictor of allopurinol maintenance dose.

CONCLUSIONS

Plasma oxypurinol concentrations, CL_CR and diuretic status are not required to predict the maintenance dose of allopurinol. Using the nomogram, the maintenance dose of allopurinol estimated to reach target concentrations can be predicted from U_P .

A general empirical model for renal drug handling in pharmacokinetic analyses

Dose adjustment in renal insufficiency is generally based on the assumption that renal drug clearance is related linearly to glomerular filtration rate. The theory underpinning this model is the intact nephron hypothesis, which says that impaired renal function is caused by a reduction in the number of complete (intact) nephrons. The purpose of the present commentary is to propose a general empirical model for renal drug handling. We will explore models for renal function under two scenarios: one that aligns with the intact nephron hypothesis, and one that relaxes the assumptions of this hypothesis. We propose that a nonlinear, non-intact nephron model will allow for differences in renal drug handling, while incorporating the intact nephron hypothesis model as a special case.

Predicting allopurinol response in patients with gout

AIMS

The primary aim of this research was to predict the allopurinol maintenance doses required to achieve the target plasma urate of ≤0.36 mmol l(-1) .

METHODS

A population analysis was conducted in nonmem using oxypurinol and urate plasma concentrations from 133 gout patients. Maintenance dose predictions to achieve the recommended plasma urate target were generated.

RESULTS

The urate response was best described by a direct effects model. Renal function, diuretic use and body size were found to be significant covariates. Dose requirements increased approximately 2-fold over a 3-fold range of total body weight and were 1.25-2 fold higher in those taking diuretics. Renal function had only a modest impact on dose requirements.

CONCLUSIONS

Contrary to current guidelines, the model predicted that allopurinol dose requirements were determined primarily by differences in body size and diuretic use. A revised guide to the likely allopurinol doses to achieve the target plasma urate concentration is proposed.

What do we learn from repeated population analyses?

Population analyses are performed on new and existing drugs. They play an important role in quantifying the time course of drug effects and provide a means of understanding the impact of variability between individuals on dosing requirements. For some drugs there have been several population analyses reported in the literature. It is important to understand how repeated population analyses can value add and what authors and readers can consider when reviewing such analyses. The purpose of this review is to explore what is learnt from repeated population analyses and provide an understanding of how the value-added nature of these analyses can be considered.

A proposal for dose-adjustment of dabigatran etexilate in atrial fibrillation guided by thrombin time

Dabigatran is an oral anticoagulant that is increasingly used for atrial fibrillation (AF). Presently, many authorities state that routine laboratory coagulation monitoring is not required. However, data have recently been published demonstrating that higher trough plasma dabigatran concentrations are associated with lower thromboembolic and higher haemorrhagic event rates. Using these data, we simulate a range of AF patients with varying risks for these events and derive a target range of trough plasma dabigatran concentrations (30-130 μg l(-1) ). Finally, we propose that a conventional screening coagulation assay, the thrombin time (TT), can be used to discern whether or not patients are within this range of dabigatran concentrations.

Coagulation assays and plasma fibrinogen concentrations in real-world patients with atrial fibrillation treated with dabigatran

AIMS

In patients with atrial fibrillation prescribed dabigatran, the aim was to examine the correlation between plasma dabigatran concentrations and the three screening coagulation assays [international normalized ratio (INR), activated partial thromboplastin time (aPTT) and thrombin time (TT)] as well as the dilute thrombin time (dTT) and to examine the contribution of plasma fibrinogen concentrations to the variability in TT results.

METHODS

Plasma from patients with atrial fibrillation on dabigatran were analysed for clotting times and concentrations of fibrinogen and dabigatran. Correlation plots (and associated r(2) values) were generated using these data. The variability in TT results explained by fibrinogen concentrations was quantified using linear regression.

RESULTS

Fifty-two patients (38-94 years old) contributed 120 samples, with plasma dabigatran concentrations ranging from 9 to 408 μg l(-1) . The r(2) values of INR, aPTT, TT and dTT against plasma dabigatran concentrations were 0.49, 0.54, 0.70 and 0.95, respectively. Plasma fibrinogen concentrations explained some of the residual variability in TT values after taking plasma dabigatran concentrations into account (r(2) = 0.12, P = 0.02).

CONCLUSIONS

Of the screening coagulation assays, the TT correlated best with plasma dabigatran concentrations. Variability in fibrinogen concentrations accounts for some of the variability in the TT.

Correlation between trough plasma dabigatran concentrations and estimates of glomerular filtration rate based on creatinine and cystatin C

AIMS

Dabigatran is largely cleared by renal excretion. Renal function is thus a major determinant of trough dabigatran concentrations, which correlate with the risk of thromboembolic and haemorrhagic outcomes. Current dabigatran dosing guidelines use the Cockcroft-Gault (CG) equation to gauge renal function, instead of contemporary equations including the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations employing creatinine (CKD-EPI_Cr), cystatin C (CKD-EPI_Cys) and both renal biomarkers (CKD-EPI_CrCys).

METHODS

A linear regression model including the dabigatran etexilate maintenance dose rate, relevant interacting drugs and genetic polymorphisms (including CES1), was used to analyse the relationship between the values from each renal function equation and trough steady-state plasma dabigatran concentrations.

RESULTS

The median dose-corrected trough steady-state plasma dabigatran concentration in 52 patients (38-94 years) taking dabigatran etexilate was 60 µg/L (range 9-279). The dose-corrected trough concentration in a patient on phenytoin and phenobarbitone was >3 standard deviations below the cohort mean. The CG, CKD-EPI_Cr, CKD-EPI_Cys and CKD-EPI_CrCys equations explained (R (2), 95 % CI) 32 % (9-55), 37 % (12-60), 41 % (16-64) and 47 % (20-69) of the variability in dabigatran concentrations between patients, respectively. One-way analysis of variance (ANOVA) comparing the R (2) values for each equation was not statistically significant (p = 0.74).

DISCUSSION

Estimates of renal function using the four equations accounted for 32-47 % of the variability in dabigatran concentrations between patients. We are the first to provide evidence that co-administration of phenytoin/phenobarbitone with dabigatran etexilate is associated with significantly reduced dabigatran exposure.

Impaired response or insufficient dosage? Examining the potential causes of "inadequate response" to allopurinol in the treatment of gout

OBJECTIVES

Gout is one of the most common forms of arthritis. It is well established that urate-lowering therapy that aims for a serum urate less than at least 0.36 mmol/l (6 mg/dl) is required for the successful management of gout. Allopurinol, a xanthine oxidase (XO) inhibitor, is the most commonly used urate-lowering therapy. However, many patients fail to achieve the target serum urate on allopurinol; these patients can be considered to have "inadequate response" to allopurinol. Herein, we examine the potential mechanisms and implications of inadequate response to allopurinol.

METHODS

The literature was reviewed for potential causes for failure to reach target serum urate in patients receiving allopurinol.

RESULTS

The two most common causes of inadequate response to allopurinol are poor adherence and under-dosing of allopurinol. Adherent patients who fail to achieve target serum urate on standard doses of allopurinol form a group that could be considered to be "partially resistant" to allopurinol. There are four potential mechanisms for partial allopurinol resistance: decreased conversion of allopurinol to oxypurinol; increased renal excretion of oxypurinol; abnormality in XO structure and/or function such that oxypurinol is rendered less effective and/or drug interactions.

CONCLUSIONS

It is important to determine the reasons for failure to achieve treatment targets with allopurinol, particularly as newer agents become available. The knowledge of the mechanisms for inadequate response may help guide the clinician towards making a therapeutic choice that is more likely to result in achieving the serum urate target.

Dabigatran: rational dose individualisation and monitoring guidance is needed

Dabigatran is the first oral anticoagulant to be introduced in New Zealand without prescribing restrictions for over 50 years. Not surprisingly, the drug has created a great deal of interest amongst health care providers as well as the general public and media. There seems to be a general feeling that warfarin, with its requisite dose adjustments and INR monitoring, is an outdated drug and should be shelved in favour of this novel agent. The assumption is that the newer drug must be better and safer as well as easier to use. Much of the literature associated with dabigatran encourages this view, stressing that dabigatran is a 'game changer' with the advantage of fixed dosing for most patients and no anticoagulation monitoring. In this paper we question whether dabigatran can really live up to these expectations. We suggest that the safe and effective prescribing of dabigatran, like all anticoagulants used in therapeutic doses, will most likely require dose individualisation and selective monitoring. This requirement should not be viewed as a failure for dabigatran but rather as a success for rational therapeutics.

Interpreting population pharmacokinetic-pharmacodynamic analyses - a clinical viewpoint

The population analysis approach is an important tool for clinical pharmacology in aiding the dose individualization of medicines. However, due to their statistical complexity the clinical utility of population analyses is often overlooked. One of the key reasons to conduct a population analysis is to investigate the potential benefits of individualization of drug dosing based on patient characteristics (termed covariate identification). The purpose of this review is to provide a tool to interpret and extract information from publications that describe population analysis. The target audience is those readers who are aware of population analyses but have not conducted the technical aspects of an analysis themselves. Initially we introduce the general framework of population analysis and work through a simple example with visual plots. We then follow-up with specific details on how to interpret population analyses for the purpose of identifying covariates and how to interpret their likely importance for dose individualization.

Understanding the time course of pharmacological effect: a PKPD approach

The key concepts that underpin the choice of drug and dosing regimen are an understanding of the drugs' effectiveness, the potential for adverse effects, and the expected time course over which both desired and adverse effects are likely to occur. Research in clinical pharmacology should therefore address three fundamental questions: (1) What is the magnitude of drug effects (beneficial or adverse) from a given dose? (2) How quickly will any given effects occur? (3) How long will these effects last? Under steady-state conditions, only the magnitude of drug effects can be examined. This requires researchers to consider non-steady-state conditions, which require more complex models and an understanding of the mechanisms that drive the time course of drug effect. The aim of this review is to provide a conceptual framework for understanding the time course of drug effects using pharmacokinetic-pharmacodynamic models. Key examples will illustrate how this can inform the optimal use of drugs in the clinic.