Does renal function matter for polymyxin B?

A pharmacovigilance study of adverse events associated with polymyxins based on the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) database

BACKGROUND

Polymyxins have been regarded as last-line treatment for multidrug-resistant gram-negative bacterial infections. Nonetheless, concerns regarding toxicity persist. This study aimed to explore and compare potential adverse events (AEs) between colistin and polymyxin B (PMB).

METHODS

Outpatient antibiotic use associated with acute upper respiratory infections in China: a nationwide cross-sectional study Polymyxins-related AEs were retrieved from the U.S. Food and Drug Administration Adverse Event Reporting System between 2004 and 2022. Potential signals were estimated by the reporting odds ratio (ROR), and subgroup analyses were preformed to adjust for potential factors in AEs with significant disproportionality.

RESULTS

Analysis of 3,915 records involving 718 patients revealed a higher disproportionality of renal and urinary disorders (ROR 1.62, 95% CI 1.01-2.59) and acute kidney injury (ROR 1.75, 95% CI 1.07-2.87) with colistin treatment. Conversely, colistin exhibited a lower risk for neurotoxicity (ROR 0.47, 95% CI 0.30-0.73). Seven cases of skin hyperpigmentation were reported with PMB, whereas none were reported with colistin. Over 80% of cases involving polymyxin-related AEs occurred during the first two weeks of therapies, with a median onset time of 4.5 days.

CONCLUSIONS

Outpatient antibiotic use associated with acute upper respiratory infections in China: a nationwide cross-sectional study Patients received colistin displayed a higher potential risk of nephrotoxicity but a lower risk of neurotoxicity. Clinicians should be vigilant in monitoring the AEs of hyperpigmentation disorders induced by PMB.

A systematic evaluation of population pharmacokinetic models for polymyxin B in patients with liver and/or kidney dysfunction

Polymyxin B (PMB) is considered a last-line treatment for multidrug-resistant (MDR) gram-negative bacterial infections. Model-informed precision dosing with population pharmacokinetics (PopPK) models could help to individualize PMB dosing regimens and improve therapy. However, the external prediction ability of the established PopPK models has not been fully elaborated. This study aimed to systemically evaluate eleven PMB PopPK models from ten published literature based on a new independent population, which was divided into four different populations, patients with liver dysfunction, kidney dysfunction, liver and kidney dysfunction, and normal liver and kidney function. The whole data set consisted of 146 patients with 391 PMB concentrations. The prediction- and simulation-based diagnostics and Bayesian forecasting were conducted to evaluate model predictability. In the overall evaluation process, none of the models exhibited satisfactory predictive ability in both prediction- and simulation-based diagnostic simultaneously. However, the evaluation of the models in the subgroup of patients with normal liver and kidney function revealed improved predictive performance compared to those with liver and/or kidney dysfunction. Bayesian forecasting demonstrated enhanced predictability with the incorporation of two to three prior observations. The external evaluation highlighted a lack of consistency between the prediction results of published models and the external validation dataset. Nonetheless, Bayesian forecasting holds promise in improving the predictive performance of the models, and feedback from therapeutic drug monitoring is crucial in optimizing individual dosing regimens.

Efficacy and nephrotoxicity of polymyxin B in elderly patients with carbapenem resistant bacterial infection

BACKGROUND

To study the efficacy and nephrotoxicity of polymyxin B in the treatment of elderly patients with carbapenem-resistant organism (CRO) infection.

METHODS

The clinical and microbiological data of patients with CRO-infected sepsis treated with polymyxin B were retrospectively analyzed. The effective rate, bacterial clearance, incidence and recovery rate of acute renal injury (AKI) and prognosis-related indicators in AKI at different stages were compared.

RESULTS

The effective rate of 215 elderly patients with CRO infection treated with polymyxin was 50.7%. The total bacterial clearance rate was 44.2%, the total incidence of AKI was 37.2%, the recovery rate of AKI was 35%, and the incidence range of polymyxin B-related AKI was 10.2-37.2%. Logistic multivariate regression analysis showed that the predictors of AKI in elderly patients were high APACHE II score, long duration of polymyxin, chronic renal insufficiency and ineffective outcome; the ROC curve showed that the cutoff value for predicting AKI was a serum creatinine concentration of 73 mmol/L before polymyxin B use, and the AUC was 0.931.

CONCLUSIONS

Rational use of polymyxin B is safe and effective in elderly patients with CRO infection, and its effective outcome can improve the recovery rate of AKI.

A population pharmacokinetic model of polymyxin B based on prospective clinical data to inform dosing in hospitalized patients

OBJECTIVES

To develop a population pharmacokinetic (PK) model with data from the largest polymyxin B-treated patient population studied to date to optimize its dosing in hospitalized patients.

METHODS

Hospitalized patients receiving intravenous polymyxin B for ≥48 hours were enrolled. Blood samples were collected at steady state and drug concentrations were analysed by liquid chromotography tandem mass spectrometry (LC-MS/MS). Population PK analysis and Monte Carlo simulations were performed to determine the probability of target attainment (PTA).

RESULTS

One hundred and forty-two patients received intravenous polymyxin B (1.33-6 mg/kg/day), providing 681 plasma samples. Twenty-four patients were on renal replacement therapy, including 13 on continuous veno-venous hemodiafiltration (CVVHDF). A 2-compartment model adequately described the PK with body weight as a covariate on the volume of distribution that affected Cmax, but it did not impact clearance or exposure. Creatinine clearance was a statistically significant covariate on clearance, although clinically relevant variations of dose-normalized drug exposure were not observed across a wide creatinine clearance range. The model described higher clearance in CVVHDF patients than in non-CVVHDF patients. Maintenance doses of ≥2.5 mg/kg/day or ≥150 mg/day had a PTA ≥90% (for non-pulmonary infections target) at a steady state for minimum inhibitory concentrations ≤2 mg/L. The PTA at a steady state for CVVHDF patients was lower.

DISCUSSION

Fixed loading and maintenance doses of polymyxin B seemed to be more appropriate than weight-based dosing regimens in patients weighing 45-90 kg. Higher doses may be needed in patients on CVVHDF. Substantial variability in polymyxin B clearance and volume of distribution was found, suggesting that therapeutic drug monitoring may be indicated.

Pharmacokinetics and pharmacodynamics of peptide antibiotics

Antimicrobial resistance is a major global health challenge. As few new efficacious antibiotics will become available in the near future, peptide antibiotics continue to be major therapeutic options for treating infections caused by multidrug-resistant pathogens. Rational use of antibiotics requires optimisation of the pharmacokinetics and pharmacodynamics for the treatment of different types of infections. Toxicodynamics must also be considered to improve the safety of antibiotic use and, where appropriate, to guide therapeutic drug monitoring. This review focuses on the pharmacokinetics/pharmacodynamics/toxicodynamics of peptide antibiotics against multidrug-resistant Gram-negative and Gram-positive pathogens. Optimising antibiotic exposure at the infection site is essential for improving their efficacy and minimising emergence of resistance.

Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients

Polymyxin B (PMB) has reemerged as a last‐line therapy for infections caused by multidrug‐resistant gram‐negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction‐based and simulation‐based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two‐compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model‐informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill.

External evaluation of published population pharmacokinetic models of polymyxin B

OBJECTIVES

Several population pharmacokinetics (popPK) models for polymyxin B have been constructed to optimize therapeutic regimens. However, their predictive performance remains unclear when extrapolated to different clinical centers. Therefore, this study aimed to evaluate the predictive ability of polymyxin B popPK models.

METHODS

A literature search was conducted, and the predictive performance was determined for each selected model using an independent dataset of 20 patients (92 concentrations) from the Third Xiangya Hospital. Prediction- and simulation-based diagnostics were used to evaluate model predictability. The influence of prior information was assessed using Bayesian forecasting.

RESULTS

Eight published studies were evaluated. In prediction-based diagnostics, the prediction error within ± 30% was over 50% in two models. In simulation-based diagnostics, the prediction- and variability-corrected visual predictive check (pvcVPC) showed satisfactory predictivity in three models, while the normalized prediction distribution error (NPDE) tests indicated model misspecification in all models. Bayesian forecasting demonstrated a substantially improvement in the model predictability even with one prior observation.

CONCLUSION

Not all published models were satisfactory in prediction- and simulation-based diagnostics; however, Bayesian forecasting improved the predictability considerably with priors, which can be applied to guide polymyxin B dosing recommendations and adjustments for clinicians.