Daptomycin Exposure as a Risk Factor for Daptomycin-Induced Eosinophilic Pneumonia and Muscular Toxicity

Daptomycin for Pediatric Complex Bone and Joint Infections: Real-world Efficacy and Safety Data from a Three-year Study

Bone and joint infections present a significant therapeutic challenge in children, particularly in complex or chronic cases. Staphylococcus aureus is the most common causative pathogen, with methicillin resistance rates varying by geographic location and hospital setting, underscoring the need for antibiotics effective against both methicillin-sensitive Staphylococcus aureus and methicillin-resistant Staphylococcus aureus. Daptomycin, a cyclic lipopeptide antibiotic effective against gram-positive pathogens, is increasingly used off-label in pediatric osteomyelitis. This prospective study evaluates its real-world application, focusing on clinical outcomes, dosing strategies, safety, and therapeutic potential. Over a 3-year period, 20 children (median age: 13.5 years) with bone and joint infections were treated with daptomycin. The patient cohort was highly complex, with 70% having severe orthopedic or medical comorbidities. Methicillin-sensitive Staphylococcus aureus was isolated in 60% of cases, while MRSA was identified in 35%. Daptomycin was administered following bacteremia dosing guidelines, with some patients receiving higher doses (mean: 10 mg/kg). The median duration of daptomycin therapy was 24.5 days. Treatment was successful in 90% of cases, often transitioning to oral antibiotic therapy. C-reactive protein levels showed a median reduction of 90%. A composite score evaluating clinical response-including C-reactive protein levels, type of continuation therapy, and the need for surgery-indicated substantial improvement in the majority of patients, with a median score of 4. No severe adverse events were recorded, though transient neutropenia and elevated creatine kinase levels were observed in 2 cases. This study underscores daptomycin's safety and efficacy in treating complex pediatric osteoarticular infections and suggests its potential as a first-line therapy, particularly for MRSA cases. The comprehensive data reflect the current microbiological landscape of pediatric bone and joint infections, supporting the reconsideration of daptomycin's role in initial treatment protocols. Further research and controlled trials are warranted to confirm these findings and optimize treatment strategies.

Therapeutic drug monitoring of antibiotics for methicillin-resistant Staphylococcus aureus infections: an updated narrative review for clinicians

BACKGROUND

Infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are associated with high mortality rates. Optimal antibiotic dosage plays a crucial role in reducing MRSA burden; thus, the use of therapeutic drug monitoring (TDM) in the clinical practice, especially of new drugs such as ceftobiprole, ceftaroline, dalbavancin, and oritavancin, should be implemented.

OBJECTIVES

We aim to examine and summarize the available evidence about TDM of anti-MRSA molecules, with a focus on pneumonia, endocarditis and vascular infections, and bone and joint infections.

SOURCES

We applied 'therapeutic drug monitoring' and 'Staphylococcus aureus' as search terms in PubMed, considering a time frame of 24 years (2001-2024). Articles in English language, non-duplicated, evaluating antibiotic therapeutic target, and role of TDM were included in the study.

CONTENT

In this review, available data for therapeutic target and TDM were critically analysed and summarized and suggestions about the use of old and new anti-MRSA antibiotics were provided, focusing on optimal dosages, tissue penetration according to infection types, and toxicity. Limitations to the widespread use of TDM in clinical practice were discussed.

IMPLICATIONS

The use of TDM may play an important role for the optimal management of patients with MRSA infections and may impact on patient outcomes by increasing efficacy and reducing the risk of adverse events. TDM may be implemented in clinical practice; however, several limitations such as the wide variability in the methodology and the need for skilled personnel need to be considered.

PK/PD Analysis of High-Dose Daptomycin Use in the Treatment of Bone and Joint Infections: Data from a Real-World Setting

BACKGROUND

Daptomycin is widely used in bone and joint infections (BJIs) caused by Gram-positive cocci. The pharmacokinetics of daptomycin are characterized by relevant variability in terms of drug exposure. Due to these pharmacological properties, the dosing suggested by the Summary of medical Product Characteristics could result in sub-therapeutic or toxic concentrations, especially considering the high doses recommended for BJIs. Therapeutic Drug Monitoring (TDM) of daptomycin helps clinicians in verifying the patient's exposure, due to the lack of pharmacokinetic/pharmacodynamic (PK/PD) data in this clinical setting.

METHODS

We retrospectively analyzed 170 daptomycin plasma concentrations of 77 patients with BJIs from July 2022 to December 2023. We focused on the pharmacokinetics of daptomycin to investigate when drug plasma concentrations achieved adequate PK/PD targets.

RESULTS

In the first TDM, 7.8% of patients were underexposed according to the estimated area under the curve (eAUC0-24h < 666 mg·h/L), whereas 35.1% were on target according to both the eAUC and trough plasma concentration (eAUC0-24h 666 - 939 mg·h/L; Cmin < 24.3 mg/L). The patients who were overexposed had trough plasma concentrations > 24.3 mg/L (27.3%) or eAUC0-24h > 1174 mg·h/L (33.8%). Differences in drug exposure were observed according to weight and sex.

CONCLUSIONS

Due to the difficult management of this drug's dosing, analyzing daptomycin plasma concentrations through TDM represents a powerful tool in BJIs.

Limited sampling approach for model-informed precision dosing of daptomycin to rapidly achieving the target area under the concentration-time curve: A simulation study

Daptomycin, an anti-methicillin-resistant Staphylococcus aureus drug, causes exposure-dependent muscle toxicity and eosinophilic pneumonia. Although the area under the concentration-time curve (AUC)-guided dosing is crucial, an optimal blood sampling strategy is lacking. This study aimed to identify an optimal limited sampling strategy using Bayesian forecasting to rapidly achieve the target AUC. Two validated population pharmacokinetic models generated a virtual population of 1000 individuals (models 1 and 2 represent diverse patients and kidney transplant recipients, respectively). The AUC for each blood sample was assessed using the probability of achieving the estimated/reference AUC ratio on the second day (AUC24-48) and at the steady state (AUCss). In Model 1, Bayesian posterior probabilities for AUC24-48 increased from 50.7% (a priori) to 59.4% and for AUCss from 48.9% (a priori) to 61.9%, with one-point Ctrough sampling at 24 h. With two-point sampling at 7 and 24 h, the probabilities increased to 73.8% for AUC24-48 and 69.7% for AUCss. In Model 2, the probabilities for both AUC24-48 and AUCss with one-point Ctrough or two-point sampling incorporating Ctrough sampling increased compared to a priori probabilities. These results suggest that two-point sampling incorporating Ctrough during initial dosing enhanced achieving the target AUC24-48 and AUCss rapidly.

A prospective study to evaluate high dose daptomycin pharmacokinetics and pharmacodynamics in Staphylococcus spp. infective endocarditis

Background

Daptomycin pharmacokinetics and pharmacodynamics data relative to higher doses in patients are necessary for clinical practice.

Objectives

A monocentric, prospective study that enrolled patients with a diagnosis of Staphylococcus spp. infective endocarditis treated with daptomycin according to clinical practice, to evaluate the pharmacokinetics/pharmacodynamics of different daptomycin daily doses (group A: 8-10 and group B: 11-12 mg/kg).

Design and methods

A monocentric, prospective, cohort study that enrolled patients with a diagnosis of Staphylococcus spp. infective endocarditis treated with daptomycin. Daptomycin was administered by intravenous infusion over a 30-min period for at least five consecutive days before PK study.

Results

Twenty-two patients were included. Native valve infectious endocarditis (IE) was diagnosed in 9 patients, prosthetic valve IE was diagnosed in 10 patients and 3 patients had concomitant intracardiac device infections. All patients showed a microbiologic response with negative blood cultures by day 5 (1-3 interquartile rate (IQR) 3-8). The median calculated AUC0-24 was 1298 (1-3 IQR 1069-1484) and 1459 (1-3 IQR 1218-1711) µg*h/mL, with the corresponding clearance of 0.49 (1-3 IQR 0.37-0.57) and 0.57 (1-3 IQR 0.40-0.71) L/h, respectively. A value of area under the curve/minimum inhibitory concentration (AUC/MIC) > 666 was reached by all patients; however, 4 out of 15 patients in group A and 1 out of 14 patients in group B did not reach the pharmacokinetic/pharmacodynamic (PK/PD) target of 1061; therefore, AUC/MIC equal to or above 1061 was reached by 73.3% in group A and 92.9% in group B.

Conclusion

From a PK/PD point of view, all patients reached the value of AUC/MIC > 666, while roughly 70% of patients in group A and 90% in group B reached the target value of AUC/MIC>1061. Even if this cut-off value is arbitrary, 11-12 mg/kg daily dose could be taken into consideration in case of serious infections characterised by a high inoculum or in cases of prosthetic valve infections.

Daptomycin eosinophilic pneumonia, a systematic review of the literature and case series

PURPOSE

Daptomycin-induced eosinophilic pneumonia (DIEP) is a rare yet severe adverse event that requires rapid recognition and management. Diagnosing a definite case is challenging and involves meeting the American Thoracic Society (ATS) criteria, although alternative criteria have been suggested. This study aims to conduct a systematic review of literature and includes a case series.

METHODS

Six cases of DIEP identified at Perugia Hospital, Perugia, Italy have been described. A systematic review was carried out adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement guidelines.

RESULTS

a total of 74 cases of DIEP were analysed. Using ATS clinical criteria, 15 were classified as definite (20.3%), 54 as probable (73.0%), and 5 as possible (6.8%). Phillips criteria and the Lyon Algorithm identified 43/74 (58.2%) and 64/67 (95.5%) cases as definite, respectively. Bronchoalveolar lavage (BAL) was performed in 43 cases, revealing an average eosinophil count of 28.6% (SD 24.4). Radiological findings highlighted recurring features like bilateral opacities (68.1%), ground-glass opacities (41.7%), patchy infiltrates (30.6%), and peripheral predominance (19.4%). Upon suspicion, daptomycin was discontinued; 20 cases required no additional treatment, 38 received corticosteroids, and 12 received both corticosteroids and antibiotics. Recovery rates were high across all treatment types (≥ 73.7%). Most reports described rapid improvement post-withdrawal (within 96 h).

CONCLUSIONS

DIEP is a rare, fast-progressing condition where early diagnosis and prompt treatment are vital. Diagnosis relies on clinical, laboratory, and radiological evaluations. Stopping daptomycin is essential, with corticosteroids often necessary. Further research is needed to enhance diagnostic accuracy for this disease.

Revolutionizing Daptomycin Dosing: A Single 7-11-Hour Sample for Pragmatic Application

Precision daptomycin dosing faces clinical implementation barriers despite known exposure-safety concerns with the use of twice the regulatory-approved doses. We propose achieving a single 7-11-hour post-dose plasma target concentration of 30 mg/L to 43 mg/L to be a practical starting point to facilitate precision daptomycin dosing.

Daptomycin Dosage Optimization in Renal Impairment Using Model-Informed Precision Dosing

BACKGROUND

Daptomycin's efficacy and toxicity are closely related to its exposure, which can vary widely among individuals. The patient, a 59-year-old male with an estimated glomerular filtration rate (eGFR) of 12 mL/min/1.73 m² and a weight of 64 kg, was treated with 850 mg of daptomycin every other day for infective endocarditis caused by methicillin-resistant Staphylococcus aureus (MRSA). For patients with an estimated glomerular filtration rate of less than 30 mL/min/1.73 m², the dosing recommendations are not explicitly defined in the endocarditis guidelines. Subsequently, the pharmacology department was contacted to adjust the dosage.

METHODS

A population pharmacokinetic model developed by Dvorchik et al. was used for Bayesian estimation of the patient's pharmacokinetic parameters. The 24-hour area under the curve (AUC24) of daptomycin was calculated at steady state using peak and trough plasma samples.

RESULTS

The minimum inhibitory concentration (MIC) of the MRSA strain was 0.25 mg/L. An AUC24/MIC ratio below 666 is associated with higher mortality risk, while an AUC24 above 939 h·mg/L correlates with increased risk of muscular toxicity. Initial AUC24 estimation was 1091 h·mg/L. Following a dosage reduction to 700 mg every other day, the AUC24 increased to 1600 h·mg/L. Further reduction to 500 mg every other day brought the AUC24 down to 750 h mg/L, with two subsequent measurements showing consistent AUC24 values of 500 h·mg/L, which is within the target range.

CONCLUSIONS

Daptomycin ended 6 weeks after the initial negative blood culture, with no adverse effects or recurrence of MRSA infection. This case underscores the need for therapeutic drug monitoring and a multidisciplinary approach to adjust daptomycin doses in patients with renal impairment.

Fixed dose daptomycin: An opportunity for pharmacokinetic/pharmacodynamic optimization in Staphylococcus aureus infections

BACKGROUND

Daptomycin is a high-use intravenous antimicrobial agent affording the convenience of once-daily dosing. Prior studies suggest an opportunity to use a more operationally convenient fixed rather than weight-based dosing but this approach has not been studied prospectively.

METHODS

This study quantified the probability of toxicity and efficacy end points by prospectively testing a fixed dose regimen of daptomycin (750 mg) in obese and non-obese adults. At least, three daptomycin concentrations were measured at steady-state for each patient. A population pharmacokinetic model was constructed to evaluate concentration-time profiles and investigate covariates of daptomycin clearance. Simulations were performed to evaluate the probability of achieving efficacy (24-h area under the curve (AUC0-24) ≥ 666 mg∙h/L) and toxicity (minimum concentration (C min) ≥24.3 mg/L) targets for fixed (500-1000 mg) and weight-based (6-12 mg/kg) daptomycin doses.

RESULTS

Thirty-one patients (16 females, 15 males) with median (interquartile range (IQR)) age of 50 (30, 62) years and weight of 74 (54, 156) kg were included in the final analysis. Fixed dose daptomycin (750 mg) resulted in similar exposure across weights with a median (IQR) AUC0-24 of 819 (499, 1501) mg∙h/L and 749 (606, 1265) mg∙h/L in patients weighing ≤74 kg and >74 kg, respectively. Overall, male sex and increased kidney function necessitate higher fixed and weight-based doses to achieve efficacy. Creatine phosphokinase elevation was observed in two patients (6.5%) and predicted to be lower with fixed versus weight-based regimens.

CONCLUSIONS

Fixed daptomycin dosing adjusted for sex and kidney function is expected to improve the efficacy-to-toxicity ratio, transitions of care, and costs compared to weight-based doses. However, no empiric dosing approach is predicted to achieve ≥90% efficacy while minimizing the risk of toxicity, so therapeutic drug monitoring should be considered on a patient-specific basis.

A machine learning approach to predict daptomycin exposure from two concentrations based on Monte Carlo simulations

Daptomycin is a concentration-dependent lipopeptide antibiotic for which exposure/effect relationships have been shown. Machine learning (ML) algorithms, developed to predict the individual exposure to drugs, have shown very good performances in comparison to maximum a posteriori Bayesian estimation (MAP-BE). The aim of this work was to predict the area under the blood concentration curve (AUC) of daptomycin from two samples and a few covariates using XGBoost ML algorithm trained on Monte Carlo simulations. Five thousand one hundred fifty patients were simulated from two literature population pharmacokinetics models. Data from the first model were split into a training set (75%) and a testing set (25%). Four ML algorithms were built to learn AUC based on daptomycin blood concentration samples at pre-dose and 1 h post-dose. The XGBoost model (best ML algorithm) with the lowest root mean square error (RMSE) in a 10-fold cross-validation experiment was evaluated in both the test set and the simulations from the second population pharmacokinetic model (validation). The ML model based on the two concentrations, the differences between these concentrations, and five other covariates (sex, weight, daptomycin dose, creatinine clearance, and body temperature) yielded very good AUC estimation in the test (relative bias/RMSE = 0.43/7.69%) and validation sets (relative bias/RMSE = 4.61/6.63%). The XGBoost ML model developed allowed accurate estimation of daptomycin AUC using C0, C1h, and a few covariates and could be used for exposure estimation and dose adjustment. This ML approach can facilitate the conduct of future therapeutic drug monitoring (TDM) studies.