| Literature DB >> 35892386 |
Pier Giorgio Cojutti1, Sara Tedeschi2,3, Milo Gatti1,3, Eleonora Zamparini2, Marianna Meschiari4, Paola Della Siega5, Maria Mazzitelli6, Laura Soavi7, Raffaella Binazzi8, Elke Maria Erne8, Marco Rizzi7, Anna Maria Cattelan6, Carlo Tascini5, Cristina Mussini4, Pierluigi Viale2,3, Federico Pea1,3.
Abstract
A population pharmacokinetic analysis of dalbavancin was conducted in patients with different infection sites. Non-linear mixed effect modeling was used for pharmacokinetic analysis and covariate evaluation. Monte Carlo simulations assessed the probability of target attainment (PTA) of total dalbavancin concentration ≥ 8.04 mg/L over time (associated with ≥90% probability of optimal pharmacodynamic target attainment of fAUC24h/MIC > 111.1 against S. aureus) associated with a single or double dosage, one week apart, of 1000 or 1500 mg in patients with different classes of renal function. Sixty-nine patients with 289 concentrations were included. Most of them (53/69, 76.8%) had bone and joint infections. A two-compartment model adequately fitted dalbavancin concentration-time data. Creatinine clearance (CLCR) was the only covariate associated with dalbavancin clearance. Monte Carlo simulations showed that, in patients with severe renal dysfunction, the 1000 mg single or double one week apart dosage may ensure optimal PTAs of 2 and 5 weeks, respectively. In patients with preserved renal function, the 1500 mg single or double one-week apart dosage may ensure optimal PTAs of 2 and 4 to 6 weeks, respectively. Therapeutic drug monitoring should be considered mandatory for managing inter-individual variability and for supporting clinicians in long-term treatments of subacute and chronic infections.Entities:
Keywords: dalbavancin; long-term treatment; off-label use; population pharmacokinetics; therapeutic drug monitoring
Year: 2022 PMID: 35892386 PMCID: PMC9331863 DOI: 10.3390/antibiotics11080996
Source DB: PubMed Journal: Antibiotics (Basel) ISSN: 2079-6382
Population characteristics.
| Patient Demographics | |
|---|---|
| Total number of patients | 69 |
| Age (years) | 62 (51–73) |
| Gender (male/female) | 44/25 |
| Weight (kg) | 75 (62–88) |
| Height (cm) | 170 (165–177) |
| Baseline laboratory parameters | |
| CLCR (mL/min/1.73 m2) | 93.0 (72.0–104.0) |
| Albumin (g/dL) | 3.7 (3.3–4.0) |
| C-RP (mg/L) | 3.21 (1.41–6.26) |
| Type of infections | |
| Prosthetic joint infection | 26 (37.7) |
| Osteomyelitis | 11 (15.9) |
| Endovascular prosthetic infections | 9 (13.0) |
| Endocarditis | 7 (10.1) |
| Spondilodiscitis | 5 (7.2) |
| Infected pseudoarthrosis non-unions | 4 (5.8) |
| Septic arthritis | 1 (1.5) |
| Multiple site infections | |
| Endocarditis + spondilodiscitis | 2 (2.9) |
| Endocarditis + septic arthitis | 1 (1.5) |
| Endovascular prosthetic infection + spondilodiscitis | 2 (2.9) |
| Endovascular prosthetic infection + osteomyelitis | 1 (1.5) |
| Patients with identified microbiological isolates | 63 (91.3) |
| Dalbavancin treatment | |
| Number of doses per patient | 2 (2–4) |
| Number of TDM instances per patient | 3 (2–5) |
Data are presented as median (IQR) for continuous variables, and as number (%) for dichotomous variables. C-RP, C-reactive protein; CLCR, creatinine clearance; TDM, therapeutic drug monitoring.
Parameter estimates of the base and final dalbavancin population pharmacokinetic models.
| Parameter | Base Model | Final Model |
|---|---|---|
| Fixed-Effects | ||
| CL (L/h) | 0.041 (4.91) | 0.029 (11.6) |
| βCLcr-CL | - | 0.0043 (28.9) |
| V1 (L) | 6.15 (4.79) | 6.14 (5.26) |
| Q (L/h) | 0.026 (17.9) | 0.026 (18.1) |
| V2 (L) | 10.51 (13.7) | 9.52 (19.0) |
| Random Effects (Inter-patient %CV) | ||
| IIVCL | 31.76 (16.2) | 26.44 (13.3) |
| IIVV1 | 16.10 (33.2) | 16.10 (40.1) |
| IIVQ | 45.06 (34.6) | 50.90 (32.9) |
| IIVV2 | 37.19 (207) | 37.15 (61.7) |
| Residual variability | ||
| b (proportional) | 33.92 (7.96) | 33.92 (5.97) |
% RSE, relative standard error of the estimate; CV, coefficient of variation; CL, total body clearance; V1, central volume of distribution; Q, inter-compartmental clearance; V2, peripheral volume of distribution; IIV, inter-individual variability (associated with CL (IIVCL), with V1 (IIVV1), with Q (IIVQ), with V2 (IIVV2)).
Figure 1Diagnostic plot for the final population pharmacokinetic model. The observed versus population-predicted concentrations (left panel) and observed versus individual-predicted concentrations (right panel) in plasma are shown. Solid and dashed lines refer to linear regression and identity line, respectively, between the observed and the predicted concentrations.
Figure 2Visual predictive check for the final population pharmacokinetic model. Blue dots are the observed dalbavancin concentrations; blue lines represent the median, 10th and 90th percentiles of the observed values; and shaded areas are the prediction intervals for the median (red central area) and 10th and 90th percentiles (light blue lower and upper areas).
Figure 3Probability of attaining a plasma concentration ≥ 8.04 mg/L over time associated with the dosages of 1500 mg on day 1, 1000 mg on day 1 + 500 mg on day 8 and 1500 mg on day 1 + 1500 mg on day 8, according to different classes of renal function. Dashed lines refer to a probability ≥ 90%.
Figure 4Simulated dalbavancin plasma concentration versus time profiles of a two-dosing regimen one week apart in different classes of renal function. The solid line is the simulated median concentration. The dashed lines are the 5th, 25th, 75th, and 95th percentiles of simulated concentrations. The horizontal dashed line is the threshold of concentration (8.04 mg/L) above which the desired pharmacodynamics target of fAUC24h/MIC > 111.1 is granted over time.
Suggested timings (days) for assessing in a timely and cost-effective manner the TDM of dalbavancin in relation to the tested dosing regimens and CLCR classes.
| Drug Dosages | Classes of CLCR (mL/min/1.73 m2) | |||
|---|---|---|---|---|
| ≤30 | 30–59 | 60–89 | 90–120 | |
| 1000 d1 + 1000 d8 | 28 ± 3 | - | - | - |
| 1500 d1 + 1500 d8 | - | 35 ± 3 | 28 ± 3 | 21 ± 3 |