Population Pharmacokinetic Analysis of Daptomycin in Patients With Osteoarticular Infections

Joint Infection Clinical Trial

Official title:

Population Pharmacokinetic Analysis of Daptomycin in Patients With Osteoarticular Infections

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT03134521
• Other study ID #: 69HCL17_0182
• Status: Active, not recruiting
• Phase: N/A
• First received: March 29, 2017
• Last updated: May 10, 2017
• Start date: December 1, 2016
• Est. completion date: June 30, 2017

Study information

• Verified date: May 2017
• Source: Hospices Civils de Lyon
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Daptomycin is validated as a treatment of bone and joint infections by the Infectious Disease Society of America. However, most of studies did not investigate daptomycin pharmacokinetics in this indication while it is known that efficacy and toxicity concentration studies show a close therapeutic margin.

Evaluation of P-Glycoprotein (P-gp), a transmembrane transport protein, has demonstrated its influence on the concentration and intracellular activity of daptomycin. Recent work has linked the genetic polymorphism of P-gp to the pharmacokinetics of daptomycin, which may explain inter-individual variability but requires further explorations. Previous studies demonstrated existence of interindividual variabilities as sex, renal function and p-glycoprotein polymorphism couple with an intraindividual variabilities unexplained yet.

A population approach will be used to determinate the pharmacokinetics factors, their intra and interindividual variabilities, the parameters associated to those variabilities (as the p glycoprotein).

The investigator's goal is to evaluate different posology and to try to increase daptomycin efficacy and security in bone and joint infection.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 189
• Est. completion date: June 30, 2017
• Est. primary completion date: June 30, 2017
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

Patients

• having had a bone or joint infection, with or without implant,

• having an antibiotherapy with daptomycin between December 2012 and December 2016 at the Croix-Rousse hospital

• are at least 18 years old

Exclusion Criteria:

Related Conditions & MeSH terms

• Bone Infection
• Communicable Diseases
• Infection
• Joint Infection
• Osteomyelitis

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Hospices Civils de Lyon

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Peak plasma concentration (Cmax)		Month 6
Secondary	Area under the concentration-time curve		up to 6 months
Secondary	typical daptomycin clearance and volume of distribution in the population		Month 6
Secondary	Mean daptomycine plasma clearance	(unit, liters per hour)	Month 6
Secondary	Mean daptomycine volume of distribution	(unit, liters)	Month 6
Secondary	Inter-individual coefficient of variation of daptomycin clearance	(unit, %)	Month 6
Secondary	Inter-individual coefficient of variation of daptomycin volume of distribution	(unit, %)	Month 6
Secondary	Intra-individual coefficient of variation of daptomycin clearance	(unit, %)	Month 6
Secondary	Intra-individual coefficient of variation of daptomycin volume of distribution	(unit, %)	Month 6
Secondary	influence of demographic and biological covariates on pharmacokinetics (e.g. : renal function, gender)	the influence of demographic and biological covariates on pharmacokinetics will be assessed statistically by using the Akaike Information Criterion (AIC, no unit). AIC = -2xLL + 2P, where LL is the log-likelihood computed by the population algorithm and P is the number of parameters in the model. A covariate will be considered as significant if it is associated with a decrease in the AIC value compared with the base model without covariate.	Month 6
Secondary	influence of p-glycoprotein pharmacogenetics on daptomycin pharmacokinetics	the influence of P-glycoprotein pharmacogenetics on pharmacokinetics will be assessed statistically by using the Akaike Information Criterion (AIC, no unit). AIC = -2xLL + 2P, where LL is the log-likelihood computed by the population algorithm and P is the number of parameters in the model. The P-glycoprotein genotype will be considered as significant if it is associated with a decrease in the AIC value compared with the base model without covariate.	Month 6