Population Pharmacokinetic Analysis of Daptomycin in Patients With Osteoarticular Infections
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.
Studieoversigt
Status
Status
Betingelser
Betingelser
Undersøgelsestype
Undersøgelsestype
Tilmelding (Faktiske)
Tilmelding
Deltagelseskriterier
Berettigelseskriterier
Berettigelseskriterier
Aldre berettiget til at studere
Tager imod sunde frivillige
Køn, der er berettiget til at studere
Prøveudtagningsmetode
Studiebefolkning
Beskrivelse
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:
- None
Studieplan
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
Hvad måler undersøgelsen?
Primære resultatmål
Primære resultatmål
Resultatmål |
Tidsramme |
|---|---|
|
Peak plasma concentration (Cmax)
Tidsramme: Month 6
|
Month 6
|
Sekundære resultatmål
Sekundære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Area under the concentration-time curve
Tidsramme: up to 6 months
|
up to 6 months
|
|
|
typical daptomycin clearance and volume of distribution in the population
Tidsramme: Month 6
|
Month 6
|
|
|
Mean daptomycine plasma clearance
Tidsramme: Month 6
|
(unit, liters per hour)
|
Month 6
|
|
Mean daptomycine volume of distribution
Tidsramme: Month 6
|
(unit, liters)
|
Month 6
|
|
Inter-individual coefficient of variation of daptomycin clearance
Tidsramme: Month 6
|
(unit, %)
|
Month 6
|
|
Inter-individual coefficient of variation of daptomycin volume of distribution
Tidsramme: Month 6
|
(unit, %)
|
Month 6
|
|
Intra-individual coefficient of variation of daptomycin clearance
Tidsramme: Month 6
|
(unit, %)
|
Month 6
|
|
Intra-individual coefficient of variation of daptomycin volume of distribution
Tidsramme: Month 6
|
(unit, %)
|
Month 6
|
|
influence of demographic and biological covariates on pharmacokinetics (e.g. : renal function, gender)
Tidsramme: Month 6
|
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
|
|
influence of p-glycoprotein pharmacogenetics on daptomycin pharmacokinetics
Tidsramme: Month 6
|
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
|
Samarbejdspartnere og efterforskere
Sponsor
Sponsor
Efterforskere
Efterforskere
- Ledende efterforsker: Tristan Ferry, Hospices Civils de Lyon - Hôpital de la Croix Rousse
Datoer for undersøgelser
Studer store datoer
Studiestart (Faktiske)
Studiestart
Primær færdiggørelse (Forventet)
Primær færdiggørelse
Studieafslutning (Forventet)
Studieafslutning
Datoer for studieregistrering
Først indsendt
Først indsendt
Først indsendt, der opfyldte QC-kriterier
Først indsendt, der opfyldte QC-kriterier
Først opslået (Faktiske)
Først opslået
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
Sidste opdatering sendt
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidst verificeret
Sidst verificeret
Mere information
Begreber relateret til denne undersøgelse
Yderligere relevante MeSH-vilkår
Andre undersøgelses-id-numre
Andre undersøgelses-id-numre
- 69HCL17_0182
Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter
Studerer et amerikansk FDA-reguleret lægemiddelprodukt
Studerer et amerikansk FDA-reguleret enhedsprodukt
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