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Bone InfectionNCT03134521

Population Pharmacokinetic Analysis of Daptomycin in Patients With Osteoarticular Infections

An observational study of Bone Infection and Joint Infection, run by Hospices Civils de Lyon.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Official record
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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. Read more about this study

Who is it for?
Ages 18 years and older
Conditions the study is for
Bone Infection, Joint Infection
How many people
189 participants
Where
No sites listed yet
Study dates
1 Dec 2016to 30 Jun 2017
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: Patients having bone or joint infection, with or without implant, having an antibiotherapy with daptomycin

Who may be able to join

  • 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

Who cannot join

  • None

About this study

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.

Read more

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.

Keywords
bone and joint infection, daptomycin, population pharmacokinetics, Glycoprotein-P (PgP)

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Peak plasma concentration (Cmax)

    Measured: Month 6

Secondary outcomes (10)

  1. Area under the concentration-time curve

    Measured: up to 6 months

  2. typical daptomycin clearance and volume of distribution in the population

    Measured: Month 6

  3. Mean daptomycine plasma clearance

    (unit, liters per hour)

    Measured: Month 6

  4. Mean daptomycine volume of distribution

    (unit, liters)

    Measured: Month 6

  5. Inter-individual coefficient of variation of daptomycin clearance

    (unit, %)

    Measured: Month 6

  6. Inter-individual coefficient of variation of daptomycin volume of distribution

    (unit, %)

    Measured: Month 6

  7. Intra-individual coefficient of variation of daptomycin clearance

    (unit, %)

    Measured: Month 6

  8. Intra-individual coefficient of variation of daptomycin volume of distribution

    (unit, %)

    Measured: Month 6

  9. 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.

    Measured: Month 6

  10. 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.

    Measured: Month 6

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted1 May 2017
  2. Study start1 Dec 2016
  3. Primary completion30 Jun 2017 (estimated)
  4. Study completion30 Jun 2017 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Retrospective
Enrolment
189 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT03134521
Sponsor's protocol ID
69HCL17_0182
Status last verified
May 2017
First submitted
29 Mar 2017
Last updated
11 May 2017
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No

Publications

  • Rivals F, Goutelle S, Codde C, Garreau R, Ponthier L, Marquet P, Ferry T, Labriffe M, Destere A, Woillard JB. A Machine Learning Algorithm to Predict the Starting Dose of Daptomycin. Clin Pharmacokinet. 2024 Aug;63(8):1137-1146. doi: 10.1007/s40262-024-01405-z. Epub 2024 Jul 31.

    PubMed 39085523

  • Tuloup V, Millet A, Taricco A, Parant F, Ferry T, Goutelle S. Evaluation of Limited Sampling Strategies for Bayesian Estimation of Daptomycin Area Under the Concentration-Time Curve: A Short Communication. Ther Drug Monit. 2023 Aug 1;45(4):562-565. doi: 10.1097/FTD.0000000000001070. Epub 2023 Jan 2.

    PubMed 36728573

Questions about this trial

What is this clinical trial studying?

An observational study of Bone Infection and Joint Infection, run by Hospices Civils de Lyon.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: status not confirmed, as of the sponsor's last update on 11 May 2017. Status can change between updates, so confirm with the study contact before making plans.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

Results are not available in the source record.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Peak plasma concentration (Cmax) (time frame: Month 6). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT03134521, which also lists 2 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 May 2017.

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