{"title":"External Evaluation of Longitudinal Population Pharmacokinetic Models of Vancomycin in Patients With Osteoarticular Infections.","authors":"Van Dong Nguyen, Alice Côté, Amélie Marsot","doi":"10.1097/FTD.0000000000001303","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Osteoarticular infections pose a challenge for therapeutic drug monitoring of vancomycin because they often require prolonged treatment. Given the extensive renal elimination of vancomycin, its pharmacokinetic properties are difficult to predict in the later stages of treatment because the risk of nephrotoxicity increases with the duration of treatment. In this study, published longitudinal population pharmacokinetic (popPK) models were externally evaluated in a cohort of patients with osteoarticular infections.</p><p><strong>Methods: </strong>A literature search was performed in PubMed/EMBASE and published reviews. The predictive performance of the selected models was assessed through prediction- and simulation-based diagnostics using NONMEM software. Data were collected during both the retrospective and prospective phases, during which prospectively recruited patients provided additional vancomycin concentrations.</p><p><strong>Results: </strong>The external validation dataset comprised 525 vancomycin concentrations obtained from 73 patients treated for osteoarticular infections at Montréal General Hospital. Two published popPK models that provided different approaches for integrating a longitudinal structure were identified. Both failed to meet the clinically acceptable threshold of imprecision in population predictions. The weighted median absolute prediction error ranged from 34.9% to 48.3% before re-estimation of model parameters and from 33.5% to 35.2% after re-estimation. The re-estimated models tended to underpredict vancomycin concentrations in the later stages of treatment.</p><p><strong>Conclusions: </strong>The 2 evaluated models showed poor predictive performance in our local study population. Further studies should explore new strategies to incorporate a longitudinal component and consider other relevant clinical covariates to develop improved longitudinal popPK models for vancomycin.</p>","PeriodicalId":23052,"journal":{"name":"Therapeutic Drug Monitoring","volume":" ","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic Drug Monitoring","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/FTD.0000000000001303","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Osteoarticular infections pose a challenge for therapeutic drug monitoring of vancomycin because they often require prolonged treatment. Given the extensive renal elimination of vancomycin, its pharmacokinetic properties are difficult to predict in the later stages of treatment because the risk of nephrotoxicity increases with the duration of treatment. In this study, published longitudinal population pharmacokinetic (popPK) models were externally evaluated in a cohort of patients with osteoarticular infections.
Methods: A literature search was performed in PubMed/EMBASE and published reviews. The predictive performance of the selected models was assessed through prediction- and simulation-based diagnostics using NONMEM software. Data were collected during both the retrospective and prospective phases, during which prospectively recruited patients provided additional vancomycin concentrations.
Results: The external validation dataset comprised 525 vancomycin concentrations obtained from 73 patients treated for osteoarticular infections at Montréal General Hospital. Two published popPK models that provided different approaches for integrating a longitudinal structure were identified. Both failed to meet the clinically acceptable threshold of imprecision in population predictions. The weighted median absolute prediction error ranged from 34.9% to 48.3% before re-estimation of model parameters and from 33.5% to 35.2% after re-estimation. The re-estimated models tended to underpredict vancomycin concentrations in the later stages of treatment.
Conclusions: The 2 evaluated models showed poor predictive performance in our local study population. Further studies should explore new strategies to incorporate a longitudinal component and consider other relevant clinical covariates to develop improved longitudinal popPK models for vancomycin.
期刊介绍:
Therapeutic Drug Monitoring is a peer-reviewed, multidisciplinary journal directed to an audience of pharmacologists, clinical chemists, laboratorians, pharmacists, drug researchers and toxicologists. It fosters the exchange of knowledge among the various disciplines–clinical pharmacology, pathology, toxicology, analytical chemistry–that share a common interest in Therapeutic Drug Monitoring. The journal presents studies detailing the various factors that affect the rate and extent drugs are absorbed, metabolized, and excreted. Regular features include review articles on specific classes of drugs, original articles, case reports, technical notes, and continuing education articles.