Yu Cheng1,2, Chen-Yu Wang1, Zi-Ran Li3, Yan Pan1, Mao-Bai Liu4, Zheng Jiao5. 1. Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241 West Huaihai Road, Shanghai, 200040, China. 2. Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Road, Gulou, Fuzhou, 350001, China. 3. College of Pharmacy, Fudan University, Shanghai, China. 4. Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Road, Gulou, Fuzhou, 350001, China. xhlmbtg@163.com. 5. Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241 West Huaihai Road, Shanghai, 200040, China. jiaozhen@online.sh.cn.
Abstract
BACKGROUND AND OBJECTIVE: External evaluation is an important issue in the population pharmacokinetic analysis of antibiotics. The purpose of this review was to summarize the current approaches and status of external evaluations and discuss the implications of external evaluation results for the future individualization of dosing regimens. METHODS: We systematically searched the PubMed and EMBASE databases for external evaluation studies of population analysis and extracted the relevant information from these articles. A total of 32 studies were included in this review. RESULTS: Vancomycin was investigated in 17 (53.1%) articles and was the most studied drug. Other studied drugs included gentamicin, tobramycin, amikacin, amoxicillin, ceftaroline, meropenem, fluconazole, voriconazole, and rifampicin. Nine (28.1%) studies were prospective, and the sample size varied widely between studies. Thirteen (40.6%) studies evaluated the population pharmacokinetic models by systematically searching for previous studies. Seven (21.9%) studies were multicenter studies, and 27 (84.4%) adopted the sparse sampling strategy. Almost all external evaluation studies of antibiotics (93.8%) used metrics for prediction-based diagnostics, while relatively fewer studies were based on simulations (46.9%) and Bayesian forecasting (25.0%). CONCLUSION: The results of external evaluations in previous studies revealed the poor extrapolation performance of existing models of prediction- and simulation-based diagnostics, whereas the posterior Bayesian method could improve predictive performance. There is an urgent need for the development of standards and guidelines for external evaluation studies.
BACKGROUND AND OBJECTIVE: External evaluation is an important issue in the population pharmacokinetic analysis of antibiotics. The purpose of this review was to summarize the current approaches and status of external evaluations and discuss the implications of external evaluation results for the future individualization of dosing regimens. METHODS: We systematically searched the PubMed and EMBASE databases for external evaluation studies of population analysis and extracted the relevant information from these articles. A total of 32 studies were included in this review. RESULTS:Vancomycin was investigated in 17 (53.1%) articles and was the most studied drug. Other studied drugs included gentamicin, tobramycin, amikacin, amoxicillin, ceftaroline, meropenem, fluconazole, voriconazole, and rifampicin. Nine (28.1%) studies were prospective, and the sample size varied widely between studies. Thirteen (40.6%) studies evaluated the population pharmacokinetic models by systematically searching for previous studies. Seven (21.9%) studies were multicenter studies, and 27 (84.4%) adopted the sparse sampling strategy. Almost all external evaluation studies of antibiotics (93.8%) used metrics for prediction-based diagnostics, while relatively fewer studies were based on simulations (46.9%) and Bayesian forecasting (25.0%). CONCLUSION: The results of external evaluations in previous studies revealed the poor extrapolation performance of existing models of prediction- and simulation-based diagnostics, whereas the posterior Bayesian method could improve predictive performance. There is an urgent need for the development of standards and guidelines for external evaluation studies.
Authors: H Sun; E O Fadiran; C D Jones; L Lesko; S M Huang; K Higgins; C Hu; S Machado; S Maldonado; R Williams; M Hossain; E I Ette Journal: Clin Pharmacokinet Date: 1999-07 Impact factor: 6.447
Authors: Sebastian G Wicha; Martin G Kees; Alexander Solms; Iris K Minichmayr; Alexander Kratzer; Charlotte Kloft Journal: Int J Antimicrob Agents Date: 2015-01-10 Impact factor: 5.283
Authors: Michael Neely; Michael Philippe; Teresa Rushing; Xiaowei Fu; Michael van Guilder; David Bayard; Alan Schumitzky; Nathalie Bleyzac; Sylvain Goutelle Journal: Ther Drug Monit Date: 2016-06 Impact factor: 3.681
Authors: A S Darwich; K Ogungbenro; A A Vinks; J R Powell; J-L Reny; N Marsousi; Y Daali; D Fairman; J Cook; L J Lesko; J S McCune; Caj Knibbe; S N de Wildt; J S Leeder; M Neely; A F Zuppa; P Vicini; L Aarons; T N Johnson; J Boiani; A Rostami-Hodjegan Journal: Clin Pharmacol Ther Date: 2017-04-04 Impact factor: 6.875
Authors: Jason A Roberts; Mohd H Abdul-Aziz; Jeffrey Lipman; Johan W Mouton; Alexander A Vinks; Timothy W Felton; William W Hope; Andras Farkas; Michael N Neely; Jerome J Schentag; George Drusano; Otto R Frey; Ursula Theuretzbacher; Joseph L Kuti Journal: Lancet Infect Dis Date: 2014-04-24 Impact factor: 25.071
Authors: Ron J Keizer; Rob Ter Heine; Adam Frymoyer; Lawrence J Lesko; Ranvir Mangat; Srijib Goswami Journal: CPT Pharmacometrics Syst Pharmacol Date: 2018-10-16
Authors: S Baklouti; S Marolleau; P Chavanet; E Bonnet; D Concordet; P Gandia Journal: Antimicrob Agents Chemother Date: 2021-10-18 Impact factor: 5.938
Authors: Eleni Karatza; Samit Ganguly; Chi D Hornik; William J Muller; Amira Al-Uzri; Laura James; Stephen J Balevic; Daniel Gonzalez Journal: Front Pharmacol Date: 2022-03-17 Impact factor: 5.810