Sensitivity of Estimated Tacrolimus Population Pharmacokinetic Profile to Assumed Dose Timing and Absorption in Real World Data and Simulated Data

Author(s):  
Michael L. Williams ◽  
Hannah L. Weeks ◽  
Cole Beck ◽  
Kelly A. Birdwell ◽  
Sara L. Van Driest ◽  
...  
2020 ◽  
pp. 001316442092656
Author(s):  
Yutian T. Thompson ◽  
Hairong Song ◽  
Dexin Shi ◽  
Zhengkui Liu

Conventional approaches for selecting a reference indicator (RI) could lead to misleading results in testing for measurement invariance (MI). Several newer quantitative methods have been available for more rigorous RI selection. However, it is still unknown how well these methods perform in terms of correctly identifying a truly invariant item to be an RI. Thus, Study 1 was designed to address this issue in various conditions using simulated data. As a follow-up, Study 2 further investigated the advantages/disadvantages of using RI-based approaches for MI testing in comparison with non-RI-based approaches. Altogether, the two studies provided a solid examination on how RI matters in MI tests. In addition, a large sample of real-world data was used to empirically compare the uses of the RI selection methods as well as the RI-based and non-RI-based approaches for MI testing. In the end, we offered a discussion on all these methods, followed by suggestions and recommendations for applied researchers.


2021 ◽  
Author(s):  
Nathan T James ◽  
Sara L Van Driest ◽  
Prince J Kannankeril ◽  
Leena Choi

Dexmedetomidine is commonly used as part of intraoperative anesthetic management and for sedation and pain control after surgery in children. Dexmedetomidine infusion dose is typically given on a fixed weight basis with titration to achieve sedation goals while avoiding potential toxicities. Pharmacokinetic (PK) studies are useful for accurate prediction of the individual dose required to achieve sedation and analgesia goals without toxicity, but lack of PK data is a challenge in precision dosing for pediatric populations. In this study, population PK models were developed using a nonlinear mixed-effects modeling approach and used to explore the relationship between PK profile and clinical, demographic, and genotype covariates. A simulation study was used to demonstrate the impact of important covariates on concentration using a fixed weight dosing scheme. Our final study population included data from 354 patients age 0 to 22 years (median age 16 months). In the final two-compartment model with fixed allometric weight scaling we found significant effects of both age and UGT2B10 genotype. The population PK parameter estimates (95% confidence interval) for a standard 70 kg weight were clearance 22.3 (18.3 - 27.3) L/hr, central compartment volume of distribution 133 (112 - 157) L, intercompartmental clearance 24.1 (19.4 - 29.9) L/hr, peripheral compartment volume of distribution 5230 (3310 - 8260) L. Our study provides support for the feasibility of using real-world data obtained from EHRs and remnant samples to perform population PK analysis for groups of patients where traditional PK studies are challenging to perform. Inclusion of UGT2B10 genotype in the model significantly improved the model fit, but the effects were not large enough to impact clinical dosing.


2019 ◽  
Author(s):  
Paul G Curran ◽  
Alexander James Denison

It is an accepted fact in survey research that not all participants will respond to items with the thoughtful introspection required to produce a valid response. When participants respond without sufficient effort their responses are considered to be careless, and these responses represent error. Many methods exist for the detection of these individuals (Huang, Curran, Keeney, Poposki, & Deshon, 2012; Johnson, 2005; Meade & Craig, 2012), and several techniques exist for testing their effectiveness. These techniques often involve generating careless responses through some process, then attempting to detect those known cases in otherwise normal data. One method to produce these data is through the simulation of data with varying degrees of randomness. Despite the common use of this technique, we know little about how it actually maps onto real world data. The purpose of this paper is to compare simulated data with real world data on commonly used careless response metrics. Results suggest that care should be applied when simulating data, and that decisions researchers make when generating this data can have large effects on the apparent effectiveness of these metrics. Despite these potential limitations, it appears that with proper use and continued research simulation techniques can still be quite valuable.


2016 ◽  
Vol 22 ◽  
pp. 219
Author(s):  
Roberto Salvatori ◽  
Olga Gambetti ◽  
Whitney Woodmansee ◽  
David Cox ◽  
Beloo Mirakhur ◽  
...  

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