Dataset Information

Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data.

ABSTRACT: Sample sizes for single-period clinical trials, including pharmacokinetic studies, are statistically determined by within-subject variability (WSV). However, it is difficult to determine WSV without replicate-designed clinical trial data, and statisticians typically estimate optimal sample sizes using total variability, not WSV. We have developed an efficient population-based method to predict WSV accurately with single-period clinical trial data and demonstrate method performance with eperisone. We simulated 1000 virtual pharmacokinetic clinical trial datasets based on single-period and dense sampling studies, with various study sizes and levels of WSV and interindividual variabilities (IIVs). The estimated residual variability (RV) resulting from population pharmacokinetic methods were compared with WSV values. In addition, 3 × 3 bioequivalence results of eperisone were used to evaluate method performance with a real clinical dataset. With WSV of 40% or less, regardless of IIV magnitude, RV was well approximated by WSV for sample sizes greater than 18 subjects. RV was underestimated at WSV of 50% or greater, even with datasets having low IIV and numerous subjects. Using the eperisone dataset, RV was 44% to 48%, close to the true value of 50%. In conclusion, the estimated RV accurately predicted WSV in single-period studies, validating this method for sample size estimation in clinical trials.

SUBMITTER: Kang WH

PROVIDER: S-EPMC7913178 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data.

Kang Won-Ho WH Lee Jae-Yeon JY Chae Jung-Woo JW Lee Kyeong-Ryoon KR Baek In-Hwan IH Kim Min-Soo MS Back Hyun-Moon HM Jung Sangkeun S Shaffer Craig C Savic Rada R Yun Hwi-Yeol HY

Pharmaceuticals (Basel, Switzerland) 20210203 2

Sample sizes for single-period clinical trials, including pharmacokinetic studies, are statistically determined by within-subject variability (WSV). However, it is difficult to determine WSV without replicate-designed clinical trial data, and statisticians typically estimate optimal sample sizes using total variability, not WSV. We have developed an efficient population-based method to predict WSV accurately with single-period clinical trial data and demonstrate method performance with eperisone ...[more]

PMID: 33546114

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Project description:BackgroundThe QuantiFERON®-TB Gold In-Tube test (QFT-GIT) is a viable alternative to the tuberculin skin test (TST) for detecting Mycobacterium tuberculosis infection. However, within-subject variability may limit test utility. To assess variability, we compared results from the same subjects when QFT-GIT enzyme-linked immunosorbent assays (ELISAs) were performed in different laboratories.MethodsSubjects were recruited at two sites and blood was tested in three labs. Two labs used the same type of automated ELISA workstation, 8-point calibration curves, and electronic data transfer. The third lab used a different automated ELISA workstation, 4-point calibration curves, and manual data entry. Variability was assessed by interpretation agreement and comparison of interferon-? (IFN-?) measurements. Data for subjects with discordant interpretations or discrepancies in TB Response >0.05 IU/mL were verified or corrected, and variability was reassessed using a reconciled dataset.ResultsNinety-seven subjects had results from three labs. Eleven (11.3%) had discordant interpretations and 72 (74.2%) had discrepancies >0.05 IU/mL using unreconciled results. After correction of manual data entry errors for 9 subjects, and exclusion of 6 subjects due to methodological errors, 7 (7.7%) subjects were discordant. Of these, 6 (85.7%) had all TB Responses within 0.25 IU/mL of the manufacturer's recommended cutoff. Non-uniform error of measurement was observed, with greater variation in higher IFN-? measurements. Within-subject standard deviation for TB Response was as high as 0.16 IU/mL, and limits of agreement ranged from -0.46 to 0.43 IU/mL for subjects with mean TB Response within 0.25 IU/mL of the cutoff.ConclusionGreater interlaboratory variability was associated with manual data entry and higher IFN-? measurements. Manual data entry should be avoided. Because variability in measuring TB Response may affect interpretation, especially near the cutoff, consideration should be given to developing a range of values near the cutoff to be interpreted as "borderline," rather than negative or positive.

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Dataset Information

Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data.

Publications

Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data.

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