Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models
Longitudinal‐ordered categorical data, common in clinical trials, can be effectively analyzed with nonlinear mixed effect models. In this article, we systematically evaluated the performance of three different models in longitudinal muscle spasm adverse event (AE) data obtained from a clinical trial...
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2020-02-01
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Online Access: | https://doi.org/10.1002/psp4.12487 |
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doaj-f3c5803c58e24353bbe4c503c5431c4b2020-11-25T03:50:04ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062020-02-01929610510.1002/psp4.12487Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric ModelsTong Lu0Yujie Yang1Jin Y. Jin2Matts Kågedal3Department of Clinical Pharmacology Genentech, Inc South San Francisco California USADepartment of Pharmaceutical Sciences School of Pharmacy and Pharmaceutical Sciences University at Buffalo, The State University of New York Buffalo New York USADepartment of Clinical Pharmacology Genentech, Inc South San Francisco California USADepartment of Clinical Pharmacology Genentech, Inc South San Francisco California USALongitudinal‐ordered categorical data, common in clinical trials, can be effectively analyzed with nonlinear mixed effect models. In this article, we systematically evaluated the performance of three different models in longitudinal muscle spasm adverse event (AE) data obtained from a clinical trial for vismodegib: a proportional odds (PO) model, a discrete‐time Markov model, and a continuous‐time Markov model. All models developed based on weekly spaced data can reasonably capture the proportion of AE grade over time; however, the PO model overpredicted the transition frequency between grades and the cumulative probability of AEs. The influence of data frequency (daily, weekly, or unevenly spaced) was also investigated. The PO model performance reduced with increased data frequency, and the discrete‐time Markov model failed to describe unevenly spaced data, but the continuous‐time Markov model performed consistently well. Clinical trial simulations were conducted to illustrate the muscle spasm resolution time profile during the 8‐week dose interruption period after 12 weeks of continuous treatment.https://doi.org/10.1002/psp4.12487 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tong Lu Yujie Yang Jin Y. Jin Matts Kågedal |
spellingShingle |
Tong Lu Yujie Yang Jin Y. Jin Matts Kågedal Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models CPT: Pharmacometrics & Systems Pharmacology |
author_facet |
Tong Lu Yujie Yang Jin Y. Jin Matts Kågedal |
author_sort |
Tong Lu |
title |
Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models |
title_short |
Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models |
title_full |
Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models |
title_fullStr |
Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models |
title_full_unstemmed |
Analysis of Longitudinal‐Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models |
title_sort |
analysis of longitudinal‐ordered categorical data for muscle spasm adverse event of vismodegib: comparison between different pharmacometric models |
publisher |
Wiley |
series |
CPT: Pharmacometrics & Systems Pharmacology |
issn |
2163-8306 |
publishDate |
2020-02-01 |
description |
Longitudinal‐ordered categorical data, common in clinical trials, can be effectively analyzed with nonlinear mixed effect models. In this article, we systematically evaluated the performance of three different models in longitudinal muscle spasm adverse event (AE) data obtained from a clinical trial for vismodegib: a proportional odds (PO) model, a discrete‐time Markov model, and a continuous‐time Markov model. All models developed based on weekly spaced data can reasonably capture the proportion of AE grade over time; however, the PO model overpredicted the transition frequency between grades and the cumulative probability of AEs. The influence of data frequency (daily, weekly, or unevenly spaced) was also investigated. The PO model performance reduced with increased data frequency, and the discrete‐time Markov model failed to describe unevenly spaced data, but the continuous‐time Markov model performed consistently well. Clinical trial simulations were conducted to illustrate the muscle spasm resolution time profile during the 8‐week dose interruption period after 12 weeks of continuous treatment. |
url |
https://doi.org/10.1002/psp4.12487 |
work_keys_str_mv |
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