Estimating a treatment effect with repeated measurements accounting for varying effectiveness duration

Y. Q. Chen; J. Yang; S. Cheng; J. B. Jackson

doi:10.1093/biomet/asm019

Estimating a treatment effect with repeated measurements accounting for varying effectiveness duration

Y. Q. Chen
, J. Yang
, S. Cheng
, J. B. Jackson

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

To assess treatment efficacy in clinical trials, certain clinical outcomes are repeatedly measured over time for the same subject. The difference in their means may characterize a treatment effect. Since treatment effectiveness lag and saturation times may exist, erosion of treatment effect often occurs during the observation period. Instead of using models based on ad hoc parametric or purely nonparametric time-varying coefficients, we model the treatment effectiveness durations, which are the time intervals between the lag and saturation times. Then we use some mean response models to include such treatment effectiveness durations. Our methodology is demonstrated by simulations and analysis of a landmark HIV/AIDS clinical trial of short-course nevirapine against mother-to-child HIV vertical transmission during labour and delivery.

Original language	English (US)
Pages (from-to)	387-402
Number of pages	16
Journal	Biometrika
Volume	94
Issue number	2
DOIs	https://doi.org/10.1093/biomet/asm019
State	Published - Jun 2007
Externally published	Yes

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT We sincerely thank the editor, an associate editor, two referees and Ms. Emily Hemminger for their careful reading and invaluable comments. This research was supported in part by a federal grant from the U.S. National Institute of Allergy and Infectious Disease.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 5 Gender Equality

Keywords

Effect erosion
HIV/AIDS clinical trial
Longitudinal study
Mean response model
Time-varying coefficient

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10.1093/biomet/asm019

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title = "Estimating a treatment effect with repeated measurements accounting for varying effectiveness duration",

abstract = "To assess treatment efficacy in clinical trials, certain clinical outcomes are repeatedly measured over time for the same subject. The difference in their means may characterize a treatment effect. Since treatment effectiveness lag and saturation times may exist, erosion of treatment effect often occurs during the observation period. Instead of using models based on ad hoc parametric or purely nonparametric time-varying coefficients, we model the treatment effectiveness durations, which are the time intervals between the lag and saturation times. Then we use some mean response models to include such treatment effectiveness durations. Our methodology is demonstrated by simulations and analysis of a landmark HIV/AIDS clinical trial of short-course nevirapine against mother-to-child HIV vertical transmission during labour and delivery.",

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note = "Funding Information: ACKNOWLEDGEMENT We sincerely thank the editor, an associate editor, two referees and Ms. Emily Hemminger for their careful reading and invaluable comments. This research was supported in part by a federal grant from the U.S. National Institute of Allergy and Infectious Disease.",

year = "2007",

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volume = "94",

pages = "387--402",

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T1 - Estimating a treatment effect with repeated measurements accounting for varying effectiveness duration

AU - Chen, Y. Q.

AU - Yang, J.

AU - Cheng, S.

AU - Jackson, J. B.

N1 - Funding Information: ACKNOWLEDGEMENT We sincerely thank the editor, an associate editor, two referees and Ms. Emily Hemminger for their careful reading and invaluable comments. This research was supported in part by a federal grant from the U.S. National Institute of Allergy and Infectious Disease.

PY - 2007/6

Y1 - 2007/6

N2 - To assess treatment efficacy in clinical trials, certain clinical outcomes are repeatedly measured over time for the same subject. The difference in their means may characterize a treatment effect. Since treatment effectiveness lag and saturation times may exist, erosion of treatment effect often occurs during the observation period. Instead of using models based on ad hoc parametric or purely nonparametric time-varying coefficients, we model the treatment effectiveness durations, which are the time intervals between the lag and saturation times. Then we use some mean response models to include such treatment effectiveness durations. Our methodology is demonstrated by simulations and analysis of a landmark HIV/AIDS clinical trial of short-course nevirapine against mother-to-child HIV vertical transmission during labour and delivery.

AB - To assess treatment efficacy in clinical trials, certain clinical outcomes are repeatedly measured over time for the same subject. The difference in their means may characterize a treatment effect. Since treatment effectiveness lag and saturation times may exist, erosion of treatment effect often occurs during the observation period. Instead of using models based on ad hoc parametric or purely nonparametric time-varying coefficients, we model the treatment effectiveness durations, which are the time intervals between the lag and saturation times. Then we use some mean response models to include such treatment effectiveness durations. Our methodology is demonstrated by simulations and analysis of a landmark HIV/AIDS clinical trial of short-course nevirapine against mother-to-child HIV vertical transmission during labour and delivery.

KW - Effect erosion

KW - HIV/AIDS clinical trial

KW - Longitudinal study

KW - Mean response model

KW - Time-varying coefficient

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U2 - 10.1093/biomet/asm019

DO - 10.1093/biomet/asm019

M3 - Article

AN - SCOPUS:34548414156

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Estimating a treatment effect with repeated measurements accounting for varying effectiveness duration

Abstract

Bibliographical note

UN SDGs

Keywords

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