St Andrews Research Repository

St Andrews University Home
View Item 
  •   St Andrews Research Repository
  • Mathematics & Statistics (School of)
  • Statistics
  • Statistics Masters Theses
  • View Item
  •   St Andrews Research Repository
  • Mathematics & Statistics (School of)
  • Statistics
  • Statistics Masters Theses
  • View Item
  •   St Andrews Research Repository
  • Mathematics & Statistics (School of)
  • Statistics
  • Statistics Masters Theses
  • View Item
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.

Nonlinear mixed effect models for modeling initial viral decay rates in an HIV study

Thumbnail
View/Open
SujinKangMscThesis.pdf (1.715Mb)
Date
27/11/2008
Author
Kang, Sujin
Supervisor
Donovan, Carl
Keywords
HIV
Initial viral decay rates
Long-term response
Nonlinear mixed effect models
Single and biphasic viral dynamic models
Actual treatment effect
Number of multi-PI mutations
Baseline HIV-1 RNA levels
Metadata
Show full item record
Abstract
The Nonlinear Mixed Effect Viral Dynamic Model can easily handle unbalanced repeated and continuous measures data for individuals and is also popular in many other research areas such as biology and pharmacokinetics. Wu 𝘦𝘵 𝘢𝘭. (2004) described a Nonlinear Mixed Effects Biphasic Model to estimate short-term population and individual viral decay rates in their study. Perelson 𝘦𝘵 𝘢𝘭. (1999) and Ding 𝘦𝘵 𝘢𝘭. (1999) reported that initial viral decay estimated for viral decay models would be good markers of the potency of antiretroviral regimens. The aim of this study was to model viral decay rates, and check the validity of the model for the set of data provided and investigate whether the relationships found with baseline covariates and long-term response are consistent with Wu 𝘦𝘵 𝘢𝘭.’s (2004) findings. The Nonlinear Mixed Effect Single and Biphasic Viral Dynamic Models were fitted, and their respective initial viral decay rates were derived. In this study, analyses and reports are focused on the first-phase viral decay rates of the models. The study found that the actual treatment groups were more potent than the control group. It was found that actual treatment effect and the number of multi-PI mutations at baseline had impacts on the initial viral decay rates for both models. Besides, baseline HIV-1 RNA levels had an impact on the initial viral decay rates for the biphasic model. There were no significant differences in the initial viral decay rates for different ages, ethnicities, and gender groups. The study also shows that the initial viral decay rates were somewhat negatively correlated with the baseline HIV-1 RNA levels. A strong correlation between the initial viral decay rates and week 1 virus load reduction from baseline was observed. It was also observed that individuals with the higher initial viral decay rates were more likely to have suppressed virus load at week 24. Also, individuals with higher week 1 virus load reduction, i.e. early viral dynamics, were more likely to have suppressed virus load at week 24. These findings suggest that the antiviral potency or the initial viral decay rates are predictive of long-term viral load response.
Type
Thesis, MSc Master of Science
Collections
  • Statistics Masters Theses
URI
http://hdl.handle.net/10023/20947

Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

Advanced Search

Browse

All of RepositoryCommunities & CollectionsBy Issue DateNamesTitlesSubjectsClassificationTypeFunderThis CollectionBy Issue DateNamesTitlesSubjectsClassificationTypeFunder

My Account

Login

Open Access

To find out how you can benefit from open access to research, see our library web pages and Open Access blog. For open access help contact: openaccess@st-andrews.ac.uk.

Accessibility

Read our Accessibility statement.

How to submit research papers

The full text of research papers can be submitted to the repository via Pure, the University's research information system. For help see our guide: How to deposit in Pure.

Electronic thesis deposit

Help with deposit.

Repository help

For repository help contact: Digital-Repository@st-andrews.ac.uk.

Give Feedback

Cookie policy

This site may use cookies. Please see Terms and Conditions.

Usage statistics

COUNTER-compliant statistics on downloads from the repository are available from the IRUS-UK Service. Contact us for information.

© University of St Andrews Library

University of St Andrews is a charity registered in Scotland, No SC013532.

  • Facebook
  • Twitter