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Estimating correlation by using a general linear mixed model: evaluation of the relationship between the concentration of HIV-1 RNA in blood and semen.

Publication ,  Journal Article
Chakraborty, H; Helms, RW; Sen, PK; Cohen, MS
Published in: Stat Med
May 15, 2003

Estimating the correlation coefficient between two outcome variables is one of the most important aspects of epidemiological and clinical research. A simple Pearson's correlation coefficient method is usually employed when there are complete independent data points for both outcome variables. However, researchers often deal with correlated observations in a longitudinal setting with missing values where a simple Pearson's correlation coefficient method cannot be used. General linear mixed models (GLMM) techniques were used to estimate correlation coefficients in a longitudinal data set with missing values. A random regression mixed model with unstructured covariance matrix was employed to estimate correlation coefficients between concentrations of HIV-1 RNA in blood and seminal plasma. The effects of CD4 count and antiretroviral therapy were also examined. We used data sets from three different centres (650 samples from 238 patients) where blood and seminal plasma HIV-1 RNA concentrations were collected from patients; 137 samples from 90 different patients without antiviral therapy and 513 samples from 148 patients receiving therapy were considered for analysis. We found no significant correlation between blood and semen HIV-1 RNA concentration in the absence of antiviral therapy. However, a moderate correlation between blood and semen HIV-1 RNA was observed among subjects with lower CD4 counts receiving therapy. Our findings confirm and extend the idea that the concentrations of HIV-1 in semen often differ from the HIV-1 concentration in blood. Antiretroviral therapy administered to subjects with low CD4 counts result in sufficient concomitant reduction of HIV-1 in blood and semen so as to improve the correlation between these compartments. These results have important implications for studies related to the sexual transmission of HIV, and development of HIV prevention strategies.

Duke Scholars

Published In

Stat Med

DOI

ISSN

0277-6715

Publication Date

May 15, 2003

Volume

22

Issue

9

Start / End Page

1457 / 1464

Location

England

Related Subject Headings

  • Statistics & Probability
  • Semen
  • RNA, Viral
  • Male
  • Longitudinal Studies
  • Linear Models
  • Humans
  • HIV-1
  • HIV Infections
  • Disease Transmission, Infectious
 

Citation

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Chakraborty, H., Helms, R. W., Sen, P. K., & Cohen, M. S. (2003). Estimating correlation by using a general linear mixed model: evaluation of the relationship between the concentration of HIV-1 RNA in blood and semen. Stat Med, 22(9), 1457–1464. https://doi.org/10.1002/sim.1505
Chakraborty, Hrishikesh, Ronald W. Helms, Pranab K. Sen, and Myron S. Cohen. “Estimating correlation by using a general linear mixed model: evaluation of the relationship between the concentration of HIV-1 RNA in blood and semen.Stat Med 22, no. 9 (May 15, 2003): 1457–64. https://doi.org/10.1002/sim.1505.
Chakraborty, Hrishikesh, et al. “Estimating correlation by using a general linear mixed model: evaluation of the relationship between the concentration of HIV-1 RNA in blood and semen.Stat Med, vol. 22, no. 9, May 2003, pp. 1457–64. Pubmed, doi:10.1002/sim.1505.
Journal cover image

Published In

Stat Med

DOI

ISSN

0277-6715

Publication Date

May 15, 2003

Volume

22

Issue

9

Start / End Page

1457 / 1464

Location

England

Related Subject Headings

  • Statistics & Probability
  • Semen
  • RNA, Viral
  • Male
  • Longitudinal Studies
  • Linear Models
  • Humans
  • HIV-1
  • HIV Infections
  • Disease Transmission, Infectious