Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2009 May 1;199(9):1292-300.
doi: 10.1086/597617.

Comparison of CD4 cell count, viral load, and other markers for the prediction of mortality among HIV-1-infected Kenyan pregnant women

Elizabeth R Brown  1 , Phelgona Otieno, Dorothy A Mbori-Ngacha, Carey Farquhar, Elizabeth M Obimbo, Ruth Nduati, Julie Overbaugh, Grace C John-Stewart
Affiliations

Comparison of CD4 cell count, viral load, and other markers for the prediction of mortality among HIV-1-infected Kenyan pregnant women

Elizabeth R Brown et al. J Infect Dis. .

Abstract

Background: There are limited data regarding the relative merits of biomarkers as predictors of mortality or time to initiation of antiretroviral therapy (ART).

Methods: We evaluated the usefulness of the CD4 cell count, CD4 cell percentage (CD4%), human immunodeficiency virus type 1 (HIV-1) load, total lymphocyte count (TLC), body mass index (BMI), and hemoglobin measured at 32 weeks' gestation as predictors of mortality in a cohort of HIV-1-infected women in Nairobi, Kenya. Sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic (ROC) curve (AUC) were determined for each biomarker separately, as well as for the CD4 cell count and the HIV-1 load combined.

Results: Among 489 women with 10,150 person-months of follow-up, mortality rates at 1 and 2 years postpartum were 2.1% (95% confidence interval [CI], 0.7%-3.4%) and 5.5% (95% CI, 3.0%-8.0%), respectively. CD4 cell count and CD4% had the highest AUC value (>0.9). BMI, TLC, and hemoglobin were each associated with but poorly predictive of mortality (PPV, <7%). The HIV-1 load did not predict mortality beyond the CD4 cell count.

Conclusions: The CD4 cell count and CD4% measured during pregnancy were both useful predictors of mortality among pregnant women. TLC, BMI, and hemoglobin had a limited predictive value, and the HIV-1 load did not predict mortality any better than did the CD4 cell count alone.

PubMed Disclaimer

Conflict of interest statement

Potential conflicts of interest: none reported.

Figures

Figure 1
Figure 1
Kaplan-Meier estimates of the cumulative proportion of women alive (black) and the cumulative proportion of women alive and antiretroviral therapy (ART) free (gray). The vertical dashes denote the times at which the women were censored.
Figure 2
Figure 2
Kaplan-Meier estimates of the cumulative mortality rate, as stratified by marker values. The vertical dashes denote the time points at which ≥1 woman’s event time was censored. BMI, body mass index; CD4, CD4 cell count; CD4%, CD4 cell percentage; Hb, hemoglobin; TLC, total lymphocyte count; VL, HIV-1 load.
Figure 3
Figure 3
Kaplan-Meier estimates of the cumulative combined mortality rate and rate of initiation of antiretroviral therapy (ART), as stratified by marker values. The vertical dashes denote time points at which ≥1 woman’s event time was censored. BMI, body mass index; CD4, CD4 cell count; CD4%, CD4 cell percentage; Hb, hemoglobin; TLC, total lymphocyte count; VL, HIV-1 load.
Figure 4
Figure 4
Receiver operating characteristic curves for several potential predictors of death within the first (left) and second (right) year postpartum, with the corresponding area under the ROC curve (AUC) values. BMI, body mass index; CD4, CD4 cell count; CD4%, CD4 cell percentage; Hb, hemoglobin; TLC, total lymphocyte count; VL, HIV-1 load.
See this image and copyright information in PMC

Comment in

References

    1. World Health Organization/Joint United Nations Programme on HIV/AIDS/United Nations Children’s Fund. Towards universal access: scaling up priority HIV/AIDS interventions in the health sector: progress report. 2007. Apr [Accessed 10 October 2007]. Available at: http://www.who.int/hiv/mediacentre/universal_access_progress_report_en.pdf.
    1. Ekouevi DK, Inwoley A, Tonwe-Gold B, et al. Variation of CD4 count and percentage during pregnancy and after delivery: implications for HAART initiation in resource-limited settings. AIDS Res Hum Retroviruses. 2007;23:1469–1473. - PubMed
    1. Mulcahy F, Wallace E, Woods S, et al. Counts in pregnancy do not accurately reflect the need for long-term HAART [abstract 704b]. Program and abstracts of the 13th Conference on Retroviruses and Opportunistic Infections (Denver); 2006. Available at: http://www.retroconference.org/2006/Abstracts/27587.htm.
    1. Miotti PG, Liomba G, Dallabetta GA, Hoover DR, Chiphangwi JD, Saah AJ. T lymphocyte subsets during and after pregnancy: analysis in human immunodeficiency virus type 1–infected and –uninfected Malawian mothers. J Infect Dis. 1992;165:1116–1119. - PubMed
    1. Temmerman M, Nagelkerke N, Bwayo J, Chomba EN, Ndinya-Achola J, Piot P. HIV-1 and immunological changes during pregnancy: a comparison between HIV-1-seropositive and HIV-1-seronegative women in Nairobi, Kenya. AIDS. 1995;9:1057–1060. - PubMed

Publication types

MeSH terms