Evidence map›Paper›PMID 27716818›Full record

ArticlePloS one2016

Impact of Age and Sex on CD4+ Cell Count Trajectories following Treatment Initiation: An Analysis of the Tanzanian HIV Treatment Database.

Arianna R Means, Kathryn A Risher, Eva L Ujeneza, Innocent Maposa, Joseph Nondi, Steven E Bellan

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
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  4. Evolution of CD4 T-Cell Count With Age in a Cohort of Young People Growing Up With Perinatally Acquired Human Immunodeficiency Virus.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 6 institutions in 4 countries.

Arianna R MeansDepartment of Global Health, University of Washington, Seattle, Washington, United States of America.
Kathryn A RisherDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Eva L UjenezaThe South African Department of Science and Technology, National Research Foundation Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), University of Stellenbosch, Stellenbosch, South Africa.
Innocent MaposaDepartment of Mathematics and Statistics, School of Health and Applied Sciences, Polytechnic of Namibia, Windhoek, Namibia.
Joseph NondiNational AIDS Control Program, Ministry of Health and Social Welfare (MOHSW), Dar es Salaam, The United Republic of Tanzania.
Steven E BellanDepartment of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States of America.
Johns Hopkins University · USMinistry of Health and Social Welfare · TZNamibia University of Science and Technology · NAStellenbosch University · ZAUniversity of Georgia · USUniversity of Washington · US

Funding

Understanding Transmission with Integrated Genetic and Epidemiologic InferenceU54GM111274 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BEDFORD, TREVOR BC · 2014 to 2018
$12.5M
Impacts of Individual and Social Behavior on Influenza Dynamics and ControlU01GM087719 · NIGMS · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2009 to 2018
$6.3M
Johns Hopkins HIV Epidemiology and Prevention Sciences Training ProgramT32AI102623 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Shruti H Mehta · 2013 to 2026
$5.3M
International Clinics on Infectious Disease Dynamics and Data (ICI3D Program)R25GM102149 · NIGMS · UNIVERSITY OF FLORIDA · PI PULLIAM, JULIET RC, WELTE, ALEX · 2012 to 2015
$696k
NIAID NIH HHS T32 AI102623NIGMS NIH HHS R25 GM102149NIGMS NIH HHS U01 GM087719
6 · The paper itself

Abstract

objectiveNew guidelines recommend that all HIV-infected individuals initiate antiretroviral treatment (ART) immediately following diagnosis. This study describes how immune reconstitution varies by gender and age to help identify poorly reconstituting subgroups and inform targeted testing initiatives.

designLongitudinal data from the outpatient monitoring system of the National AIDS Control Program in Tanzania.

methodsAn asymptotic nonlinear mixed effects model was fit to post-treatment CD4+ cell count trajectories, allowing for fixed effects of age and sex, and an age by sex interaction.

resultsAcross 220,544 clinic visits from 32,069 HIV-infected patients, age- and sex-specific average CD4+ cell count at ART initiation ranged from 83-136 cells/mm3, long term asymptotic CD4+ cell count ranged from 301-389 cells/mm3, and time to half of maximal CD4+ reconstitution ranged from 3.57-5.68 months. CD4+ cell count at ART initiation and asymptotic CD4+ cell count were 1.28 (95% CI: 1.18-1.40) and 1.25 (95% CI: 1.20-1.31) times higher, respectively, for females compared to males in the youngest age group (19-29 years). Older patients started treatment at higher CD4+ counts but experienced slower CD4+ recovery than younger adults. Treatment initiation at greater CD4+ cell counts was correlated with greater asymptotic CD4+ cell counts within all sex and age groups.

conclusionOlder adults should initiate care early in disease progression because total immune reconstitution potential and rate of reconstitution appears to decrease with age. Targeted HIV testing and care linkage remains crucial for patient populations who tend to initiate treatment at lower CD4+ cell counts, including males and younger adults.

Indexed as

AdultAnti-HIV AgentsAntiretroviral Therapy, Highly ActiveCD4 Lymphocyte CountCD4-Positive T-LymphocytesDisease ProgressionFemaleHIV InfectionsHumansMaleMiddle AgedTanzaniaYoung AdultAnti-HIV Agents

Identifiers

PMID27716818
PMCPMC5055355
OpenAlexW2529177547

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.