Evidence map›Paper›PMID 26558543›Full record

ArticleAIDS (London, England)2015

CD4+ cell dynamics in untreated HIV-1 infection: overall rates, and effects of age, viral load, sex and calendar time.

Anne Cori, Michael Pickles, Ard van Sighem, Luuk Gras, Daniela Bezemer, Peter Reiss, Christophe Fraser

Abstract read
In one paragraph

Article in AIDS (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. A Review of Network Models for HIV Spread.Journal of acquired immune deficiency syndromes (1999) · 2025
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  15. The impact of bone marrow stromal antigen-2 (BST2) gene variants on HIV-1 control in black South African individuals.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Anne CoriaDepartment of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK bStichting HIV Monitoring, Amsterdam, The Netherlands.
Michael Pickles
Ard van Sighem
Luuk Gras
Daniela Bezemer
Peter Reiss
Christophe Fraser

Funding

LOC: HIV Prevention Trials NetworkUM1AI068619 · NIAID · FAMILY HEALTH INTERNATIONAL · PI Sinead Delany-Moretlwe, RAPHAEL J LANDOVITZ · 2011 to 2026
$779.5M
European Research Council 339251Medical Research Council MR/K010174/1NIAID NIH HHS UM1 AI068619NIAID NIH HHS UM1AI068619
6 · The paper itself

Abstract

backgroundCD4 cell count is a key measure of HIV disease progression, and the basis of successive international guidelines for treatment initiation. CD4 cell dynamics are used in mathematical and econometric models for evaluating public health need and interventions. Here, we estimate rates of CD4 decline, stratified by relevant covariates, in a form that is clinically transparent and can be directly used in such models.

methodsWe analyse the AIDS Therapy Evaluation in the Netherlands cohort, including individuals with date of seroconversion estimated to be within 1 year and with intensive clinical follow-up prior to treatment initiation. Owing to the fact that CD4 cell counts are intrinsically noisy, we separate the analysis into long-term trends of smoothed CD4 cell counts and an observation model relating actual CD4 measurements to the underlying smoothed counts. We use a monotonic spline smoothing model to describe the decline of smoothed CD4 cell counts through categories CD4 above 500, 350-500, 200-350 and 200 cells/μl or less. We estimate the proportion of individuals starting in each category after seroconversion and the average time spent in each category. We examine individual-level cofactors which influence these parameters.

resultsAmong untreated individuals, the time spent in each compartment was 3.32, 2.70, 5.50 and 5.06 years. Only 76% started in the CD4 cell count above 500 cells/μl compartment after seroconversion. Set-point viral load (SPVL) was an important factor: individuals with at least 5 log10 copies/ml took 5.37 years to reach CD4 cell count less than 200 cells/μl compared with 15.76 years for SPVL less than 4 log10 copies/ml.

conclusionMany individuals already have CD4 cell count below 500 cells/μl after seroconversion. SPVL strongly influences the rate of CD4 decline. Treatment guidelines should consider measuring SPVL, whereas mathematical models should incorporate SPVL stratification.

Indexed as

Viral LoadAdultAge FactorsCD4 Lymphocyte CountCD4-Positive T-LymphocytesCohort StudiesFemaleHIV-1HIV InfectionsHumansMaleModels, TheoreticalNetherlandsSex FactorsTime Factors

Identifiers

PMID26558543
PMCPMC4645962

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Registered trials

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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.