Evidence map›Paper›PMID 31291281›Full record

ArticlePloS one2019

Model-based prediction of CD4 cells counts in HIV-infected adults on antiretroviral therapy in Northwest Ethiopia: A flexible mixed effects approach.

Tadesse Awoke Ayele, Alemayehu Worku, Yigzaw Kebede, Khangelani Zuma, Adetayo Kasim, Ziv Shkedy

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

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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

6 authors at 5 institutions in 4 countries.

Tadesse Awoke AyeleEpidemiology and Biostatistics, University of Gondar, Gondar, Ethiopia.ORCID 0000-0002-1839-3522
Alemayehu WorkuSchool of Public Health, Addis Ababa University, Addis Ababa, Ethiopia.
Yigzaw KebedeEpidemiology and Biostatistics, University of Gondar, Gondar, Ethiopia.
Khangelani ZumaHealth Sciences Research Council, Pretoria, South Africa.
Adetayo KasimWolfson Research Institute, Durham University, Durham, United Kingdom.
Ziv ShkedyI-BioStat, Hasselt University, Diepenbeek, Belgium.
University of Gondar · ETAddis Ababa University · ETDurham University · GBHasselt University · BEHuman Sciences Research Council · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCD4 cell counts is widely used as a biomarker for treatment progression when studying the efficacy of drugs to treat HIV-infected patients. In the past, it had been also used in determining eligibility to initiate antiretroviral therapy. The main aim of this was to model the evolution of CD4 counts over time and use this model for an early prediction of subject-specific time to cross a pre-specified CD4 threshold.

methodsHospital based retrospective cohort study of HIV-infected patients was conducted from January 2009 to December 2014 at University of Gondar hospital, Northwest Ethiopia. Fractional polynomial random effect model is used to model the evolution of CD4 counts over time in response to treatment and to estimate the individual probability to be above a pre-selected CD4 threshold. Human subject research approval for this study was received from University of Gondar Research Ethics Committee and the medical director of the hospital.

resultsA total of 1347 patients were included in the analysis presented in this paper. The cohort contributed a total of 236.58 per 100 person-years of follow-up. Later the data were divided into two periods: the first is the estimation period in which the parameters of the model are estimated and the second is the prediction period. Based on the parameters from the estimation period, model based prediction for the time to cross a threshold was estimated. The correlations between observed and predicted values of CD4 levels in the estimation period were 0.977 and 0.982 for Neverapine and Efavirenz containing regimens, respectively; while the correlation between the observed and predicted CD4 counts in the prediction period are 0.742 and 0.805 for NVP and EFV, respectively.

conclusionsThe model enables us to estimate a subject-specific expected time to cross a CD4 threshold and to estimate a subject-specific probability to have CD4 count above a pre-specified threshold at each time point. By predicting long-term outcomes of CD4 count of the patients one can advise patient about the potential ART benefits that accrue in the long-term.

Indexed as

Antiretroviral Therapy, Highly ActiveCD4 Lymphocyte CountAdultAlkynesAnti-HIV AgentsBenzoxazinesCD4-Positive T-LymphocytesCyclopropanesDisease ProgressionEthiopiaHIV InfectionsHumansModels, BiologicalRetrospective StudiesAlkynesAnti-HIV AgentsBenzoxazinesCyclopropanesefavirenz

Identifiers

PMID31291281
PMCPMC6619674
OpenAlexW2957284497

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LicenceCC BY
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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.