Evidence map›Paper›PMID 42192312›Full record

ArticleBMC infectious diseases2026

Performance comparison of CD4 T-cell count instruments based on data from the national proficiency testing program in China, 2016-2023.

Hui Zhang, Haifeng Ding, Pei Liu, Meilin Wang, Qiyu Zhu, Xin Zhang, Mengjun Ding, Fangfang Liu, Mingzhu Niu, Cong Jin

Abstract readComparative Study
In one paragraph

Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Hui Zhang *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Haifeng Ding *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Pei Liu *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Meilin WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Qiyu ZhuNational Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xin ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Mengjun DingNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Fangfang LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Mingzhu NiuDepartment of Epidemiology, School of Public Health, China Medical University, Shenyang, China.
Cong JinNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China. jinc@chinaaids.cn.

Funding

Natural Science Foundation of Beijing Municipality L234054,L244069
6 · The paper itself

Abstract

backgroundThe number of CD4 T cells is an important indicator of immune status in people living with HIV (PWH). In China, numerous CD4 count instruments have been approved; however, no studies have been conducted to systematically compare the performance of these instruments.

methodsWe retrospectively analyzed data from the national proficiency testing program for CD4 T-cell counts in China from 2016 to 2023. We conducted comparative analysis to evaluate the performance of 10 mainstream CD4 count instruments. Passing-Bablok regression and mix-effects model analyses were used to analyze the agreement and interchangeability of test results among instruments.

resultsThe proportion of laboratories participating in the CD4 proficiency testing program and using Chinese-manufactured and point-of-care testing instruments has increased annually, from 4.7% to 29.7% and from 3.3% to 8.1%, respectively. The results of the 10 devices tested showed strong correlations and agreement with target values, with correlation coefficients (R²) ranging from 0.952 to 0.983 and with the mean bias ranged from -1 to + 95 cells/µL across the 10 devices. Strong agreement was observed among the results for the 10 instruments, slopes ranged from 0.866 to 1.214, while the intercepts varied from  -42.3 cells/µL to + 24.0 cells/µL. After adjusting for sample and laboratory effects using a linear mixed-effects model, eight instruments (B, C, D, M, J, F

conclusionsThe performance of commonly used CD4 count instruments was comparable and can meet the needs of HIV testing laboratories. CLINICAL TRIAL: Not applicable.

Indexed as

CD4-Positive T-LymphocytesHIV InfectionsLaboratory Proficiency TestingCD4 Lymphocyte CountChinaHumansRetrospective StudiesCD4 T-cell countHIVProficiency testing

Identifiers

PMID42192312
PMCPMC13397692

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.