Evidence map›Paper›PMID 39698327›Full record

ArticleChina CDC weekly2024

Study on the Technical Parameters for Estimating HIV-1 Incidence by Using a Recombinant Antigen-based Capture Enzyme Immunoassay - China.

Wenli Liang, Jibao Wang, Hongxia Yan, Xinhui Zhang, Dorjiwangmo, Dongmin Li, Xing Duan, Hao Wu, Yinyin Wang, Li Bai and 10 more

Abstract read
In one paragraph

Article in China CDC weekly, 2024. 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

20 authors.

Wenli LiangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Jibao WangDepartment of AIDS/STD Control and Prevention, Dehong Center for Disease Control and Prevention, Mangshi County, Dehong Dai and Jingpo Autonomous Prefecture, Yunnan Province, China.
Hongxia YanBeijing Key Laboratory for HIV/AIDS Research, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Xinhui ZhangInstitute of Infectious Diseases Prevention and Treatment, Guizhou Provincial Center for Disease Control and Prevention, Guiyang City, Guizhou Province, China.
DorjiwangmoDepartment of AIDS Control and Prevention, Xizang Autonomous Region Center for Disease Control and Prevention, Lhasa City, Xizang Autonomous Region, China.
Dongmin LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xing DuanDepartment of AIDS/STD Control and Prevention, Dehong Center for Disease Control and Prevention, Mangshi County, Dehong Dai and Jingpo Autonomous Prefecture, Yunnan Province, China.
Hao WuBeijing Key Laboratory for HIV/AIDS Research, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Yinyin WangExperimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang City, Guizhou Province, China.
Li BaiDepartment of AIDS Control and Prevention, Gansu Provincial Center for Disease Control and Prevention, Lanzhou City, Gansu Province, China.
Jian SunDepartment of AIDS Control and Prevention, Xizang Autonomous Region Center for Disease Control and Prevention, Lhasa City, Xizang Autonomous Region, China.
Mengjie HanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yikui WangDepartment of AIDS/STD Control and Prevention, Dehong Center for Disease Control and Prevention, Mangshi County, Dehong Dai and Jingpo Autonomous Prefecture, Yunnan Province, China.
Bin SuBeijing Key Laboratory for HIV/AIDS Research, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Min WangLaboratory Department, Liupanshui Center for Disease Control and Prevention, Liupanshui City, Guizhou Province, China.
TashibazongDepartment of AIDS Control and Prevention, Xizang Autonomous Region Center for Disease Control and Prevention, Lhasa City, Xizang Autonomous Region, China.
Wenge XingNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Cui ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Ruijuan QiaoDepartment of AIDS Control and Prevention, Gansu Provincial Center for Disease Control and Prevention, Lanzhou City, Gansu Province, China.
Maofeng QiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A novel recombinant antigen-based capture enzyme immunoassay (RAg-CEIA) was optimized and used to determine technical parameters for estimating human immunodeficiency virus type 1 (HIV-1) incidence in China. Methods: We employed orthogonal experimental design to optimize RAg-CEIA by adjusting raw material dilution ratios. The assay was used to measure normalized optical density (ODn) values in 171 longitudinal plasma specimens from 51 HIV-1 seroconverting individuals, plotted against estimated days post-seroconversion. We determined the optimal ODn threshold value for differentiating recent from long-term infections and calculated the mean duration of recent infection (MDRI) for incidence estimation. The false recent rate (FRR) was determined using 481 HIV-1 antibody-positive specimens with infection durations exceeding twice the MDRI. Results: Optimal RAg-CEIA parameters were established with a raw material dilution ratio of 1/12 for calibrator preparation and an enzyme conjugate titer of 1:1200. ODn values demonstrated consistent temporal increases across HIV-1 seroconverting individuals, though with notable kinetic heterogeneity in individual responses. The optimal ODn threshold value of 0.8 for distinguishing recent from long-term infections corresponded to an MDRI of 205 days and an FRR of 4.78%. Conclusions: The optimized RAg-CEIA effectively differentiates recent from long-term HIV-1 infections at the population level, enabling reliable HIV-1 incidence estimation in China.

Indexed as

Capture enzyme immunoassayFalse recent rateHIV-1 incidenceMean duration of recent infection

Identifiers

PMID39698327
PMCPMC11649990

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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.