Evidence map›Paper›PMID 24465831›Full record

ArticlePloS one2014

Comparison of droplet digital PCR and seminested real-time PCR for quantification of cell-associated HIV-1 RNA.

Maja Kiselinova, Alexander O Pasternak, Ward De Spiegelaere, Dirk Vogelaers, Ben Berkhout, Linos Vandekerckhove

Abstract readComparative Study
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.

0numbers the graph read from it
0cells of the map it votes in
88citing 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

88 citing papers in PubMed.

  1. Predictors of Cell-Associated Human Immunodeficiency Virus (HIV)-1 DNA Over 1 Year in Very Early Treated Infants.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Trial
  2. Article
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  6. Observational
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Double Digital Assay for Single Extracellular Vesicle and Single Molecule Detection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  14. Article
  15. Article
  16. Research progress in laboratory detection of SARS-CoV-2.Irish journal of medical science · 2022
    Review
  17. Article
  18. Article
  19. Review
  20. Review

28 more citing papers are in PubMed but not listed here.

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.

Maja KiselinovaHIV Translational Research Unit (HTRU), Department of Internal Medicine, Ghent University and Ghent University Hospital, Ghent, Belgium.
Alexander O PasternakDepartment of Medical Microbiology, Laboratory of Experimental Virology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Ward De SpiegelaereHIV Translational Research Unit (HTRU), Department of Internal Medicine, Ghent University and Ghent University Hospital, Ghent, Belgium.
Dirk VogelaersHIV Translational Research Unit (HTRU), Department of Internal Medicine, Ghent University and Ghent University Hospital, Ghent, Belgium.
Ben BerkhoutDepartment of Medical Microbiology, Laboratory of Experimental Virology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Linos VandekerckhoveHIV Translational Research Unit (HTRU), Department of Internal Medicine, Ghent University and Ghent University Hospital, Ghent, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-associated (CA) HIV-1 RNA is considered a potential marker for assessment of viral reservoir dynamics and antiretroviral therapy (ART) response in HIV-infected patients. Recent studies employed sensitive seminested real-time quantitative (q)PCR to quantify CA HIV-1 RNA. Digital PCR has been recently described as an alternative PCR-based technique for absolute quantification with higher accuracy compared to qPCR. Here, a comparison was made between the droplet digital PCR (ddPCR) and the seminested qPCR for quantification of unspliced (us) and multiply spliced (ms) CA HIV-1 RNA. Synthetic RNA standards and CA HIV-1 RNA from infected patients on and off ART (N = 34) were quantified with both methods. Correlations were observed between the methods both for serially diluted synthetic standards (usRNA: R2 = 0.97, msRNA: R2 = 0.92) and patient-derived samples (usRNA: R2 = 0.51, msRNA: R2 = 0.87). Seminested qPCR showed better quantitative linearity, accuracy and sensitivity in the quantification of synthetic standards than ddPCR, especially in the lower quantification ranges. Both methods demonstrated equally high detection rate of usRNA in patient samples on and off ART (91%), whereas ddPCR detected msRNA in larger proportion of samples from ART-treated patients (p = 0.13). We observed an average agreement between the methods for usRNA quantification in patient samples, albeit with a large standard deviation (bias = 0.05±0.75 log10). However, a bias of 0.94±0.36 log10 was observed for msRNA. No-template controls were consistently negative in the seminested qPCR, but yielded a positive ddPCR signal for some wells. Therefore, the false positive signals may have affected the detection power of ddPCR in this study. Digital PCR is promising for HIV nucleic acid quantification, but the false positive signals need further attention. Quantitative assays for CA HIV RNA have the potential to improve monitoring of patients on ART and to be used in clinical studies aimed at HIV eradication, but should be cross-validated by multiple laboratories prior to wider use.

Indexed as

HIV-1HumansLeukocytes, MononuclearReal-Time Polymerase Chain ReactionReference StandardsRNA SplicingRNA, ViralRNA, Viral

Identifiers

PMID24465831
PMCPMC3897572

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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.