ArticleJournal of clinical microbiology2016
Quantitative Assessment of Commutability for Clinical Viral Load Testing Using a Digital PCR-Based Reference Standard.
Article in Journal of clinical microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- Matrix Matters: Assessment of Commutability among BK Virus Assays and Standards.Journal of clinical microbiology · 2022Article
- Persistent Challenges of Interassay Variability in Transplant Viral Load Testing.Journal of clinical microbiology · 2020Review
- Impact of Fragmentation on Commutability of Epstein-Barr Virus and Cytomegalovirus Quantitative Standards.Journal of clinical microbiology · 2019Article
- A Comprehensive Statistical Framework for Determination of Commutability, Accuracy, and Agreement in Clinical DNAemia Assays.Journal of clinical microbiology · 2019Article
- EBV Viral Loads in Diagnosis, Monitoring, and Response Assessment.Frontiers in oncology · 2019Review
- Quantitative Inference of Commutability for Clinical Viral Load Testing.Journal of clinical microbiology · 2018Article
- Quantification of Torque Teno Virus and Epstein-Barr Virus Is of Limited Value for Predicting the Net State of Immunosuppression After Lung Transplantation.Open forum infectious diseases · 2018Article
- Circulating pre-treatment Epstein-Barr virus DNA as prognostic factor in locally-advanced nasopharyngeal cancer in a non-endemic area.Oncotarget · 2017Article
- Applications of Digital PCR for Clinical Microbiology.Journal of clinical microbiology · 2017Review
- The Future of Digital Polymerase Chain Reaction in Virology.Molecular diagnosis & therapy · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Given recent advances in the development of quantitative standards, particularly WHO international standards, efforts to better understand the commutability of reference materials have been made. Existing approaches in evaluating commutability include prediction intervals and correspondence analysis; however, the results obtained from existing approaches may be ambiguous. We have developed a "deviation-from-ideal" (DFI) approach to evaluate commutability of standards and applied it to the assessment of Epstein-Bar virus (EBV) load testing in four quantitative PCR assays, treating digital PCR as a reference assay. We then discuss advantages and limitations of the DFI approach as well as experimental design to best evaluate the commutability of an assay in practice.
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Registered trials
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.