ArticleFrontiers in public health2022
Comparison of cycle threshold values of the Cobas HPV test and viral loads of the BMRT HPV test in cervical cancer screening.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Extended HPV genotyping by the BD Onclarity assay: concordance with screening HPV-DNA assays, triage biomarkers, and histopathology in women from the NTCC2 study.Microbiology spectrum · 2025Trial
- Relative HPV Viral Load Measured by ΔCt for Risk Stratification in Cervical Cancer Screening.Cancers · 2026Article
- Risk Factors for Human Papillomavirus Positivity in a Tertiary Care Center: A Case-Control Study Incorporating Genotype Distribution, Co-Infection Patterns, and Quantitative Viral Load Analysis.Journal of clinical medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To validate the HPV viral loads that are reflected by the cycle threshold values of Cobas4800 as the viral load indicators by verifying the consistency of the viral loads per unit (10,000 cells) from the BMRT assay. Methods: The analysis is based on data from the Chinese Multi-Center Screening Trial (CHIMUST). The cases included in the analysis are all positive for physician-collected hrHPV on SeqHPV and/or Cobas4800 or negative for hrHPV but abnormal in cytology (≥LSIL), and some cases selected by nested case-control randomization from those negative for physician-collected hrHPV and cytology. With HPV testing results and relevant Ct values from Cobas4800 available, we tested the entire sample set with the BMRT HPV testing assay and analyzed their agreement with Cobas4800, followed by a comparison of the CtV from Cobas4800 and viral loads (lg) from BMRT by lesion grade. Results: We included 4,485 women (mean age: 45.4 years) in the study, and 4,290 had complete data. The consistency of genotypes from Cobas4800 and BMRT for hrHPV, HPV-16, HPV-18, and 12-HPV pools was 94.9% (4070/4290, Kappa = 0.827), 99.1% (4251/4290, Kappa = 0.842), 99.6% (4,273/4,290, Kappa = 0.777), and 95.3% (4,089/4,290, Kappa = 0.821), respectively. Further analysis shows that any inconsistency between the two assays is likely among samples with comparatively lower viral loads. When analyzing per lesions of CIN2+ and CIN3+, the CtV from Cobas4800 and VL (lg) from BMRT are highly correlated inversely and follow the linear regression for HPV16 and 12-HPV pool (Pearson's or Spearman's correlation coefficient (r): In CIN3+, r Conclusion: The CtV from Cobas4800 and the viral loads (lg) of per unit cells from the BMRT are well correlated for lesion grading when tested on physician-collected samples. Cobas-CtV is worthy of further study for clinical application.
Indexed as
Identifiers
What OpenQuestion holds
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.