ArticleInternational journal of clinical and experimental pathology2018
Detection and genotyping of human papillomavirus virus (HPV): a comparative analysis of clinical performance in cervical and urine samples in Chilean women.
Article in International journal of clinical and experimental pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Accuracy of human papillomavirus tests on self-collected urine versus clinician-collected samples for the detection of cervical precancer: a systematic review and meta-analysis.Journal of gynecologic oncology · 2022Pooled it
- Genital and Oral HPV Geno-Prevalence Measured through Urine and Saliva Samples in Young Adults in Italy.Vaccines · 2024Article
- Triage of human papillomavirus infected women by methylation analysis in first-void urine.Scientific reports · 2021Article
- Article
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human papillomavirus (HPV) is the most common sexually transmitted infectious agent and is the main cause of cervical cancer (CC). In Chile, CC is the second leading cause of death by cancer in women aged 20-44 years, four times higher than in developed countries. Currently, the detection of HPV infection using a cervical brush is recommended; however, this is an invasive procedure that many women try to avoid. The aim of this study was to evaluate the clinical performance of a self-collected, urine-based HPV detection method using conventional PCR followed by a reverse line blot. A PCR-based HPV genotyping was performed on 190 paired cervical and urine samples from gynecological exams at public health centers in the Araucania Region, Chile. HPV DNA detection and genotyping were performed by PCR and reverse line blot assay. Carcinogenic HPV types were present in 64.7% and 65.8% of the cervical and urine samples; the infection rates of HPV16 were 34.7% and 33.2%, respectively. The overall percent agreement between carcinogenic HPV detection in cervical and urine samples was 73.7%, with a moderate concordance rate of carcinogenic HPV detection (kappa = 0.42). Clinical sensitivities for cervical and urine-based sampling methods to diagnose cervical intraepithelial neoplasia 2/3 (CIN2/3) by histology were 93.4% and 90.2%, respectively. These results suggest that both cervical brush and urine-based sampling show a good clinical performance in the detection of HPV infection. The urine-based sampling method represents a valuable alternative with a great impact on public health, allowing increased cervical cancer screening coverage among women who do not undergo pelvic examinations.
Indexed as
Identifiers
31949624PMC6963012W3004625217What 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.