ArticleBMJ open2022
Performance of HPV E4 and p16
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05049252 (Performance of HPV E4 and p16INK4a Biomarkers in Predicting Risk of Regression Among Women Diagnosed With Cervical Intraepithelial Neoplasia Grade 2), which is not on this map. Cited by 6 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.
Performance of HPV E4 and p16INK4a Biomarkers in Predicting Risk of Regression Among Women Diagnosed With Cervical Intraepithelial Neoplasia Grade 2 (CIN2): a Historical Cohort Study
Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Integrating Biomarkers into Cervical Cancer Screening-Advances in Diagnosis and Risk Prediction: A Narrative Review.Diagnostics (Basel, Switzerland) · 2025Review
- p16International journal of cancer · 2025Article
- Human papillomavirus (HPV) genotyping and prognostic value of HPV E4 protein and transcription factors NANOG and SOX11 in atypical p16 patchy squamous epithelium of cervix.Radiology and oncology · 2025Article
- Serum Antibodies Against the E5 Oncoprotein from Human Papillomavirus Type 16 Are Inversely Associated with the Infection and the Degree of Cervical Lesions.Biomedicines · 2024Article
- Validation of an on-chip p16Scientific reports · 2023Article
- High prevalence of HPV16 and high-grade cytology in women undergoing active surveillance for cervical intraepithelial neoplasia grade 2.Acta obstetricia et gynecologica Scandinavica · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 7 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionCervical intraepithelial neoplasia grade 2 (CIN2) represents a spectrum of lesions with variable progression and regression. Pathological diagnosis of CIN2 is subjective and poorly reproducible. Accurate diagnosis and identification of different patterns of CIN2 related to outcome are essential to reduce the risks of overtreatment or undertreatment. It is important to explore novel methods for risk stratification of CIN2 to enable targeted treatment of women at high risk of progression or persistent disease and follow-up of women at low risk. The combination of the novel biomarker human papillomavirus (HPV) E4 with p16 METHODS AND ANALYSIS: We will conduct a historical cohort study including 500 women aged 23-40 years with a first CIN2 diagnosis in Aarhus, Denmark during 2000-2010. Women will be eligible if they have undergone active surveillance and have no previous record of hysterectomy, cone biopsy, and CIN2 or worse. Women will be randomly selected through the Danish Pathology Databank. Tissue samples from women included will be sectioned for p16 ETHICS AND DISSEMINATION: The study has been approved by the Ethical Committee in Central Denmark Region (1-10-72-60-20) and registered at the Faculty of Health, Aarhus University. Results will be published in a peer-reviewed journal and presented at scientific meetings. TRIAL REGISTRATION NUMBER: NCT05049252.
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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.