ArticleEClinicalMedicine2023
Self-sampling and HPV DNA testing for cervical precancer screening in a cohort of nuns in Ghana: a cross-sectional cohort study.
Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Prevalence of cervical human papillomavirus infection among women in Ghana: a systematic review and meta-analysis.BMC public health · 2026Pooled it
- Advancing the elimination of cervical cancer across Africa.Nature communications · 2026Review
- Implementing High-Risk Human Papillomavirus Self-Sampling for Cervical Cancer Screening in Ghana: A Study (CarciSCAN) Protocol.Cancer control : journal of the Moffitt Cancer CenterArticle
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 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The need for cervical cancer screening has been emphasised in at-risk cohorts of women to reduce their risk of cervical cancer. Some women with decreased risk of acquiring human papillomavirus (HPV) infections, such as Catholic nuns, receive less attention and on occasion are missed in cervical cancer screening programmes. This study aimed to determine the high-risk HPV (hr-HPV) prevalence in such a cohort to emphasise the need for cervical precancer screening among all women. To improve compliance, we employed self-sampling. Methods: This descriptive cross-sectional cohort study involved the data of 105 Catholic nuns subjected to cervical screening using self-samples in the Greater Accra, Volta, and Central regions of Ghana between June 4, 2022 and June 30, 2022. hr-HPV testing was performed on self-samples using the MA-6000 HPV DNA platform. Screen-positive nuns underwent follow-up pap smears and EVA colposcopy. In addition to descriptive analysis, univariate and multivariable nominal logistic regression was used to explore the relationship between hr-HPV positivity and selected continuous and categorical factors. Findings: 105 nuns from three convents were screened with hr-HPV DNA testing (MA-6000). Twenty-five tested positive for hr-HPV (prevalence of 23.8% (95% CI, 15.7-32.0) [HPV 18 only (n = 2, 1.9%), non-HPV 16/18 genotypes ( Interpretation: Our findings suggest that the hr-HPV prevalence in this cohort of nuns is similar to that of the general population. To meet the World Health Organization's target for cervical cancer elimination, it is important that all women are given access to cervical cancer screening and preventative services. Further, increasing 'anonymity' and privacy among nuns through self-sampling may be crucial to expanding choice, coverage, and uptake of screening in support of their health rights. Funding: None.
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.