ArticleGynecologic oncology reports2023
Digital cervicography for cervical cancer screening in low-resource settings: A scoping review.
Article in Gynecologic oncology reports, 2023. 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, 3 citations in OpenAlex.
- Diagnostic Accuracy of Artificial Intelligence vs. Oncologist Interpretation in Digital Cervicography for Abnormal Cervical Cytology.Journal of clinical medicine · 2025Article
- Feasibility of incorporating the Pocket colposcope into nurse-led cervical cancer screening programs in Western Kenya.Ecancermedicalscience · 2025Article
- Designing CITOBOT: A portable device for cervical cancer screening using human-centered design, smart prototyping, and artificial intelligence.Computational and structural biotechnology journal · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Digital cervicography (DC) is a method of capturing images for analysis during visual inspection with acetic acid (VIA) for cervical cancer screening. Cervical cancer is the 3rd leading cause of female cancer in the world with approximately 90 % of deaths due to cervical cancer occurring in low and middle income countries (LMICs). The need for cost-effective and sustainable methods for screening is vital in these settings. This scoping review systematically synthesizes published data illustrating the use of DC in screening programs. We aim to understand how digital cervicography is used, implemented, and impacted on programs. Methods: Search of eight online databases identified 53 studies published between 1993 and 2021. Inclusion of articles were English language, cervical cancer screening program located in an LMIC, and DC as an intervention. Results: All studies were cross-sectional studies (n = 53), with variation in terminology, uses, and device methods. Devices were grouped as either smartphones (n = 14), commercially available digital cameras (n = 17), or other (EVA®, n = 4; Cerviscope, n = 12; custom device, n = 4; or not specified, n = 2). Nineteen studies found acceptability and feasibility for DC in their screening programs. Various programs using DC found benefits such as task sharing, healthcare worker training, patient education and using images for review from a remote specialist or mentor. Conclusion: The use of DC in LMICs is beneficial for support of healthcare workers, enhances quality improvement and demonstrates overall acceptability in screening programs. Advancing technologies for human papillomavirus (HPV) testing and cytology are common methods for cervical cancer screening, although are limited in LMICs. This scoping review demonstrates the different methods, uses, and benefit of digital cervicography in cervical cancer screening programs.
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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.