Evidence map›Paper›PMID 42495948›Full record

ArticleJournal of global health2026

Efficient high-risk human papillomavirus screening through pooled testing: a simulation study based on real-world data in low- and middle-income countries.

Fengming Pan, Marcel Jw Greuter, Jaap Ar Koot, Heather Cubie, Naheed Nazrul, Carolyn Nakisige, Jogchum Beltman, Geertruida H de Bock, Jurjen van der Schans

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Article in Journal of global health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Fengming PanDepartment of Epidemiology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands.
Marcel Jw GreuterDepartment of Radiology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands.
Jaap Ar KootUnit of Global Health, Department of Health Sciences, University Medical Centre Groningen, Groningen, the Netherlands.
Heather CubieGlobal Health Academy, University of Edinburgh, Edinburgh, UK.
Naheed NazrulHealth Sector, Friendship NGO, Dhaka, Bangladesh.
Carolyn NakisigeDepartment of Gynaecologic-Oncology, Uganda Cancer Institute, Kampala, Uganda.
Jogchum BeltmanDepartment of Gynaecology, Leiden University Medical Centre, Leiden University, Leiden, the Netherlands.
Geertruida H de BockDepartment of Epidemiology, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands.
Jurjen van der SchansUnit of Global Health, Department of Health Sciences, University Medical Centre Groningen, Groningen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The World Health Organization recommends high-risk human papillomavirus (hrHPV) testing as the primary method for cervical cancer screening. Combining samples in a pool can reduce the expense associated with large numbers of commercially available tests. This study simulated the potential test-saving impact of pooled hrHPV testing using real-world data from two low- and middle-income countries (LMICs). Methods: We simulated a two- and three-stage hrHPV pooling in Bangladesh (hrHPV prevalence 2.10%) and Uganda (hrHPV prevalence 22.52%) using real-world laboratory data. Measurements included the number of tests per stage, the total number of tests, and the percentage of tests saved. We performed sensitivity analysis to assess the impact of a 1.00% loss of sensitivity and specificity per additional sample in the pool on the false-negative rate (FNR). Results: In Bangladesh, the two-stage strategy (eight samples per pool) and the three-stage strategy saved 71.21% and 77.21% of tests, respectively, compared to testing individually. In Uganda, the two-stage strategy (three samples per pool) reduced the number of tests by 15.34% compared to testing individually. Assuming loss of sensitivity and specificity due to pooling, the FNR was higher (FNR = 0.012-0.134) when hrHPV prevalence was low under the two-stage strategy. Conclusions: Pooled hrHPV testing has the potential to reduce the number of tests used and enhance screening capacity in resource-limited settings. Notably, a lower prevalence of hrHPV allows for more efficient pooled testing. Despite the potential loss of sensitivity and specificity, pooled hrHPV testing could offer benefits for LMICs and warrant further verification.

Indexed as

Developing CountriesEarly Detection of CancerHuman Papillomavirus VirusesMass ScreeningPapillomavirus InfectionsUterine Cervical NeoplasmsBangladeshComputer SimulationFemaleHumansPooled TestingPrevalenceSensitivity and SpecificityUgandacervical cancerhuman papillomavirus DNA testslow- and middle-income countriespooled testingsample poolingscreening

Identifiers

PMID42495948
PMCPMC13397869

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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.