Offering HPV self-sampling kits: an updated meta-analysis of the effectiveness of strategies to increase participation in cervical cancer screening
Open accessAbstract
Background Human papillomavirus (HPV) testing on self-samples represents a great opportunity to increase cervical cancer screening uptake among under-screened women. Methods A systematic review and meta-analysis on randomised controlled trials (RCTs) were performed to update the evidence on the efficacy of strategies for offering self-sampling kits for HPV testing compared to conventional invitations and to compare different self-sampling invitation scenarios. Four experimental invitational scenarios were considered. Women in the control group were invited for screening according to existing practice: collection of a cervical specimen by a healthcare professional. Random-effects models were used to pool proportions, relative participation rates and absolute participation differences. Results Thirty-three trials were included. In the intention-to-treat analysis, all self-sampling invitation scenarios were more effective in reaching under-screened women compared to controls. Pooled participation difference (PD) and 95% confidence interval (CI) for experimental vs. control was 13.2% (95% CI = 11.0-15.3%) for mail-to-all, 4.4% (95% CI = 1.2-7.6%) for opt-in, 39.1% (95% CI = 8.4-69.9%) for community mobilisation & outreach and 28.1% (23.5-32.7%) for offer at healthcare service. PD for the comparison opt-in vs. mail-to-all, assessed in nine trials, was -8.2% (95% CI = -10.8 to -5.7%). Discussion Overall, screening participation was higher among women invited for self-sampling compared to control, regardless of the invitation strategy used. Opt-in strategies were less effective than send-to-all strategies.
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HPV self-sampling increases screening participation rates.
“HPV self-sampling increases the screening participation rates [12] and thus increases the screening coverage [13].”
From Performance of HPV Self-Sample Collected by a Novel Kit in Comparison with Clinician Collected Sample for Cervical Cancer Screening (2024) · cites this paper as [12]
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- Authors
- Costa, S., Verberckmoes, B., Castle, P. E., & Arbyn, M.
- Affiliations
- Sciensano (Belgium) (BE)
- Ghent University Hospital (BE)
- National Cancer Institute (US)
- Ghent University (BE)
- Corresponding author
- Arbyn, Marc
- Venue
- British Journal of Cancer
- Published
- 2022-12-14
- Volume
- 128
- Issue
- 5
- Pages
- 805-813
- ISSN
- 0007-0920 (ISSN-L)
- 1532-1827
- PMC
- PMC9977737
- OpenAlex
- W4311399768
- Cited by
- 139
- References
- 63
- Citations by year
- 2026: 44 · 2025: 45 · 2024: 38 · 2023: 12
- FWCI
- 3.77
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- British Journal of Cancer (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Funders
- EC | Horizon 2020 Framework Programme (825747, 847845)
- U.S. Department of Health & Human Services | NIH | NCI | Division of Cancer Epidemiology and Genetics, National Cancer Institute (ZIACP101237-01)
- VALHUDES researcher-induced frameworks for comparison and validation of HPV tests used on clinician-collected and self-collected samples
- Topics
- Health Sciences › Medicine › Epidemiology › Cervical Cancer and HPV Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Women's cancer prevention and management
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Keywords
- HPV self-sampling, cervical cancer screening, screening uptake, community mobilization, underscreened women, HPV testing
- MeSH terms
- Uterine Cervical Neoplasms, Female, Humans, Mass Screening, Self Care, Specimen Handling, Vaginal Smears, Papillomaviridae, Papillomavirus Infections, Early Detection of Cancer
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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