Self-Sampling Kits at GP Visits Could Prevent 1,000 Cervical Cancers Annually
Offering HPV self-collection kits during routine GP appointments boosts screening rates among overdue women, helping prevent cervical cancer

A new study led by Queen Mary University of London and King’s College London shows that offering HPV self-sampling kits during routine GP visits significantly increases cervical cancer screening among women overdue for testing. Involving nearly 12,000 women from 13 GP practices in west London, the research found that over half (52 percent) of women offered a kit in person during unrelated GP appointments returned samples for testing. This uptake is far higher than the 12 percent who returned kits sent by post and the 5 percent who responded to a letter offering a kit.
Cervical cancer, which affects around 3,300 women annually in the UK, is one of the most preventable cancers. Regular screening can reduce the risk of developing cervical cancer by 80-90 percent, especially for women born before HPV vaccination programs began. However, screening rates have fallen in recent years, with only 66 percent of eligible women up to date in 2024.
Researchers estimate that integrating self-sampling kits into routine GP visits could prevent up to 1,000 cases of cervical cancer each year in England. They suggest that combining opportunistic in-person offers with mailed kits may be the most effective way to reach women who face barriers to screening, such as discomfort, embarrassment, or lack of time.
Cancer Research UK supports these findings, emphasizing that home testing can make cervical screening more accessible and reduce unnecessary anxiety. The government has recently committed to rolling out home testing kits for those overdue for screening, and this study highlights the value of offering kits during GP visits to further increase participation.
Overall, this simple change could help save lives by improving early detection and preventing cervical cancer on a larger scale.
Note: This news summary was generated by AI based on a published press release, followed by a review from human editors.
