Gomes Michelle, Provaggi Elena, Pembe Andrea Barnabas, Olaitan Adeola, Gentry-Maharaj Aleksandra
Department of Global Health and Development, The London School of Hygiene and Tropical Medicine (LSHTM), London WC1E 7HT, UK.
Anne's Day Ltd. (Daye), London SE16 4DG, UK.
Diagnostics (Basel). 2025 May 6;15(9):1176. doi: 10.3390/diagnostics15091176.
Cervical cancer causes 350,000 deaths annually, with 90% occurring in low- and middle-income countries (LMICs), despite being largely preventable through vaccination and screening. This review examines innovative approaches to address screening coverage gaps worldwide, analysing both established programmes in high-income countries and implementation strategies for LMICs. Self-sampling technologies demonstrate significant potential to improve the uptake of cervical screening, thereby improving cervical cancer prevention compared to traditional methods, particularly benefiting underserved populations across all healthcare settings. Among self-collection devices, vaginal brushes achieve sensitivity of 94.6% (95% CI: 92.4-96.8) for HPV detection, while novel approaches like the tampon show promising results (sensitivity 82.9-100%, specificity 91.6-96.8%) with high user acceptability. Implementation strategies vary by healthcare context, with high-income countries achieving success through integrated screening programmes and digital solutions, while LMICs demonstrate effective adaptation through community-based distribution (20-35% uptake) and innovative delivery methods. In resource-limited settings, self-sampling increases participation through enhanced patient comfort and cultural acceptability, while reducing costs by 32-48%. Progress toward WHO's cervical cancer elimination goals require careful consideration of local healthcare infrastructure, cultural contexts and sustainable financing mechanisms. Future research priorities include optimising self-sampling technologies for sustainability and scalability, developing context-specific implementation strategies and validating artificial intelligence applications to enhance screening efficiency across diverse healthcare settings.
宫颈癌每年导致35万人死亡,其中90%发生在低收入和中等收入国家(LMICs),尽管通过疫苗接种和筛查在很大程度上是可以预防的。本综述探讨了解决全球筛查覆盖差距的创新方法,分析了高收入国家的既定项目以及低收入和中等收入国家的实施策略。与传统方法相比,自我采样技术在提高宫颈癌筛查的接受率方面具有巨大潜力,从而改善宫颈癌的预防效果,尤其使所有医疗环境中服务不足的人群受益。在自我采集设备中,阴道刷检测HPV的灵敏度达到94.6%(95%置信区间:92.4 - 96.8%),而像卫生棉条这样的新方法显示出有前景的结果(灵敏度82.9 - 100%,特异性91.6 - 96.8%),且用户接受度高。实施策略因医疗环境而异,高收入国家通过综合筛查项目和数字解决方案取得成功,而低收入和中等收入国家则通过基于社区的分发(接受率20 - 35%)和创新的递送方法实现了有效的调整。在资源有限的环境中,自我采样通过提高患者舒适度和文化接受度增加了参与度,同时成本降低了32 - 48%。要实现世界卫生组织消除宫颈癌的目标,需要仔细考虑当地的医疗基础设施、文化背景和可持续融资机制。未来的研究重点包括优化自我采样技术以实现可持续性和可扩展性,制定针对具体情况的实施策略,以及验证人工智能应用以提高不同医疗环境中的筛查效率。