ArticleThe Lancet regional health. Western Pacific2023
Cost-effectiveness of artificial intelligence-assisted liquid-based cytology testing for cervical cancer screening in China.
Article in The Lancet regional health. Western Pacific, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
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Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Economic evaluation of AI-assisted technologies in healthcare: A systematic review.Journal of food and drug analysis · 2025Pooled it
- Artificial intelligence-based risk assessment tools for sexual, reproductive and mental health: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Artificial intelligence in chronic kidney disease: Early detection, risk prediction, and personalized treatment strategies.World journal of nephrology · 2026Review
- Modelling the epidemic dynamics of HPV among women in China and optimization of ongoing cervical cancer elimination strategies.BMC medicine · 2026Article
- Health economics evaluation of artificial intelligence in the field of oncology: a scoping review.Health economics review · 2026Review
- Artificial intelligence for colposcopic and cytological image analysis in early cervical cancer detection.iScience · 2026Review
- Epidemiology and prevention of HPV-driven cervical cancer in urban-rural China: a population-based study of 60,280 women.Scientific reports · 2026Article
- The Role of Artificial Intelligence in Modern Medicine: Clinical Applications, Economic Implications, and Ethical Considerations.Current pharmaceutical design · 2026Review
- Leveraging AI and Natural Compounds: Innovative Approaches in the Diagnosis and Treatment of Hepatocellular Carcinoma.Current pharmaceutical design · 2026Review
- Artificial intelligence-driven screening, early diagnosis, and treatment strategies for cervical cancer: an overview.Infectious agents and cancer · 2025Review
- A novel non-invasive mRNA-lncRNA biomarker panel for accurate prediction of cervical squamous cell carcinoma and adenocarcinoma.Journal of gynecologic oncology · 2025Article
- Progress in the application research of cervical cancer screening developed by artificial intelligence in large populations.Discover oncology · 2025Review
- Cost-benefit analysis of p16Infectious agents and cancer · 2025Article
- Cost-effectiveness of population-based screening for chronic kidney disease among the general population and adults with diabetes in China: a modelling study.The Lancet regional health. Western Pacific · 2025Article
- Transforming cervical cancer pathological diagnosis through artificial intelligence: progress, performance, and barriers to clinical implementation.Frontiers in oncology · 2025Review
- Performance of a Full-Coverage Cervical Cancer Screening Program Using on an Artificial Intelligence- and Cloud-Based Diagnostic System: Observational Study of an Ultralarge Population.Journal of medical Internet research · 2024Observational
- Cost-Effectiveness of Computer-Assisted Cytology in a Primary hrHPV-Based Cervical Cancer Screening Programme.Cancer medicine · 2024Article
- Artificial intelligence strengthens cervical cancer screening - present and future.Cancer biology & medicine · 2024Review
- Evaluation of artificial intelligence-powered screening for sexually transmitted infections-related skin lesions using clinical images and metadata.BMC medicine · 2024Article
- Population impact and cost-effectiveness of artificial intelligence-based diabetic retinopathy screening in people living with diabetes in Australia: a cost effectiveness analysis.EClinicalMedicine · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The 2021 World Health Organization (WHO) guidelines for cervical cancer screening recommend human papillomavirus (HPV) DNA or mRNA testing. Artificial intelligence (AI)-assisted liquid-based cytology (LBC) systems also have the potential to facilitate rapid scale-up of cervical cancer screening. We aimed to evaluate the cost-effectiveness of AI-assisted LBC testing, compared with the manual LBC and HPV-DNA testing, for primary cervical cancer screening in China. Methods: We developed a Markov model for a cohort of 100,000 women aged 30 years over a lifetime to simulate the natural history of cervical cancer progression. We evaluated the incremental cost-effectiveness ratios (ICER) of 18 screening strategies (a combination of the three screening methods with six screening frequencies) from a healthcare provider's perspective. The willingness-to-pay threshold (US$30,828) was chosen as three times the Chinese per-capita gross domestic product in 2019. Univariate and probabilistic sensitivity analyses were performed to examine the robustness of the results. Findings: Compared with no screening, all 18 screening strategies were cost-effective, with an ICER of $622-24,482 per quality-adjusted life-year (QALY) gained. If HPV testing after scaling up to population level screening costs $10.80 or more, screening once every 5 years using AI-assisted LBC would be the most cost-effective strategy with an ICER of $8790/QALY gained compared with the lower-cost non-dominated strategy on the cost-effectiveness frontier. Its probability of being cost-effective was higher (55.4%) than other strategies. Sensitivity analyses showed that the most cost-effective strategy would become AI-assisted LBC testing once every 3 years if the sensitivity (74.1%) and specificity (95.6%) of this method were both reduced by ≥10%. The most cost-effective strategy would become HPV-DNA testing once every 5 years if the cost of AI-assisted LBC was more expensive than manual LBC or if the HPV-DNA test cost is slightly reduced (from $10.8 to <$9.4). Interpretation: AI-assisted LBC screening once every 5 years could be more cost-effective than manually-read LBC. Using AI-assisted LBC could have comparable cost-effectiveness to HPV DNA screening, but the relative pricing of HPV DNA testing is critical in this result. Funding: National Natural Science Foundation of China, National Key R&D Program of China.
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