Evidence map›Paper›PMID 37283979›Full record

ArticleThe Lancet regional health. Western Pacific2023

Cost-effectiveness of artificial intelligence-assisted liquid-based cytology testing for cervical cancer screening in China.

Mingwang Shen, Zhuoru Zou, Heling Bao, Christopher K Fairley, Karen Canfell, Jason J Ong, Jane Hocking, Eric P F Chow, Guihua Zhuang, Linhong Wang and 1 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  13. Cost-benefit analysis of p16Infectious agents and cancer · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Mingwang ShenChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China.
Zhuoru ZouChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China.
Heling BaoInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Christopher K FairleyChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China.
Karen CanfellCancer Research Division, Cancer Council NSW, 153 Dowling Street, Woolloomooloo, Sydney, NSW 2011, Australia.
Jason J OngChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China.
Jane HockingChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China.
Eric P F ChowMelbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia.
Guihua ZhuangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China.
Linhong WangNational Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Lei ZhangChina-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AI-assisted LBCCervical cancer screeningCost-effectivenessHPV DNA testingManual LBC

Identifiers

PMID37283979
PMCPMC10240360

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.