Work

Performance evaluation of artificial intelligence–assisted diagnostic tools for human papillomavirus–related cervical and anal cancers and their precancerous lesions: A systematic review and meta-analysis

Year: 2025

Type: review

Abstract: Detection of high-grade squamous intraepithelial lesions (HSILs) is key for the prevention of human papillomavirus (HPV)–related cancers. In this study, we aimed to identify and consolidate the existing evidence on the diagnostic performances of artificial intelligence (AI)–assisted tools for HPV-related HSILs. We followed the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy guidelines and systematically searched PubMed, Embase, Web of Science, IEEE, and the Cochrane Library for eligible studies published between 2000 and January 2024. Studies on AI-assisted colposcopy used to facilitate the diagnosis of cervical or anal HSILs and cancers were included. The revised Quality Assessment of Diagnostic Studies 2 and AI checklists were used to assess the risk of bias. With random-effect models, meta-analyses were performed on performance indicators, including accuracy, sensitivity, specificity, and area under the receiver-operating characteristic (AUC) curves. Subgroup and meta-regression analyses were performed to identify the sources of heterogeneity. Twenty-five studies, comprising 21 studies focused on cervical cancer and 4 on anal cancer, were included in the meta-analysis. When differentiating from individuals with 90%), but the meta-regression analysis did not reveal any significant contributing sources of heterogeneity. Based on this systematic review of existing literature, we concluded that AI-assisted diagnostic tools have demonstrated promising predictive performance in diagnosing HPV-related cervical and anal precancerous lesions and cancers.

Source: Intelligent Oncology

DOI: 10.1016/j.intonc.2025.10.002