Cost-benefit analysis of p16(INK4a) immunocytology and liquid-based cytology triage after primary HPV testing for cervical cancer screening in China

在中国宫颈癌筛查中,初筛HPV检测后p16(INK4a)免疫细胞学和液基细胞学分流的成本效益分析

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Abstract

BACKGROUND: HPV testing has become the recommended primary screening method for cervical cancer in China. However, referring all HPV-positive patients for colposcopy is not practical. This study monetized clinical performance metrics to evaluate the relative performance of 10 secondary triage strategies compared to referring all patients for colposcopy. METHODS: Using real-world HR-HPV sample data and strictly adhering to the HPV-FRAMEWORK, a Markov model was employed to simulate the missed diagnosis losses and health utility losses associated with referring all patients for colposcopy. These losses were monetized using one-time 2023 per capita GDP in China. Incremental net benefits of secondary triage strategies were calculated to identify the optimal strategy. Extensive sensitivity analyses were conducted to assess parameter and sample uncertainty. Additionally, the technical suitability of strategies was explored in the context of healthcare resource allocation in China. RESULTS: Solely relying on HPV genotyping for secondary triage is not recommended, and necessary secondary triage testing should be implemented. p16 performed better than LBC, particularly in the overall sample and in most age groups. The strategy of HPV16/18+ or (OH-HPV+ and p16+) was the most attractive, with an incremental net benefit of US$492,473.78 compared to referring all patients for colposcopy. Extensive sensitivity analyses confirmed the robustness of these results. Considering healthcare resource allocation in China, p16 demonstrated higher technical suitability. CONCLUSION: Based on real-world sample data and the monetization of clinical performance metrics, this study recommends p16 as the secondary triage technology. The HPV16/18+ or (OH-HPV+ and p16+) strategy is not only the most attractive but also holds high potential for large-scale implementation in China.

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