Comparative Modeling to Inform Cervical Cancer Control Policies

项目摘要 尽管美国成功地进行了宫颈癌筛查，但仍有超过13,000名妇女和4,000名妇女 每年都有妇女死于宫颈癌。人类乳头瘤病毒(HPV)的发现是必要的 宫颈癌的病因催生了大量新的证据和创新的HPV基础研究 技术，包括筛查和预防性疫苗接种，使我们的 在过去的二十年里，我们一直致力于宫颈癌的控制。这些新技术代表着巨大的 在美国，有效、公平和高效的宫颈癌项目的机会也很重要 对决策的挑战。鉴于可用于新筛查和治疗的结果数据有限 疫苗接种方法从实证研究来看，政策制定者已经变得独特地依赖于数学 为宫颈癌控制策略的决策提供综合证据基础。 这些模型可以用来集成最新的数据，将短期结果外推到长期 结果，并评估在其他情况下不实际或不可行的假设情景 临床研究。拟议的信息和通信技术网络项目将代表五个国家继续进行富有成效的合作。 来自美国、澳大利亚和荷兰的独立模特团体将利用一系列国家- 用于比较建模的最先进的HPV和宫颈癌发生的数学模型。我们将继续追查 分析新修订的筛查和HPV疫苗接种指南的影响，比较 即将到来的筛查和HPV疫苗接种战略和方法的有效性， 减少宫颈癌的差距，美国消除宫颈癌的潜力，以及最佳 艾滋病毒携带者妇女的筛查和接种战略。我们的努力还将涉及广泛传播 将调查结果提供给各利益攸关方，以增加基于模型的分析的透明度和信心。

Project Summary Despite successful cervical cancer screening in the United States (US), over 13,000 women develop and 4,000 women die from cervical cancer each year. The discovery of human papillomavirus (HPV) as the necessary cause of cervical cancer precipitated a surge of new evidence and development of innovative HPV-based technologies, both screening and prophylactic vaccination, that have allowed for significant changes in our approach to cervical cancer control over the past two decades. These new technologies represent tremendous opportunities for effective, equitable, and efficient cervical cancer programs in the US but also pose significant challenges for decision-making. Given the limited availability of outcomes data for new screening and vaccination approaches from empirical studies, policy-makers have become uniquely reliant on mathematical modeling to provide a synthesized evidence base for decision-making for cervical cancer control strategies. These models can be used to integrate the most up-to-date data, extrapolate short-term findings into long-term outcomes, and evaluate what-if scenarios that would otherwise be impractical or infeasible to conduct in clinical studies. The proposed CISNET project will represent the continued, productive collaboration of five independent modeling groups from the US, Australia, and the Netherlands that will leverage a series of state- of-the-art mathematical models of HPV and cervical carcinogenesis for comparative modeling. We will pursue analyses related to the impact of newly-revised screening and HPV vaccination guidelines, the comparative effectiveness of forthcoming screening and HPV vaccination strategies and approaches, the optimal routes for reducing cervical cancer disparities, the potential for cervical cancer elimination in the US, and optimal screening and vaccination strategies in women living with HIV. Our efforts will also involve wide dissemination of findings to various stakeholders to increase transparency and confidence in model-based analyses.