Comparative Modeling to Inform Cervical Cancer Control Policies

项目摘要/摘要 宫颈癌预防和治疗的进展导致发病率大幅下降和 美国过去二十年的死亡率。然而，即使总体利率有所改善，布莱克 与白人女性相比，女性在宫颈癌发病率、远程诊断和 死亡率。造成这些持续差异的原因是多方面的，很可能是由相加故障引起的 癌症护理连续体，包括易感危险因素患病率增加，接受癌症治疗的人数减少 建议进行宫颈癌筛查，并在诊断出异常情况后延误接受治疗。 为了在改善癌症护理公平方面取得进展，至关重要的是划定种族的决定因素。 宫颈癌发病率和死亡率的差异，作为确定可行、有效和 高价值的干预措施。 我们建议改编哈佛大学陈冯富珍的宫颈癌模型，目前默认的模型是“所有种族”(即人口 平均)，以反映疾病负担以及筛查和疫苗接种做法的变化 在美国黑人女性中，这是一种模式。 我们将通过更新关键的人口统计输入参数来适应所有种族的宫颈癌模型，以反映黑人 美国女性的全因死亡率和子宫切除率。然后，我们将使用我们的 黑人特定宫颈癌模型，以确定宫颈癌发病率差异的主要因素 和死亡率。具体地说，我们将首先更改每个主要参数类别中的值 (即自然病史、筛查实践模式、治疗模式)从所有种族的价值观到 特定于黑色的校准值，以了解每个参数块在解释 发病率和死亡率的差异。最后，我们将使用调整后的模型来检查 旨在缓解宫颈癌差异的干预措施。 这项由哈佛大学建模网站领导的工作将为相互之间的比较建模奠定基础 四个CISNET-宫颈建模站点，以及支持在以下领域的其他CISNET癌症站点之间的协作 确定战略，以减少美国人口中黑人个体的总体癌症差异。

Project Summary/Abstract Advances in cervical cancer prevention and treatment have resulted in substantial reductions in incidence and mortality in the United States (US) over the past twenty years. However, even as overall rates improve, Black women remain at higher risk than White women for cervical cancer incidence, diagnosis at distant stage, and mortality. Reasons for these persistent disparities are multifactorial, likely resulting from additive failures along the cancer care continuum, including increased prevalence of predisposing risk factors, lower receipt of recommended cervical cancer screening, and delays in receipt of treatment after abnormalities are diagnosed. To make progress in improving cancer care equity, it is essential to delineate the determinants of racial disparities in cervical cancer incidence and mortality as a first step towards identifying feasible, effective, and high-value interventions. We propose to adapt the Harvard Chan’s cervical cancer model current default “all race” (i.e., population average) to reflect variations in the disease burden, as well as both screening and vaccination practice patterns, among Black women in the US. We will adapt an all-race cervical cancer model by updating key demographic input parameters to reflect Black women in the US, such as all-cause mortality and hysterectomy rates. We then will perform analyses using our Black-specific cervical cancer model to identify the main contributors to disparities in cervical cancer incidence and mortality. Specifically, we will start by changing the values in each of the main categories of parameters (i.e., natural history, screening practice patterns, treatment patterns) sequentially from the all-race values to the Black-specific calibrated values to understand how influential each block of parameters is in explaining the differences in incidence and mortality. Finally, we will use the adapted model to examine the potential for interventions to alleviate cervical cancer disparities. This work, led by the Harvard modeling site, will lay the groundwork for comparative modeling across the other four CISNET-Cervical modeling sites, as well as enable collaboration across the other CISNET cancer sites in identifying strategies to reduce overall cancer disparities among Black individuals in the US population.