Using comparative effectiveness analyses to optimize cervical cancer screening

描述（由申请人提供）：随着致癌性人乳头瘤病毒（HPV）类型和类型特异性HPV疫苗检测的引入，在过去十年中，美国预防宫颈癌的潜在策略已大大扩展。多个选项带来了复杂性，确定如何最大限度地提高筛查效益并最大限度地减少危害（包括资源投入）已成为一个巨大的挑战。例如，比较HPV DNA检测与细胞学检查的随机试验的初步结果表明，HPV检测比细胞学检查具有更高的灵敏度（检测更多的宫颈肿瘤病例）和更低的特异性（至少使阳性检测的数量增加一倍）。考虑到大多数宫颈癌发生在从未接受过筛查或筛查不足的女性中，与每年约8000万处于风险中的女性相比，接受过筛查的美国女性的潜在可预防负担相对较小（n~5000）。虽然筛查的好处可以通过在一生中越来越频繁地进行更敏感的测试来最大化，但这种策略的危害会大大增加，特别是在健康女性中。衡量危害具有挑战性，因为它们可以采取多种形式，包括假阳性测试，导致不必要的干预，伴随着副作用，生活中断和其他与健康相关的生活质量的潜在下降。为了充分了解筛查危害的程度和影响，需要妇女的观点和偏好。最大化利益和最小化危害的一种方法是通过个体风险因素评估进行个性化筛查。例如，HPV疫苗接种似乎可以降低宫颈肿瘤的风险;因此，继续以与未接种疫苗的妇女相同的警惕性筛查接种疫苗的妇女可能会加剧筛查的危害。此外，每年对免疫功能低下的妇女进行筛查（例如，艾滋病毒感染）已经推荐了十多年，尽管目前还不清楚这种方法是否适当地平衡了利益和危害。确定如何最佳地使用新的测试（单独或组合），以及是否应该在女性亚组中考虑“个性化”方法（例如，如果我们仅仅依靠随机试验的话，接种疫苗，免疫功能低下）将仍然是困难的，如果不是不可能的话。另一种方法是使用决策分析模型和比较有效性分析，以确定提供类似获益和危害（或改善获益/危害平衡）的新策略。定义宫颈癌筛查的“合理选择范围”以及这些选择如何因个体风险因素而变化，将立即有用并合成医学研究所定义的比较有效性研究的核心目标：确定哪种策略最有效，为谁工作，在什么情况下。目前的研究将使用最先进的方法来解决宫颈癌预防的这个问题。

DESCRIPTION (provided by applicant): With the introduction of tests for oncogenic human papillomavirus (HPV) types and type-specific HPV vaccines, potential strategies for cervical cancer prevention in the US have expanded tremendously over the last decade. With multiple options has come complexity, and determining how best to maximize screening benefits and minimize harms (including resource inputs) has become a great challenge. As an example, preliminary results from randomized trials comparing HPV DNA tests to cytology indicate that HPV testing has a higher sensitivity (detects more cases of cervical neoplasia) than cytology and a lower specificity (at least doubling the number of positive tests). Given that most cervical cancer occurs among never- and inadequately-screened women, the potential preventable burden among screened US women is relatively small (n~5000) compared to the approximately 80 million women at risk per year. While screening benefits can be maximized by apply more sensitive tests at increasingly frequent intervals over a lifetime, harms increase substantially with such strategies, especially among healthy women. Measuring harms is challenging since they can take many forms including false-positive tests that lead to unnecessary interventions with concomitant side effects, life disruptions and other potential decrements in health-related quality of life. To fully capture the magnitude and effect of screening harms, the perspectives and preferences of women are needed. One approach to maximizing benefits and minimizing harms is to personalize screening by individual risk factor assessment. For example, HPV vaccination appears to lower risk of cervical neoplasia; continuing to screen vaccinated women with the same vigilance as unvaccinated women, therefore, may exacerbate screening harms. Further, annual screening of immunocompromised women (e.g., HIV infection) has been recommended for over a decade, though it is unclear if such an approach appropriately balances benefits and harms. Determining how to optimally use new tests (singly or in combination) and whether "personalized" approaches should be considered in subgroups of women (e.g., vaccinated, immunocompromised) will remain difficult, if not impossible, if we are to rely solely on randomized trials. An alternative approach is using decision analytic models and comparative effectiveness analyses to identify novel strategies that provide similar benefits and harms (or an improved benefit/harm balance). Defining a "range of reasonable options" for cervical cancer screening and how these might vary by individual risk factors, would be immediately useful and synthetic to the core goal of comparative effectiveness research as defined by the Institute of Medicine: determining which strategy works best, for whom, and under what circumstances. The current study will address this question for cervical cancer prevention using state-of-the-art methodology.