||4R01CA169093-04 Interpret this number
||University Of California, San Francisco
||Using Comparative Effectiveness Analyses to Optimize Cervical Cancer Screening
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.