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The Cost-Effectiveness of Cervical Self-Sampling to Improve Routine Cervical Cancer Screening: The Importance of Respondent Screening History and Compliance

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AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1055-9965.EPI-16-0350

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  1. Norwegian Research Council [238042]
  2. U.S. NCI of the NIH [R01CA160744]

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Background: Human papillomavirus (HPV) testing allows women to self-collect cervico-vaginal cells at home (i.e., self-sampling). Using primary data from a randomized pilot study, we evaluated the long-term consequences and cost-effectiveness of using self-sampling to improve participation to routine cervical cancer screening in Norway. Methods: We compared a strategy reflecting screening participation (using reminder letters) to strategies that involved mailing self-sampling device kits to women noncompliant to screening within a 5- or 10-year period under two scenarios: (A) self-sampling respondents had moderate under-screening histories, or (B) respondents to self-sampling had moderate and severe under-screening histories. Model outcomes included quality-adjusted life-years (QALY) and lifetime costs. The most cost-effective strategy was identified as the strategy just below $100,000 per QALY gained. Results: Mailing self-sampling device kits to all women noncompliant to screening within a 5-or 10-year period can be more effective and less costly than the current reminder letter policy; however, the optimal self-sampling strategy was dependent on the profile of self-sampling respondents. For example, 10-yearly self-sampling is preferred ($95,500 per QALY gained) if 5-yearly self-sampling could only attract moderate under-screeners; however, 5-yearly self-sampling is preferred if this strategy could additionally attract severe under-screeners. Conclusions: Targeted self-sampling of noncompliers likely represents good value-for-money; however, the preferred strategy is contingent on the screening histories and compliance of respondents. Impact: The magnitude of the health benefit and optimal self-sampling strategy is dependent on the profile and behavior of respondents. Health authorities should understand these factors prior to selecting and implementing a self-sampling policy. (C)2016 AACR.

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