Investigator
Erasmus Mc
Under which realistic circumstances is hrHPV self‐sampling increasing cervical screening effectiveness in a partly vaccinated population? A modelling study
Abstract High‐risk Human Papillomavirus self‐sampling can increase attendance rates for screening. However, observed lower sensitivity and loss to follow‐up of self‐sampling could reduce programme effectiveness when attenders of clinician‐collected sampling switch to self‐sampling. We determined the tipping point for effectiveness (based on life years gained [LYG]) of self‐sampling and the consequences for cost‐effectiveness, taking into account waste by comparing full opt‐out (no waste) to no opt‐out (waste from unused self‐sampling kits). We used the STDSIM‐MISCAN‐Cervix microsimulation model to simulate a population of Dutch women born in 2000 (50% vaccinated [sensitivity analysis: 0–100%], 70% screening attendance [sensitivity analysis: 60–80%]). Self‐sampling deployment strategies (e.g., direct‐mail) were varied by the percentage of original attenders switching to self‐sampling and the percentage of new attendance from non‐attenders. Main outcome measures were LYG and cost‐effectiveness (cost per quality adjusted [QA] LY gained) compared to the current programme. We found that if self‐sampling does not reach non‐attenders, life years cannot be gained. When reaching 10% or 30% of non‐attenders, the tipping point lies at ≤40% and ≤100% switchers to maintain effectiveness, respectively (+4 LYG, +10 LYG). Scenarios were cost‐effective (<€50,000/QALY gained) if at least 10% of non‐attenders were reached. Full opt‐out improved cost‐effectiveness substantially. So, in a partly vaccinated population, self‐sampling deployment strategies need to reach at least 10% of non‐attenders to maintain programme effectiveness and cost‐effectiveness. A well‐functioning opt‐out system further improves cost‐effectiveness by preventing waste.
Disparities in cervical cancer elimination time frames in the United States: a comparative modeling study
Abstract Population-level estimates in time frames for reaching cervical cancer elimination (ie, &lt;4 cases per 100 000 women) in the United States may mask potential disparities in achieving elimination among subpopulations. We used 3 independent Cancer Intervention and Surveillance Modeling Network models to estimate differences in the time to cervical cancer elimination across 7 strata of correlated screening and human papillomavirus vaccination uptake, based on national survey data. Compared with the average population, elimination was achieved at least 22 years earlier for the high-uptake strata and at least 27 years later for the most extreme low-uptake strata. Accounting for correlated uptake impacted the population average time frame by no more than 1 year. Consequently, national average elimination time frames mask substantial disparities in reaching elimination among subpopulations. Addressing inequalities in cervical cancer control could shorten elimination time frames and would ensure more equitable elimination across populations. Furthermore, country-level elimination monitoring could be supplemented by monitoring progress in subpopulations.
