Inge M. C. M. de Kok

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.

State-level disparities in cervical cancer prevention and outcomes in the United States: a modeling study

Abstract Background Despite human papillomavirus (HPV) vaccines’ availability for over a decade, coverage across the United States varies. Although some states have tried to increase HPV vaccination coverage, most model-based analyses focus on national impacts. We evaluated hypothetical changes in HPV vaccination coverage at the national and state levels for California, New York, and Texas using a mathematical model. Methods We developed a new mathematical model of HPV transmission and cervical cancer, creating national- and state-level models, incorporating country- and state-specific vaccination coverage and cervical cancer incidence and mortality. We quantified the national- and state-level impact of increasing HPV vaccination coverage to 80% by 2025 or 2030 on cervical cancer outcomes and the time to elimination defined as less than 4 per 100 000 women. Results Increasing vaccination coverage to 80% in Texas over 10 years could reduce cervical cancer incidence by 50.9% (95% credible interval [CrI] = 46.6%-56.1%) by 2100, from 1.58 (CrI = 1.19-2.09) to 0.78 (CrI = 0.57-1.02) per 100 000 women. Similarly, New York could see a 27.3% (CrI = 23.9%-31.5%) reduction from 1.43 (CrI = 0.93-2.07) to 1.04 (CrI = 0.66-1.53) per 100 000 women, and California a 24.4% (CrI = 20.0%-30.0%) reduction from 1.01 (CrI = 0.66-1.44) to 0.76 (CrI = 0.50-1.09) per 100 000 women. Achieving 80% coverage in 5 years will provide slightly larger and sooner reductions. If the vaccination coverage levels in 2019 continue, cervical cancer elimination could occur nationally by 2051 (CrI = 2034-2064), but state timelines may vary by decades. Conclusion Targeting an HPV vaccination coverage of 80% by 2030 will disproportionately benefit states with low coverage and higher cervical cancer incidence. Geographically focused analyses can better inform priorities.

Should the age range of the Dutch hrHPV‐based cervical cancer screening program be broadened? A modelling study using cohort effects

AbstractIn the Netherlands, women are invited for human papillomavirus (HPV) screening between the ages of 30 and 60 (with conditional screening at age 65). However, an increase in cervical cancer (CC) incidence has been observed in younger women recently. Meanwhile, HPV‐vaccinated cohorts reached the screening age of 30 in 2023. Moreover, increasing healthy life expectancy is a consideration for screening in older age groups. Due to these developments, the starting and ending ages of the HPV screening programs should be reconsidered. Microsimulation model MISCAN‐Cervix was recalibrated for cohort effects using updated CC incidence data. We used this model to calculate the cost‐effectiveness of screening unvaccinated women in birth cohorts 1962–1992 until 65 years old. Additionally, we considered starting screening at 25 for partly vaccinated cohorts (born in 2002–2006). Vaccination effects were calculated using microsimulation model STDSIM. Main outcome measures included cancers prevented, life years gained (LYG), costs, and referrals compared to the current strategy (2027 onwards). Adding screening at age 65 to the current strategy leads to +3.5% cancers prevented, +10.3% referrals, +2.4% LYG and +57.0% costs (cost‐effectiveness ratio: €275,096/LYG). Adding screening at age 25 results in extra cases prevented (+1.3%–5.7%, depending on the target group's vaccination status) and LYG (+0.8%–3.7%), but increases referrals (12.9%–37.1%) and costs (+14.0%–33.1%) (cost‐effectiveness ratio: €120,017–€323,813/LYG). So, screening unvaccinated women at 65 years old and screening women in (partly‐)vaccinated cohorts at age 25 might not represent good value for money.

Optimizing the Harms and Benefits of Cervical Screening in a Partially Vaccinated Population in Ontario, Canada: A Modeling Study

Objectives In Ontario, Canada, the first cohorts who were offered school-based human papillomavirus (HPV) vaccination are now eligible for cervical screening. We determined which screening strategies for these populations would result in optimal harms–benefits ratios of screening. Methods We used the hybrid microsimulation model STDSIM- MISCAN-Cervix to determine the harms and cancers prevented of 309 different primary HPV screening strategies, varying by screening ages and triage methods. In addition, we performed an unstratified (i.e., uniform screening protocols) and stratified (i.e., screening protocols by vaccination status) analysis. Harms induced were quantified as a weighted combination of the number of primary HPV-based screens and colposcopy referrals at 1:10. A harms–benefit acceptability threshold of number of harms induced for each cancer prevented was set at the estimated ratio under current screening recommendations in unvaccinated cohorts in Ontario. Results For the unstratified scenario, 5 lifetime screens with HPV16/18 genotyping was optimal. For the stratified scenario, the optimal scenario was 3 lifetime screens with HPV16/18/31/33/45/52/58 genotyping for vaccinated individuals versus 6 lifetime screens with HPV16/18 genotyping for unvaccinated individuals. Conclusions We determined the optimal cervical screening strategy in Ontario over the next decades. To maintain an optimal harms–benefits balance of screening, the Ontario Cervical Screening Program could adjust screening recommendations in the future to reduce the number of lifetime screens and extend screening intervals to account for vaccinated cohorts. Stratified screening by vaccination status could further improve this balance on an individual level. Highlights People in cohorts who were offered HPV vaccination as part of Ontario’s school-based program may achieve a better harms–benefits balance if cervical screening recommendations are updated to a less intensive protocol in future. This holds for the cohorts as a whole (i.e., unstratified screening) as well as for both vaccinated and unvaccinated individuals in these cohorts. Instead of using a cost-effectiveness threshold, it is possible to determine optimal screening protocols by calculating an acceptability threshold using alternative harms–benefits measures based on existing policy. Using univariate harms measures such as primary HPV screening tests or colposcopies per 1,000 people can yield biases in optimizing cervical screening programs. Alternatively, combining both primary screens and colposcopy referrals could provide a more accurate harms measure and result in optimal strategies with a better balance between harms and benefits.

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, <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.

The impact of loss to follow‐up in the Dutch organised HPV‐based cervical cancer screening programme

AbstractLoss to follow‐up (LTFU) within cervical screening programmes can result in missed clinically relevant lesions, potentially reducing programme effectiveness. To examine the health impact of losing women during the screening process, we determined the proportion of women LTFU per step of the Dutch hrHPV‐based screening programme. We then determined the probability of being LTFU by age, screening history and sampling method (self‐ or clinician‐sampled) using logistic regression analysis. Finally, we estimated the number of missed CIN2+/3+ lesions per LTFU moment by using the CIN‐risk in women compliant with follow‐up. Data from the Dutch nationwide pathology databank (Palga) was used. Women eligible for screening in 2017 and 2018 were included (N = 840,428). For clinician collected (CC) samples, the highest proportion LTFU was found following ‘referral advice for colposcopy’ (5.5% after indirect referral; 3.8% after direct referral). For self‐sampling, the highest proportions LTFU were found following the advice for repeat cytology (13.6%) and after referral advice for colposcopy (8.2% after indirect referral; 4.3% after direct referral). Self‐sampling users and women with no screening history had a higher LTFU‐risk (OR: 3.87, CI: 3.55–4.23; OR: 1.39, CI: 1.20–1.61) compared to women that used CC sampling and women that have been screened before, respectively. Of all women LTFU in 2017/18, the total number of potentially missed CIN2+ was 844 (21% of women LTFU). Most lesions were missed after ‘direct referral for colposcopy’ (N = 462, 11.5% of women LTFU). So, this indicates a gap between the screening programme and clinical care which requires further attention, by improving monitoring of patients after referral.

Cost‐effectiveness of HPV‐based cervical screening based on first year results in the Netherlands: a modelling study

ObjectiveWe aim to compare the cost‐effectiveness of the old cytology programme with the new high‐risk human papillomavirus (hrHPV) screening programme, using performance indicators from the new Dutch hrHPV screening programme.DesignModel‐based cost‐effectiveness analysis.SettingThe Netherlands.PopulationDutch 30‐year‐old unvaccinated females followed up lifelong.MethodsWe updated the microsimulation screening analysis (MISCAN) model using the most recent epidemiological and screening data from the Netherlands. We simulated both screening programmes, using the screening behaviour and costs observed in each programme. Sensitivity analyses were performed on screening behaviour, utility losses and discount rates.Main outcome measuresCervical cancer incidence and mortality rates, number of screening tests and repeat tests, colposcopy referrals by lesion grade, costs from a societal perspective, quality‐adjusted life years (QALYs) gained and cost‐effectiveness.ResultsThe new Dutch cervical cancer screening programme decreased the cervical cancer mortality by 4% and the incidence by 1% compared with the old programme. Colposcopy referrals of women without cervical intra‐epithelial neoplasia grade 2 or worse, increased by 172%, but 13% more QALYs were still achieved. Total costs were reduced by 21%, mainly due to fewer screening tests. Per QALY gained, the hrHPV programme cost 46% less (€12,225) than the cytology programme (€22,678), and hrHPV‐based screening remained more cost‐effective in all sensitivity analyses.ConclusionsThe hrHPV‐based screening programme was found to be more effective and cost‐effective than the cytology programme. Alternatives for the current triage strategy should be considered to lower the number of unnecessary referrals.Tweetable abstractFirst results after implementation confirm that HPV screening is more cost‐effective than cytology screening.

The Impact of Different Screening Model Structures on Cervical Cancer Incidence and Mortality Predictions: The Maximum Clinical Incidence Reduction (MCLIR) Methodology

Background. To interpret cervical cancer screening model results, we need to understand the influence of model structure and assumptions on cancer incidence and mortality predictions. Cervical cancer cases and deaths following screening can be attributed to 1) (precancerous or cancerous) disease that occurred after screening, 2) disease that was present but not screen detected, or 3) disease that was screen detected but not successfully treated. We examined the relative contributions of each of these using 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models. Methods. The maximum clinical incidence reduction (MCLIR) method compares changes in the number of clinically detected cervical cancers and mortality among 4 scenarios: 1) no screening, 2) one-time perfect screening at age 45 that detects all existing disease and delivers perfect (i.e., 100% effective) treatment of all screen-detected disease, 3) one-time realistic-sensitivity cytological screening and perfect treatment of all screen-detected disease, and 4) one-time realistic-sensitivity cytological screening and realistic-effectiveness treatment of all screen-detected disease. Results. Predicted incidence reductions ranged from 55% to 74%, and mortality reduction ranged from 56% to 62% within 15 years of follow-up for scenario 4 across models. The proportion of deaths due to disease not detected by screening differed across the models (21%–35%), as did the failure of treatment (8%–16%) and disease occurring after screening (from 1%–6%). Conclusions. The MCLIR approach aids in the interpretation of variability across model results. We showed that the reasons why screening failed to prevent cancers and deaths differed between the models. This likely reflects uncertainty about unobservable model inputs and structures; the impact of this uncertainty on policy conclusions should be examined via comparing findings from different well-calibrated and validated model platforms.

Shift in harms and benefits of cervical cancer screening in the era of HPV screening and vaccination: a modelling study

AbstractObjectiveTo calculate the changes in harms and benefits of cervical cancer screening over the first three screening rounds of the Dutch high‐risk human papillomavirus (hrHPV) screening programme.DesignMicrosimulation study.SettingDutch hrHPV screening programme; women are invited for screening every 5 or 10 years (depending on age and screening history) from age 30 to 65.PopulationPartly vaccinated population of 100 million Dutch women.MethodsMicrosimulation model MISCAN was used to estimate screening effects. Sensitivity analyses were performed on test characteristics and attendance.Main outcome measuresHarms (screening tests, unnecessary referrals, treatment‐related health problems), benefits (CIN2+ diagnoses) and programme efficiency (number needed to screen [NNS]) over the first (period 2017–2021), second (period 2022–2026) and third (period 2027–2031) rounds of hrHPV‐based screening.ResultsThe number of screening tests and CIN2+ diagnoses decreased from the first to the second round (−25.8% and −23.6%, respectively). In the third screening round, these numbers decreased further, albeit only slightly (−2.7% and −5.3%, respectively). NNS to detect a CIN2+ remained constant over the rounds; however, it increased in younger age groups while decreasing in older age groups.ConclusionBoth harms and benefits of hrHPV screening decreased over the first screening rounds. For younger women, the efficiency would decrease, whereas longer screening intervals would lead to increased efficiency in older women. Programme efficiency overall remained stable, showing the importance of longer intervals for low‐risk women.Tweetable abstract:Cervical cancer screening: both harms and benefits of hrHPV screening will decrease in the future.

Long-term cervical cancer risk following negative hrHPV-based versus negative cytology-based screening: A population-based study

Randomized trials have shown that hrHPV-testing provides better protection against cervical cancer than cytology. However, long-term assessment of programme sensitivity remains essential. In the Netherlands, hrHPV-screening replaced cytology in 2017. We estimated the long-term cervical cancer risk following negative results in hrHPV- versus cytology-based screening. Screening and histology data from the nationwide Dutch pathology databank (Palga) were used to identify 469,116 women without referral in 2014 (cytology-based) and 362,128 in 2017 (hrHPV-based), representing 4,071,690 person-years. Cervical cancer risk following non-referral, including interval cancers (IC) and those detected in the next screening round were analysed. The incidence rate per 100,000 person-years was 3.3 IC following non-referral in cytology-based versus 2.7 following non-referral in hrHPV-based screening. Including next-round cancers, these numbers increase to 5.7 and 4.5. HrHPV-test negative women had a 50 % lower IC risk compared to those with normal cytology (HR 0.5; 95 % CI: 0.3-0.8), and 60 % lower when including next-round cancers (HR 0.4; 95 % CI: 0.3-0.5). HrHPV-positive women without referral had the highest cancer risk: 24 IC per 100,000 person-years, rising to 45 when including next-round cancers. Their risk was 3.4 times higher than for women with positive primary cytology without referral (HR: 3.4; 95 % CI: 1.1-8.1 for IC and HR: 3.4; 95 % CI: 1.4-8.1 including next-round cancers). A negative hrHPV test was linked to lower long-term risk of cervical cancer than normal cytology, supporting longer screening intervals for hrHPV-negative women. However, hrHPV-positivity with negative cytology was associated with increased risk, suggesting the possible need for alternative triage guidelines.