Modeling HPV Self-Sampling Impact on Cervical Cancer in East African Immigrants.

Introduction: Cervical cancer screening uptake among East African immigrants in the U.S. is low. Offering self-collected samples for human papillomavirus (HPV) testing increases screening coverage among underserved populations, but the potential impact on cervical cancer incidence and mortality is understudied.

Methods: A Markov cohort state-transition model was used to predict the impact of primary HPV screening with self-sampling on cervical cancer incidence and mortality among East African immigrant women in Washington state. The model estimated cervical cancer cases and deaths for a hypothetical cohort from ages 25 to 80 years under alternative screening, diagnostic colposcopy and treatment scenarios. Base case scenarios compared primary HPV testing by clinician-sampling exclusively (standard of care) with self-sampling exclusively, assuming higher screening coverage (70% vs 63%) but lower colposcopy adherence with self-sampling (67% vs 83%) with equal treatment coverage of 85%, based on Washington state patient data. Sensitivity analyses with varied coverages, and also the combinations of the 2 strategies were evaluated. The model was developed and fitted between 2022 and 2024.

Results: In the base case scenario, an exclusive self-sampling strategy results in 4% higher cervical cancer incidence and mortality compared to the standard of care. Self-sampling results in lower cancer incidence and mortality if colposcopy adherence is raised to the level of the standard of care and/or if coverage is increased beyond 90%. In scenarios combining clinician- with self-sampling, the benefits of reaching more women with self-sampling are attenuated if more than 34% of screening is done by self-sampling.

Conclusions: Self-sampling has the potential to improve cervical cancer prevention for underserved populations. The impact of the strategy can be enhanced with stronger linkage to follow-up care.