Back

Direct mailing of HPV self-sampling kits to older women non-participating in cervical screening in the Czech Republic

Ngo, O.; Chloupkova, R.; Cibula, D.; Slama, J.; Mandelova, L.; Hejduk, K.; Hajduch, M.; Minka, P.; Koudelakova, V.; Jaworek, H.; Trnkova, M.; Vanek, P.; Dvorak, V.; Dusek, L.; Majek, O.

2023-10-05 oncology
10.1101/2023.10.05.23296387 medRxiv
Show abstract

BackgroundA population-based cervical cancer screening programme is implemented in the Czech Republic. However, participation is insufficient among women over 50 years. This study aimed to estimate the potential improvement in participation through directly mailed HPV self-sampling kits (HPVssk) compared to standard invitation letters in women aged 50-65 non-participating in screening. MethodsThe study recruited 1,564 eligible women (no cervical cancer screening in the last 3 years or more, no previous treatment associated with cervical lesions or cervical cancer). Eight hundred women were mailed with an HPVssk (HPVssk group), and 764 women were sent a standard invitation letter (control group) inviting them to a routine screening (Pap test). The primary outcome was a comparison of the overall participation rate between study groups using a binominal regression model. ResultsThe participation rate in the HPVssk group was 13.4% (95% CI 11.2-15.9%; 7.4% of women returned the HPVssk and 6.0% attended gynaecological examination) and 5.0% (95% CI 3.6-6.8%) in the control group. Using the binominal regression model, the difference between the groups was estimated as 7.6% (95% CI 5.0-10.2%; p < 0.001). In the HPVssk group, 22% of women who returned HPVssk had a positive result and 70% of them underwent a follow-up examination. ConclusionsCompared to traditional invitation letters, the direct mailing of the HPVssk achieved a significantly higher participation rate, along with a notable HPV positivity rate among HPVssk responders. This approach offers a potentially viable method for engaging women who have not yet attended a cervical screening programme.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.