Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort

Abstract

Whereas HPV16 and HPV18 have been the focus in current risk-based cervical cancer screening algorithms using HPV genotype information, mounting evidence suggests that oncogenic HPV types such as HPV31, 33, 52 and 58 pose a ≥CIN3 risk equivalent to or greater than that of HPV18, and the combined risk of HPV31 and HPV33 rivals even HPV16 in women above 30 years of age. Here, we evaluate the baseline risk of CIN2 and CIN3 by genotype in a colposcopy referral population from Denmark and Italy. In total, 655 women were enrolled upon a referral to colposcopy after a positive screening sample. All samples were HPV analyzed using Onclarity HPV assay with extended genotyping and combined with the histology outcomes, a Bayesian probability modeling was used to determine the risk per genotype assessed. The combined data for this referral population showed that the ≥CIN2 risk of HPV16 was 69.1%, HPV31 at 63.3%, HPV33/58 at 52.7%, HPV18 at 46.6% and HPV52 at 40.8%. For ≥CIN3, the risks were 44.3%, 38.5%, 36.8%, 30.9% and 16.8% for HPV16, HPV31, HPV18, HPV33/58 and HPV52, respectively, indicating that the baseline risk of disease arising from HPV16 is, not surprisingly, the highest among the oncogenic HPV genotypes. We find that the HPV genotype-specific ≥CIN2 and ≥CIN3 risk-patterns are so distinct that, for example, 35/39/68 and 56/59/66 should be considered only for low intensive follow-up, thereby proposing active use of this information in triage strategies for screening HPV-positive women.