Molecular Pathology Laboratory, Department of Pathology, Copenhagen University, Hvidovre Hospital, Hvidovre, Denmark.
Laboratory Medicine Division, European Institute of Oncology, Milan, Italy.
Int J Cancer. 2019 Aug 15;145(4):1033-1041. doi: 10.1002/ijc.32291. Epub 2019 Apr 30.
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.
虽然 HPV16 和 HPV18 一直是当前基于 HPV 基因型信息的宫颈癌风险筛查算法的重点,但越来越多的证据表明,致癌 HPV 型如 HPV31、33、52 和 58 造成的 CIN3 风险等同于或大于 HPV18,而 HPV31 和 HPV33 的联合风险在 30 岁以上的女性中甚至可与 HPV16 相媲美。在这里,我们评估了丹麦和意大利阴道镜转诊人群中基于基因型的 CIN2 和 CIN3 的基线风险。共有 655 名女性在阳性筛查样本后因阴道镜转诊而被纳入研究。所有样本均使用 Onclarity HPV 检测进行 HPV 分析,具有扩展的基因分型,并与组织学结果相结合,使用贝叶斯概率模型确定每种基因型的风险评估。该转诊人群的综合数据显示 HPV16 的 ≥CIN2 风险为 69.1%,HPV31 为 63.3%,HPV33/58 为 52.7%,HPV18 为 46.6%,HPV52 为 40.8%。对于 ≥CIN3,HPV16、HPV31、HPV18、HPV33/58 和 HPV52 的风险分别为 44.3%、38.5%、36.8%、30.9%和 16.8%,这表明 HPV16 致癌 HPV 基因型中疾病的基线风险最高,这并不奇怪。我们发现 HPV 基因型特异性的 ≥CIN2 和 ≥CIN3 风险模式差异如此明显,例如,35/39/68 和 56/59/66 仅应作为低强度随访的指征,因此建议在 HPV 阳性女性的筛查中积极使用这些信息进行分类策略。