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

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...

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Autores principales: Bonde, Jesper, Bottari, Fabio, Parvu, Valentin, Pedersen, Helle, Yanson, Karen, Iacobone, Anna D., Kodsi, Salma, Landoni, Fabio, Vaughan, Laurence, Ejegod, Ditte M., Sandri, Maria T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617734/
https://www.ncbi.nlm.nih.gov/pubmed/30895602
http://dx.doi.org/10.1002/ijc.32291
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author Bonde, Jesper
Bottari, Fabio
Parvu, Valentin
Pedersen, Helle
Yanson, Karen
Iacobone, Anna D.
Kodsi, Salma
Landoni, Fabio
Vaughan, Laurence
Ejegod, Ditte M.
Sandri, Maria T.
author_facet Bonde, Jesper
Bottari, Fabio
Parvu, Valentin
Pedersen, Helle
Yanson, Karen
Iacobone, Anna D.
Kodsi, Salma
Landoni, Fabio
Vaughan, Laurence
Ejegod, Ditte M.
Sandri, Maria T.
author_sort Bonde, Jesper
collection PubMed
description 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.
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spelling pubmed-66177342019-07-22 Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort Bonde, Jesper Bottari, Fabio Parvu, Valentin Pedersen, Helle Yanson, Karen Iacobone, Anna D. Kodsi, Salma Landoni, Fabio Vaughan, Laurence Ejegod, Ditte M. Sandri, Maria T. Int J Cancer Infectious Causes of Cancer 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. John Wiley & Sons, Inc. 2019-04-30 2019-08-15 /pmc/articles/PMC6617734/ /pubmed/30895602 http://dx.doi.org/10.1002/ijc.32291 Text en © 2019 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Infectious Causes of Cancer
Bonde, Jesper
Bottari, Fabio
Parvu, Valentin
Pedersen, Helle
Yanson, Karen
Iacobone, Anna D.
Kodsi, Salma
Landoni, Fabio
Vaughan, Laurence
Ejegod, Ditte M.
Sandri, Maria T.
Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort
title Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort
title_full Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort
title_fullStr Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort
title_full_unstemmed Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort
title_short Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort
title_sort bayesian analysis of baseline risk of cin2 and ≥cin3 by hpv genotype in a european referral cohort
topic Infectious Causes of Cancer
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617734/
https://www.ncbi.nlm.nih.gov/pubmed/30895602
http://dx.doi.org/10.1002/ijc.32291
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