HPV genotype-specific distribution and attributable risk in cervical intraepithelial neoplasia in a referral population with a history of LSIL. Journal Articles uri icon

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abstract

  • BACKGROUND AND OBJECTIVE: CINtec PLUS and cobas HPV tests (Roche) were previously ascertained for triaging an LSIL referral population [1]. As part of this study, genotype-specific distribution and attributable risk of high-risk (HR)-HPV in cervical intraepithelial neoplasia (CIN) were determined. METHODS: Archived cervical specimens in ThinPrep PreservCyt (Hologic Inc) from the LSIL referral population (n= 533) were genotyped using the Anyplex II HPV HR test (Anyplex, Seegene Inc). Since the study specimens had been in storage in ambient temperature for 31-47 months since collection, Anyplex results were compared with that of the initial cobas testing of fresh specimens to validate the suitability and stability of specimens for the present study. RESULTS: Overall, Anyplex test was positive in 63% (336/533) vs. 55.7% (297/533) for cobas test. Anyplex test performed identical to cobas test identifying 93.2% (82/88) of ⩾CIN2/adenocarcinoma in situ (AIS). Anyplex test detected genotypes 16/18 in 15.7% (36/230) ⩽CIN1 vs. 45.5% (40/88) ⩾CIN2/AIS; the corresponding figures were 13.5% (31/230) and 45.5% (40/48) for the cobas test. Genotype 16 showed increasing attribution, 13.2% in CIN1, 27.1% in CIN2 and 40% in CIN3/AIS. Of the 12 other high-risk (OHR) types collectively identified by cobas, Anyplex test specifically detected, in decreasing order, genotypes 51, 31, 35, 56, 39, and 45 as the most frequent types, often in multiple-type infections, in 64.8% ⩾CIN2. Regardless, estimated attribution was evident for each of the 12 OHR types in ⩾CIN2. Multiple-type infections were more frequent than single-type infections in all CIN grades. CONCLUSIONS: Attributable risk of all HR-HPV genotypes targeted by both Anyplex and cobas tests was evident in ⩾CIN2/AIS Testing for these genotypes in HPV primary cervical screening and cytology triage could identify those at increased risk of cervical cancer and also be beneficial in the management of LSIL referral populations.

authors

  • Ratnam, Sam
  • Jang, Dan
  • Alaghehbandan, Reza
  • Gilbert, Laura
  • Xu, Yunwen
  • Wang, Wei
  • Andrews, Phillip
  • Green, Ashley
  • Speicher, David J
  • Chernesky, Max

publication date

  • 2023