title: Proof-of-principle study of a novel cervical screening and triage strategy: Computer-analyzed cytology to decide which HPV-positive women are likely to have ≥CIN2.
abstract: A challenge in implementation of sensitive HPV-based screening is limiting unnecessary referrals to colposcopic biopsy. We combined two commonly recommended triage methods: partial HPV typing and "reflex" cytology, evaluating the possibility of automated cytology. This investigation was based on 1,178 exfoliated cervical specimens collected during the enrollment phase of The Study to Understand Cervical Cancer Early Endpoints and Determinants (SUCCEED, Oklahoma City, OK). We chose a colposcopy clinic population to maximize number of outcomes, for this proof-of-principle cross-sectional study. Residual aliquots of PreservCyt were HPV-typed using Linear Array (LA, Roche Molecular Systems, Pleasanton, CA). High-risk HPV typing data and cytologic results (conventional and automated) were used jointly to predict risk of histologically defined ≥CIN2. We developed a novel computer algorithm that uses the same optical scanning features that are generated by the FocalPoint Slide Profiler (BD, Burlington, NC). We used the Least Absolute Shrinkage and Selection Operator (LASSO) method to build the prediction model based on a training dataset (n = 600). In the validation set (n = 578), for triage of all HPV-positive women, a cytologic threshold of ≥ASC-US had a sensitivity of 0.94, and specificity of 0.30, in this colposcopy clinic setting. When we chose a threshold for the severity score (generated by the computer algorithm) that had an equal specificity of 0.30, the sensitivity was 0.91. Automated cytology also matched ≥ASC-US when partial HPV typing was added to the triage strategy, and when we re-defined cases as ≥CIN3. If this strategy works in a prospective screening setting, a totally automated screening and triage technology might be possible.
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
authors.forename: Mark
authors.initials: M
authors.lastname: Schiffman
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
authors.forename: Kai
authors.initials: K
authors.lastname: Yu
authors.affiliation: Oklahoma University Health Sciences Center, Oklahoma City, OK.
authors.forename: Rosemary
authors.initials: R
authors.lastname: Zuna
authors.affiliation: Oklahoma State Department of Health, Oklahoma City, OK.
authors.forename: S
authors.initials: S
authors.lastname: Terence Dunn
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
authors.forename: Han
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Oklahoma State Department of Health, Oklahoma City, OK.
authors.forename: Joan
authors.initials: J
authors.lastname: Walker
authors.affiliation: Tulsa Cancer Institute, Tulsa, OK.
authors.forename: Michael
authors.initials: M
authors.lastname: Gold
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
authors.forename: Noorie
authors.initials: N
authors.lastname: Hyun
authors.affiliation: Information Management Services, Calverton, MD.
authors.forename: Greg
authors.initials: G
authors.lastname: Rydzak
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
authors.forename: Hormuzd A
authors.initials: HA
authors.lastname: Katki
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Wentzensen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001706:Biopsy / Q000379:methods; D003127:Colposcopy / Q000379:methods; D003430:Cross-Sectional Studies; D003581:Cytodiagnosis / Q000379:methods; D055088:Early Detection of Cancer / Q000379:methods; D005260:Female; D006801:Humans; D008403:Mass Screening / Q000379:methods; D008875:Middle Aged; D027383:Papillomaviridae; D030361:Papillomavirus Infections / Q000473:pathology* / Q000821:virology; D012680:Sensitivity and Specificity; D014218:Triage / Q000379:methods; D002583:Uterine Cervical Neoplasms / Q000473:pathology* / Q000821:virology*; D014626:Vaginal Smears / Q000379:methods
keywords: HPV; automation; cancer; cervical; cytology; screening