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.
Keywords: HPV; automation; cancer; cervical; cytology; screening.
© 2016 UICC.