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Artificial intelligence estimates the impact of human papillomavirus types in influencing the risk of cervical dysplasia recurrence

progress toward a more personalized approach

Bogani, Giorgioa; Ditto, Antoninoa; Martinelli, Fabioa; Signorelli, Mauroa; Chiappa, Valentinaa; Leone Roberti Maggiore, Umbertoc,d; Taverna, Francescab; Lombardo, Claudiab; Borghi, Chiarae; Scaffa, Conoa; Lorusso, Domenicaa; Raspagliesi, Francescoa

European Journal of Cancer Prevention: March 2019 - Volume 28 - Issue 2 - p 81–86
doi: 10.1097/CEJ.0000000000000432
Research Papers: Gynaecological Cancer

The objective of this study was to determine whether the pretreatment human papillomavirus (HPV) genotype might predict the risk of cervical dysplasia persistence/recurrence. Retrospective analysis of prospectively collected data of consecutive 5104 women who underwent the HPV-DNA test were matched with retrospective data of women undergoing either follow-up or medical/surgical treatment(s) for genital HPV-related infection(s). Artificial neuronal network (ANN) analysis was used in order to weight the importance of different HPV genotypes in predicting cervical dysplasia persistence/recurrence. ANN simulates a biological neuronal system from both the structural and functional points of view: like neurons, ANN acquires knowledge through a learning-phase process and allows weighting the importance of covariates, thus establishing how much a variable influences a multifactor phenomenon. Overall, 5104 women were tested for HPV. Among them, 1273 (25%) patients underwent treatment for HPV-related disorders. LASER conization and cervical vaporization were performed in 807 (59%) and 386 (30%) patients, respectively, and secondary cervical conization in 45 (5.5%). ANN technology showed that the most important genotypes predicting cervical dysplasia persistence/recurrence were HPV-16 (normalized importance: 100%), HPV-59 (normalized importance: 51.2%), HPV-52 (normalized importance: 47.7%), HPV-18 (normalized importance: 32.8%) and HPV-45 (normalized importance: 30.2%). The pretreatment diagnosis of all of those genotypes, except HPV-45, correlated with an increased risk of cervical dysplasia persistence/recurrence; the pretreatment diagnosis was also arrived at using standard univariate and multivariable models (P<0.01). Pretreatment positivity for HPV-16, HPV-18, HPV-52 and HPV-59 might correlate with an increased risk of cervical dysplasia persistence/recurrence after treatment. These data might be helpful during patients’ counseling and to implement new vaccination programs.

aDepartment of Gynecologic Oncology

bDepartment of Immunohematology and Transfusion Medicine, IRCCS National Cancer Institute, Milan

cDepartment of Obstetrics and Gynecology, IRCCS AOU San Martino

dDepartment of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI), University of Genoa, Genoa

eDepartment of Obstetrics and Gynecology, Sant’Anna University Hospital, Ferrara, Italy

Correspondence to Giorgio Bogani, MD, PhD, Department of Gynecologic Oncology, IRCCS National Cancer Institute, Via Venezian 1, 20133 Milan, Italy Tel: +39 022 390 2392; fax: +39 022 390 2349; e-mails:,

Received April 11, 2017

Accepted July 23, 2017

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