title: Personalised management of women with cervical abnormalities using a clinical decision support scoring system.
abstract: OBJECTIVE
  To develop a clinical decision support scoring system (DSSS) based on artificial neural networks (ANN) for personalised management of women with cervical abnormalities.
  
  
  METHODS
  We recruited women with cervical abnormalities and healthy controls that attended for opportunistic screening between 2006 and 2014 in 3 University Hospitals. We prospectively collected detailed patient characteristics, the colposcopic impression and performed a series of biomarkers using a liquid-based cytology sample. These included HPV DNA typing, E6&E7 mRNA by NASBA or flow cytometry and p16INK4a immunostaining. We used ANNs to combine the cytology and biomarker results and develop a clinical DSSS with the aim to improve the diagnostic accuracy of tests and quantify the individual's risk for different histological diagnoses. We used histology as the gold standard.
  
  
  RESULTS
  We analysed data from 2267 women that had complete or partial dataset of clinical and molecular data during their initial or followup visits (N=3565). Accuracy parameters (sensitivity, specificity, positive and negative predictive values) were assessed for the cytological result and/or HPV status and for the DSSS. The ANN predicted with higher accuracy the chances of high-grade (CIN2+), low grade (HPV/CIN1) and normal histology than cytology with or without HPV test. The sensitivity for prediction of CIN2 or worse was 93.0%, specificity 99.2% with high positive (93.3%) and negative (99.2%) predictive values.
  
  
  CONCLUSIONS
  The DSSS based on an ANN of multilayer perceptron (MLP) type, can predict with the highest accuracy the histological diagnosis in women with abnormalities at cytology when compared with the use of tests alone. A user-friendly software based on this technology could be used to guide clinician decision making towards a more personalised care.
authors.affiliation: Institute of Reproductive and Developmental Biology, Department of Surgery and Cancer, Imperial College London, UK; West London Gynaecological Cancer Centre, Queen Charlotte's and Chelsea - Hammersmith Hospital, Imperial Healthcare NHS Trust, London, UK. Electronic address: m.kyrgiou@imperial.ac.uk.
authors.forename: Maria
authors.initials: M
authors.lastname: Kyrgiou
authors.affiliation: Cytopathology, National and Kapodistrian University of Athens, Athens, Greece.
authors.forename: Abraham
authors.initials: A
authors.lastname: Pouliakis
authors.affiliation: 2nd Department of Pathology, National and Kapodistrian University of Athens, Athens, Greece.
authors.forename: John G
authors.initials: JG
authors.lastname: Panayiotides
authors.affiliation: Cytopathology, National and Kapodistrian University of Athens, Athens, Greece.
authors.forename: Niki
authors.initials: N
authors.lastname: Margari
authors.affiliation: Biomedical Engineering Laboratory, National Technical University of Athens, Greece.
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Bountris
authors.affiliation: Obstetrics & Gynaecology, University of Ioannina, Ioannina, Greece.
authors.forename: George
authors.initials: G
authors.lastname: Valasoulis
authors.affiliation: Institute of Reproductive and Developmental Biology, Department of Surgery and Cancer, Imperial College London, UK.
authors.forename: Maria
authors.initials: M
authors.lastname: Paraskevaidi
authors.affiliation: Elena Venizelou Hospital, Athens, Greece.
authors.forename: Evripidis
authors.initials: E
authors.lastname: Bilirakis
authors.affiliation: 2nd Department of Obstetrics & Gynecology and Molecular Clinical Cytology Laboratory, Hippokration Hospital, Aristotle University of Thessaloniki, Greece.
authors.forename: Maria
authors.initials: M
authors.lastname: Nasioutziki
authors.affiliation: 2nd Department of Obstetrics & Gynecology and Molecular Clinical Cytology Laboratory, Hippokration Hospital, Aristotle University of Thessaloniki, Greece.
authors.forename: Aristotelis
authors.initials: A
authors.lastname: Loufopoulos
authors.affiliation: Institute of Communication and Computer Systems, Athens, Greece.
authors.forename: Maria
authors.initials: M
authors.lastname: Haritou
authors.affiliation: Biomedical Engineering Laboratory, National Technical University of Athens, Greece.
authors.forename: Dimitrios D
authors.initials: DD
authors.lastname: Koutsouris
authors.affiliation: Cytopathology, National and Kapodistrian University of Athens, Athens, Greece.
authors.forename: Petros
authors.initials: P
authors.lastname: Karakitsos
authors.affiliation: Obstetrics & Gynaecology, University of Ioannina, Ioannina, Greece.
authors.forename: Evangelos
authors.initials: E
authors.lastname: Paraskevaidis
mesh_terms: D004279:DNA, Viral / Q000032:analysis; D020000:Decision Support Systems, Clinical; D005260:Female; D006801:Humans; D016571:Neural Networks, Computer; D027383:Papillomaviridae / Q000302:isolation & purification; D057285:Precision Medicine; D011446:Prospective Studies; D002583:Uterine Cervical Neoplasms / Q000628:therapy* / Q000821:virology; D002578:Uterine Cervical Dysplasia / Q000628:therapy* / Q000821:virology
chemical_list: D004279:DNA, Viral
keywords: Artificial neural networks; CIN; Cervical intra-epithelial neoplasia; Decision Support Scoring System; Modelling; Multilayer perceptron