[Aid to the clinical and biological diagnosis of malignancy in a nodular hepatic image discovered by echography].
When ultrasound examination of the upper abdomen detects a liver nodule, the malignancy of this lesion must be discussed. If past history of cancer is known, a benign lesion cannot be excluded. Conversely, if the examination is performed without a history of cancer, we must raise the possibility of a malignant lesion. We attempted to demonstrate that the simple clinical and biological findings allow, if well used, a diagnosis of malignancy or benign nature, rather than performing further investigations, sometimes costly or invasive. We therefore compared three different methods: the well known bayesian diagnostic process; the multivariate analysis using logistic regression model; the Decision Theory, constructing a binary discrimination tree. The three methods lead to approximately the same rate of well classified patients (93 to 95%). Advantages and disadvantages are discussed.
D000704:Analysis of Variance; D001499:Bayes Theorem; D003657:Decision Making; D003937:Diagnosis, Differential; D006801:Humans; D008107:Liver Diseases / Q000175:diagnosis* / Q000473:pathology; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D008487:Medical History Taking; D008962:Models, Theoretical; D011336:Probability; D014463:Ultrasonography
Aide au diagnostic clinique et biologique de malignité devant une image nodulaire hépatique découverte par échographie.