BACKGROUND: @entity3557 is the most common endocrine malignancy. The most sensitive and specific diagnostic tool for thyroid nodule diagnosis is fine-needle aspiration (FNA) biopsy with cytological evaluation. Nevertheless, FNA biopsy is not always decisive leading to "indeterminate" or "suspicious" diagnoses in 10  %-30  % of cases. @entity817 @entity8554 detection is currently used as molecular test to improve the diagnosis of thyroid nodules, yet it lacks sensitivity. The aim of the present study was to identify novel molecular markers/computational models to improve the discrimination between benign and @entity1374 . METHODS: We collected 118 pre-operative thyroid FNA samples. All 118 FNA samples were characterized for the presence of the @entity817 @entity8554 mutation (exon15) by pyrosequencing and further assessed for mRNA expression of four genes ( @entity2467 , @entity23905 , @entity10074 , @entity38113 ) by quantitative polymerase chain reaction. Computational models (Bayesian Neural Network Classifier, discriminant analysis) were built, and their ability to discriminate benign and malignant @entity5 were tested. Receiver operating characteristic (ROC) analysis was performed and principal component analysis was used for visualization purposes. RESULTS: In total, 36/70 malignant samples carried the @entity8554 mutation, while all 48 benign samples were wild type for @entity817 exon15. The Bayesian neural network (BNN) and discriminant analysis, including the mRNA expression of the four genes ( @entity2467 , @entity23905 , @entity10074 , @entity38113 ) showed a very strong predictive value (94.12  % and 92.16  %, respectively) in discriminating malignant from benign @entity1 . The discriminant analysis showed a correct classification of 100  % of the samples in the malignant group, and 95  % by BNN. @entity2467 and @entity38113 showed the highest diagnostic accuracy of the ROC curve, with area under the curve values of 0.973 for @entity2467 and 0.931 for @entity38113 . CONCLUSIONS: The four genes model proposed in this study proved to be highly discriminative of the malignant status compared with @entity817 assessment alone. Its implementation in clinical practice can help in identifying malignant/benign nodules that would otherwise remain suspicious.

The combination of four molecular markers improves thyroid cancer cytologic diagnosis and XXXX management.

@entity3557 :: ('MESH:C536915', 'Disease') :: ['Papillary thyroid cancer'] @entity1 :: ('9606', 'Species') :: ['patients'] @entity23905 :: ('6947', 'Gene') :: ['TC1'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumors'] @entity38113 :: ('574447', 'Gene') :: ['miR-146b'] @entity8554 :: ('p|SUB|V|600|E', 'ProteinMutation') :: ['V600E'] @entity10074 :: ('407007', 'Gene') :: ['miR-222'] @entity2467 :: ('3815', 'Gene') :: ['KIT'] @entity817 :: ('673', 'Gene') :: ['BRAF'] @entity1374 :: ('MESH:D013959', 'Disease') :: ['malignant thyroid lesions']
@entity1 :: (9606,Species) :: ['patient']
