Diagnostic models for predicting malignancy in thyroid nodules classified as Bethesda Category III in an endemic region.

Autor: Kasap ZA; Department of Biostatistics and Medical Informatics, Faculty of Medicine, Karadeniz Technical University, Trabzon, Turkey., Kurt B; Department of Biostatistics and Medical Informatics, Faculty of Medicine, Karadeniz Technical University, Trabzon, Turkey., Özsağır E; Bingöl Provincial Health Directorate, State Hospital, Bingöl, Turkey., Ercin ME; T.R. Ministry of Health Ankara Atatürk Sanatorium Education and Research Hospital, Ankara, Turkey., Güner A; Department of General Surgery, Faculty of Medicine, Karadeniz Technical University, Trabzon, Turkey.
Jazyk: angličtina
Zdroj: Diagnostic cytopathology [Diagn Cytopathol] 2024 Apr; Vol. 52 (4), pp. 200-210. Date of Electronic Publication: 2024 Jan 25.
DOI: 10.1002/dc.25270
Abstrakt: Background: This study aims to develop a diagnostic model to help physicians determine whether thyroid nodules categorized as atypia of undetermined significance (AUS) in category III of the Bethesda system are benign or malignant preoperatively. To create a diagnostic model for predicting thyroid nodules' benign or malignant with AUS cytology based on clinical, ultrasonographic, and cytopathological findings.
Methods: This is a retrospective cohort study involving patients (>19) at risk of thyroid cancer who had thyroidectomy after an AUS cytology. The dataset consists of 53 variables 204 nodules from 183 patients. Binary logistic regression and factor analysis methods were used to identify risk factors for malignancy. Finally, four prediction models were developed using different approaches, based on clinical, pathological clinical + pathological, and the factors.
Results: A total of 88 (48.1%) of 183 patients diagnosed with AUS were benign and 95 (51.9%) the malignant. After determining risk factors, four prediction models were developed based on different approaches to assist physicians in deciding to detect AUS nodules early. It was seen that bilaterality was found to be a risk factor for malignancy in the clinical model (p bilaterality  = .03) and it was also seen that the pathological variables pale chromatin and irregular contours in the oncocyte variables were risk factors for malignancy (p palechromatin  = .02, p irregularcontoursintheoncocyte  = .04). The best model obtained sensitivity and specificity values are 73% and 87% based on clinical and pathological variables.
Conclusion: This comprehensive study may provide a more in-depth understanding of AUS and make a notable contribution to healthcare professionals before surgery.
(© 2024 Wiley Periodicals LLC.)
Databáze: MEDLINE
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