Laboratory assessment of Fine-Needle Aspiration of Thyroid nodules. Quality assurance and surgical implications. Weltevreden E.F. and Daliri-Naseri N. Department of Clinical Pathology, Gelre hospitals, Apeldoorn, The Netherlands
Background: The management of patients with a thyroid nodule is largely based on Fine-Needle Aspiration (FNA) cytology. Apart from the major contribution of FNA in the detection and therapy of simple thyroid cysts, FNA cytology is considered safe, simple, cost-effective and accurate. It is however generally known that a substantial number of patients with (solitary) thyroid nodules is subject to surgical overtreatment, probably based on an indeterminate classification like for instance Atypical Cellular Lesions (ACL) or “follicular neoplasm” (FN). On the other hand false negative cytology does occurs. With the present study we tried to get insight in our performance in FNA cytology of the thyroid, with the aim to monitor laboratory quality and to look for opportunities to optimize the procedure. Design: For this retrospective study, local data were retrieved from “PALGA”, the nationwide network and registry of histo- and cytopathology in the Netherlands", for a 10 year period (01-012000 to 31-12-2009). The data comprise 648 consecutive primary FNA’s, routinely performed at our hospital, including 59 cases with histopathological follow-up. All cases had at least 20 month clinical follow-up. Some data are properly reshuffled along with the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC), because of inconsistent classification rules used over time by different (cyto-)pathologists. For data analysis we used ROC-curve analysis and for a proper comparison with data from literature, we derived the predictive value of the FNA-cytology of the thyroid lesions from Bayes’s theorem, in which prevalence (prior odds) and the probability quotient (A) determine the predictive value (posterior odds) of a test.
Results: Of 648 FNA samples, 17% were classified as unsatisfactory partly cystic lesions, 68% were classified as benign including many cysts, 5% were classified as ACL, 5% were classified as FN, 1% were classified as suspicious and 3% were classified as malignant. Fifty-nine patients had surgical followup. The rates for histological confirmed malignancy in adequate FNA were 3% in benign FNA, 33% in ACL, 13% in FN, 86% in suspicious cases and 85% in malignancy in FNA. The overall percentages are in accordance with the literature except for interchangeable results in cases classified as ACL and FN. Also in concordance with the literature, are our findings as to accuracy , with a relative low sensitivity (se = 0.66) and a relative high specificity (sp = 0.93) fitting the “classic ROCcurve” of Herle (1982). A favourable performance / strength of the procedure is shown in the Probability Quotient ( = 9.4). Predictive value = prevalence / ( prevalence + (1 – prevalence / probability quotient)) So, derived from Bayes’s theorem, the predictive value in case of a not-benign outcome of FNA cytology = 0.78 (prevalence 27/95)
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Conclusion: In our hands, the predicted value of FNA-cytology of the thyroid nodule is adequate and the low Fals Positive ratio ( = high specificity) minimizes surgical overtreatment. A subset of non-diagnostic “cyst-fluid-only” cases can cause a high percentage of unsatisfactory classified lesions. It is optional to classify these as benign if the nodule is entirely cystic and without any other suspicious findings. Outcome indicators like the positive predictive value and the False Positive ratio can simply be assessed on a regular basis to monitor laboratory quality. A uniform classification is a prerequisite to compare results over time and amomg laboratories. Recommendations to interpretation of FNA-cytology results have to be followed more strictly to distinguish ACL and FN cases to get to the preferred management plan; repeat FNA or surgical lobectomy. To raise sensitivity and to minimize the grey-zone of indeterminate diagnosis, we have to assign FNA-cytology of the thyroid to a specialized cytopathologist.