Diagnostic Accuracy of Fine Needle Aspiration Cytology of Thyroid in Hospital Sultanah Nur Zahirah, Malaysia
Year: 2025
Type: article
Study design: Observational Study
Abstract: INTRODUCTION: Fine Needle Aspiration Cytology (FNAC) is widely used as an initial screening method in the preoperative examination of thyroid lesions. However, diagnostic cytology interpretation remains inconsistent among reporting pathologists worldwide. This study aimed to determine the diagnostic accuracy of FNAC of thyroid lesions at Hospital Sultanah Nur Zahirah (HSNZ), a tertiary hospital in Kuala Terengganu, Malaysia. MATERIAL AND METHODS: We conducted a retrospective cross-sectional study at the Department of Pathology, HSNZ, from January 2017 to December 2019. Data of patients were collected from the Laboratory Information System (LIS) and Hospital Information System (HIS). The study included patients with thyroid lesions who underwent both FNAC and subsequent histopathological examination (HPE). RESULT: A total of 389 cases of thyroid lesions underwent FNAC, with 162 cases proceeding to surgical resection. The median age of the patients was 43.3 years, with a male to female ratio of 1:5.3. FNAC diagnoses were categorized as follows: 85 cases (52.5%) were benign, 23 (14.2%) as atypia or follicular lesion of undetermined significance, 9 (5.6%) as follicular neoplasm, 21 (13%) as suspicious for malignancy, and 12 (7.4%) as malignant and unsatisfactory. The diagnostic accuracy of FNAC was 85.8%, with sensitivity of 66.7% and specificity of 96.2%. The positive predictive value was 90.5%, and the negative predictive value was 84.2%. CONCLUSION: FNAC has proven to be an accurate diagnostic method for screening thyroid lesions. However, continuous improvement in sampling and preparation techniques and cytopathologist training is necessary to enhance its reliability further.
Source: IIUM Medical Journal Malaysia
Authors: Nurul Nadhihah Adam, Alaa Siddig, Ahmad Fazlin Nasaruddin, Nor Hayati Ismail, Anani Aila Mat Zin, Wan Faiziah Wan Abdul Rahman
Institutions: Universiti Sains Malaysia, Hospital Sultanah Nur Zahirah
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4411917435