Background

Despite widespread clinical use, lymph node fine-needle aspiration cytology (LN-FNAC) lacks universal acceptance for definitively diagnosing lymphomas. This is likely due to reports of lower diagnostic performance, inconsistent terminology use in cytopathology diagnostic reports, and only limited data on the clinical implications of LN-FNAC diagnoses. Recently, a uniform LN-FNAC cytopathological diagnostic reporting system was proposed (the Sydney System). This study evaluated LN-FNAC diagnostic performance and risks of malignancy associated with the proposed diagnostic categories.

Methods

LN-FNAC specimens obtained in 2018-2019, with and without concurrent core biopsy, to evaluate for suspected lymphoma were analyzed (n = 349). LN-FNAC diagnoses were compared with final diagnoses obtained via subsequent tissue biopsy and/or clinical assessment.

Results

The mean patient age was 57.6 years, and 41% were female. LN-FNAC was the initial diagnostic test in 223 (63.9%), and it was used to evaluate for recurrence in 126 (36.1%). LN-FNAC diagnosed 202 hematological malignancies (57.9%), 23 nonhematological malignancies (6.6%), and 124 reactive processes (35.5%). Subsequent tissue biopsy was performed in 42 (12%). The risks of malignancy per diagnostic category were as follows: inadequate, 58.3%; benign, 6.4%; atypical, 69.2%; suspicious, 96.7%; and malignant, 99.3%. LN-FNAC demonstrated up to 96.3% sensitivity, 91.91% specificity, and 87.35% accuracy. Optimal specimen quality and the use of intradepartmental consultation reduced diagnostic error rates in FNA cases without concurrent core biopsy (P = .029 and P = .0002 respectively).

Conclusions

LN-FNAC is accurate and reliable for the diagnosis of lymphoma. Inadequate LN-FNAC samples should be resampled due to a significant associated risk of lymphoma. The diagnostic performance of LN-FNAC may be improved with good specimen quality and reviews by multiple pathologists. Understanding the risks of malignancy associated with LN-FNAC diagnostic categories will help to guide optimal patient management.