Document Type
Abstract
Publication Date
2-2021
Academic Year
2020-2021
Abstract
Introduction: Excisional biopsy (EB) of lymph nodes is the gold standard for diagnosing lymphoma. Recent literature suggests that diagnostic techniques such as immunohistochemistry, flow cytometry and FISH/Cytogenetics yield similar diagnostic adequacy rates when paired with less invasive procedures, like Core Needle Biopsy (CNB). We were interested in comparing the diagnostic odds ratio and adequacy of patients suspected of lymphoma who underwent CNB to EB at Thomas Jefferson University Hospital (TJUH).
Methods: We performed a retrospective cohort study on biopsies collected from 01/01/2016 and 12/31/2019 at TJUH. Specimens were considered diagnostically inadequate if there was not enough lesional tissue for diagnosis or the disease process was unable to be fully characterized. The diagnostic odds ratio and confidence intervals were calculated using the Baptista-Pike method. Adequacy of the specimens was then compared for statistical significance using a chi-squared test.
Results: A total of 457 biopsy samples were included in the final analysis, consisting of 339 EB samples and 118 CNB samples. EBs had adequate tissue to make a diagnosis 96.8% (328) of the time, while CNB’s had adequate tissue 56.8% (67) of the time. The diagnostic odds ratio of CNB was determined to be 0.03583, [95% confidence interval {CI}: 0.01695 to 0.07532] (Baptista-Pike), p<0.0001 (Chi square).
Discussion: TJUH has begun moving away from EBs in recent years, but our results indicate that EB should remain the standard of care. Additional research is needed to understand the reason for this recent trend as well as how ancillary studies could enhance CNB diagnostic accuracy.
Recommended Citation
Gardner, Christopher A.; Ye, Xiangyun; Tucker, MD, Catherine; Redilla, Austin; Uppal, MD, Guldeep; and Binder, Adam F., "Assessment of the Diagnostic Accuracy of Core Needle Biopsy in the Diagnosis of Lymphoma" (2021). Phase 1. Paper 86.
https://jdc.jefferson.edu/si_ctr_2023_phase1/86
Language
English
