Pathological Findings in COVID-19 and Non-COVID-19 Vaccine-Associated Lymphadenopathy: A Systematic Review

COVID-19 vaccine-associated lymphadenopathy (C19-VAL) is increasingly encountered with the widespread use of the vaccine in controlling the outbreak. We aim to characterize the pathological findings of COVID-19 and non-COVID-19 vaccine-associated lymphadenopathy (NC19-VAL). A search for studies that reported pathological findings in vaccine-associated lymphadenopathy on PubMed and Google Scholar was performed on 11 December 2021. C19-VAL studies were pooled for analysis. These studies were split into clinical lymphadenopathy (CL) and subclinical lymphadenopathy detected on imaging (SLDI) for subgroup analysis. A total of 25 studies were related to COVID-19 vaccines, and 21 studies were included in the pooled analysis. The pooled analysis included 37 patients with a mean age of 47.8 ± 19.1 years old, and 62.2% were females. The mean duration from last vaccination to development of CL/SLDI was 14.5 ± 11.0 days. Most were diagnosed as reactive or negative for malignancy (28/37, 75.5%), followed by Kikuchi–Fujimoto disease (KFD) (3/37, 8.1%), florid lymphoid hyperplasia (2/37, 5.4%), and granulomatous inflammation (2/37, 5.4%). Metastases were reported in two patients with a history of malignancy (2/37, 5.4%). Cases with florid lymphoid hyperplasia and KFD were younger than those with reactive changes. A total of 14 studies were related to non-COVID-19 vaccines. Caseating granulomatous inflammation was reported in BCG vaccine-associated lymphadenopathy, while other vaccines were associated with reactive lymphoid hyperplasia, florid post-vaccinal reactions, and KFD. Although most C19-VAL cases were reported as reactive or negative for malignancy, other diagnoses included florid lymphoid hyperplasia, KFD, and granulomatous inflammation. Metastases were reported in lymphadenopathy of patients with a history of malignancy, who had been incidentally vaccinated. In conclusion, C19-VAL can yield different histopathological diagnoses when sampled, most of which require clinical and radiological correlation for optimal patient management.