Pathological assessment of the lymph node biopsies for lymphadenopathy in rheumatoid arthritis.
Chika YamadaEri OguroSoichiro TsujiEriko Kudo-TanakaSatoru TeshigawaraShiro OhshimaJun HashimotoYukihiko SaekiTetsuya HoriuchiNorishige IizukaYasuhiko TomitaYoshihiko HoshidaPublished in: Modern rheumatology (2019)
Objectives: To assess the incidence of reactive lymph node hyperplasia (RLH) and the diagnostic characteristics that can help differentiate it from lymphoproliferative disorders (LPD) in patients with rheumatoid arthritis (RA).Methods: Data on patient characteristic from 32 consecutive RA patients with lymphadenopathy at a single medical center over a 6-year period were collected and analyzed to determine whether any of these characteristics can differentiated RLH from LPD.Results: LPD including methotrexate (MTX) - associated LPD (MTX-LPD) and RLH were diagnosed in 19 and 10 patients, respectively. Conclusive diagnosis was not reached in the remaining three cases and they were regarded as grey-zone cases. Age, levels of lactate dehydrogenase (LDH) and soluble interleukin-2 receptor (sIL-2R), as well as maximum standardized uptake value (SUVmax), were significantly higher in LPD than in RLH patients. The diagnosis cut-off values for these parameters were 66 year, 169 U/L, 899 U/mL and 8.18, respectively, based on the receiver operating characteristics curve analysis for both RLH and LPD.Conclusions: About one-third of patients with RA who presented with lymphadenopathy had reactive lymph node enlargement. Older age and higher levels of LDH, sIL-2R, and SUVmax are more associated with LPD than should be considered when deciding to perform a biopsy.
Keyphrases
- lymph node
- rheumatoid arthritis
- end stage renal disease
- newly diagnosed
- ejection fraction
- chronic kidney disease
- disease activity
- neoadjuvant chemotherapy
- prognostic factors
- ankylosing spondylitis
- squamous cell carcinoma
- fine needle aspiration
- patient reported outcomes
- low dose
- electronic health record
- systemic lupus erythematosus
- physical activity
- machine learning
- multiple sclerosis
- rectal cancer
- locally advanced
- clinical evaluation