Naresh, Kikkeri N.Ibrahim, Hazem A. H.Lazzi, StefanoRince, PatriciaOnorati, MonicaAmbrosio, Maria R.Bilhou-Nabera, Chryste`leAmen, FurratReid, AlistairMawanda, MichaelCalbi, ValeriaOgwang, MartinRogena, EmilyByakika, BessieSayed, ShahinMoshi, EmmaMwakigonja, AmosRaphael, MartineMagrath, IanLeoncini, Lorenzo2022-04-292022-04-292011Naresh, K. N., Ibrahim, H. A., Lazzi, S., Rince, P., Onorati, M., Ambrosio, M. R., ... & Leoncini, L. (2011). Diagnosis of Burkitt lymphoma using an algorithmic approach–applicable in both resource‐poor and resource‐rich countries. British journal of haematology, 154(6), 770-776. doi:10.1111/j.1365-2141.2011.08771.x10.1111/j.1365-2141.2011.08771.xhttps://nru.uncst.go.ug/handle/123456789/2978Distinguishing Burkitt lymphoma (BL) from B cell lymphoma, unclassifiable with features intermediate between diffuse large B-cell lymphoma (DLBCL) and BL (DLBCL/BL), and DLBCL is challenging. We propose an immunohistochemistry and fluorescent in situ hybridization (FISH) based scoring system that is employed in three phases – Phase 1 (morphology with CD10 and BCL2 immunostains), Phase 2 (CD38, CD44 and Ki-67 immunostains) and Phase 3 (FISH on paraffin sections for MYC, BCL2, BCL6 and immunoglobulin family genes). The system was evaluated on 252 aggressive B-cell lymphomas from Europe and from sub-Saharan Africa. Using the algorithm, we determined a specific diagnosis of BL or not-BL in 82%, 92% and 95% cases at Phases 1, 2 and 3, respectively. In 3Æ4% cases, the algorithm was not completely applicable due to technical reasons. Overall, this approach led to a specific diagnosis of BL in 122 cases and to a specific diagnosis of either DLBCL or DLBCL/BL in 94% of cases that were not diagnosed as BL. We also evaluated the scoring system on 27 cases of BL confirmed on gene expression/microRNA expression profiling. Phase 1 of our scoring system led to a diagnosis of BL in 100% of these cases.enLymphomaDiagnostic haematologyImmunophenotyping.Article