title: IHC and the WHO classification of lymphomas: cost effective immunohistochemistry using a deductive reasoning "decision tree" approach.
abstract: The 2008 World Health Organization Classification of Tumors of the Hematopoietic and Lymphoid Tissues defines current standards of practice for the diagnosis and classification of malignant lymphomas and related entities. More than 50 different types of lymphomas are described, combining fine morphologic criteria with immunohistochemical (IHC), and sometimes molecular, findings. Faced with such a broad range of different lymphomas, some encountered only rarely, and a rapidly growing, ever changing, armamentarium of approximately 80 pertinent IHC "stains", the challenge to the pathologist is to employ IHC in an efficient manner, to arrive at an assured diagnosis as rapidly as possible. This review uses deductive reasoning, after a decision tree or dendrogram model that relies upon recognition of basic morphologic patterns for efficient selection, use and interpretation of IHC markers to classify node-based malignancies by the World Health Organization schema. The review is divided into 2 parts, the first addressing those lymphomas that produce a follicular or nodular pattern of lymph nodal involvement; the second addressing diffuse proliferations in lymph nodes. It is accepted that only specialized centers are able to apply all of the technical resources and experience necessary for definitive diagnosis of unusual cases. Emphasis therefore is given to the more common lymphomas and the more commonly available IHC "stains", for a pragmatic and practical approach that is both broadly feasible and cost effective. By this method an assured diagnosis may be reached in the majority of nodal lymphomas, at the same time developing a sufficiency of data to recognize those rare or atypical cases that require referral to a specialized center.
authors.affiliation: Applied Immunohistochemistry and Molecular Morphology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. ctaylor@keck.usc.edu
authors.forename: Clive R
authors.initials: CR
authors.lastname: Taylor
mesh_terms: D003362:Cost-Benefit Analysis; D003663:Decision Trees; D006801:Humans; D007150:Immunohistochemistry; D008223:Lymphoma / Q000145:classification* / Q000378:metabolism