Blood 89(11): 3909-3918, 1997.
The Non-Hodgkin's Lymphoma Classification Project
The recognition of several new types of non-Hodgkin's lymphoma (NHL) in recent years has led to proposals for changing lymphoma classifications, including a new proposal put forth by the International Lymphoma Study Group (ILSG). However, the clinical significance of the new entities and the practical utility of this new proposal have not been studied. Therefore, we performed a clinical evaluation of the ILSG classification. A cohort of 1,403 cases of NHL was organized at nine study sites around the world and consisted of consecutive patients seen between 1988 and 1990 who were previously untreated. A detailed protocol for histologic and clinical analysis was followed at each site, and immunologic characterization as to T- or B-cell phenotype was required. Five expert hematopathologists visited the sites and each classified each case using the ILSG classification. A consensus diagnosis was also reached in each case, and each expert rereviewed a 20% random sample of the cases. Clinical correlations and survival analyses were then performed. A diagnosis of NHL was confirmed in 1,378 (98.2%) of the cases. The most common lymphoma types were diffuse large B-cell lymphoma (31%) and follicular lymphoma (22%), whereas the new entities comprised 21% of the cases. Diagnostic accuracy was at least 85% for most of the major lymphoma types, and reproducibility of the diagnosis was 85%. Immunophenotyping improved the diagnostic accuracy by 10% to 45% for a number of the major types. The clinical features of the new entities were distinctive. Both the histologic types and the patient characteristics as defined by the International Prognostic Index predicted for patient survival. In conclusion we found that the ILSG classification can be readily applied and identifies clinically distinctive types of NHL. However, for clinical application, prognostic factors as defined by the International Prognostic Index must be combined with the histologic diagnosis for appropriate clinical decisions.
Rheinische Friedrich- Wilhelms- Universität Bonn