The American Journal of Surgical Pathology vol:33 issue:1 pages:50-57
The distinction between benign and malignant cartilaginous tumors of bone is one of the most difficult subjects in surgical pathology. The grading of chondrosarcoma also seems to vary considerably among pathologists. However, clinical management differs. The purpose of this study was (1) to investigate interobserver variability in histological diagnosis and grading of central cartilaginous tumors and (2) to assess the diagnostic value of defined histologic parameters in differentiating enchondroma and central grade I chondrosarcoma. The interobserver variability was assessed using a set of 16 cases evaluated by 18 specialized pathologists. Subsequently, 20 enchondromas and 37 central grade I chondrosarcomas diagnosed in a multidisciplinary team with full clinical, radiologic, and pathologic data available with 10 years of follow-up were collected. Cytologic and tissue-architectural features were assessed to find an optimal set of parameters to differentiate enchondroma from central grade I chondrosarcoma. We demonstrate considerable variation in the histologic assessment of cartilaginous tumors (weighted kappa=0.78). The distinction between enchondroma and grade I chondrosarcoma was shown to be the most disconcordant (kappa coefficient=0.54), and also the differentiation between grade I and grade II chondrosarcoma was subjected to variation (kappa coefficient=0.80). The application of a combination of 5 parameters (high cellularity, presence of host bone entrapment, open chromatin, mucoid matrix quality, and age above 45 y) allowed optimal differentiation between enchondromas and central grade I chondrosarcomas. With a classification tree based on 2 parameters (mucoid matrix degeneration more than 20% and/or host bone entrapment present), 54 of the 57 (94.7%) cases were assessed correctly (sensitivity 95% and specificity 95%). Our study confirms the low reliability of the diagnosis and grading of central chondrosarcoma. However, these classifications guide therapeutic decision making in daily practice. Therefore, we propose a classification model that, combined with a tailored radiologic assessment, may improve reliability of the diagnosis of cartilaginous tumors.