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. 2002 Mar 1;94(5):1574-83.
doi: 10.1002/cncr.10359.

Morphologic features of neuroblastoma (Schwannian stroma-poor tumors) in clinically favorable and unfavorable groups

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Free article

Morphologic features of neuroblastoma (Schwannian stroma-poor tumors) in clinically favorable and unfavorable groups

Inge M Ambros et al. Cancer. .
Free article

Abstract

Background: After the establishment of the International Neuroblastoma Pathology Classification system, the authors studied retrospectively the prognostic impact of morphologic features in a series of two clinically distinct subsets of patients with peripheral neuroblastic tumors (NTs), i.e., tumors in the neuroblastoma category.

Methods: Forty-seven NTs categorized into either clinically favorable or unfavorable subgroups were selected randomly from 100 NTs for a histologic review that included the evaluation of 14 morphologic characteristics. The review was performed individually followed by a group review. The correlations of the prognostic significance of the individual morphologic features and the correlations among them were determined by use of odds ratios (ORs) with corresponding 95% confidence intervals (95%CIs). The inter-rater agreement was determined by using the Cohen kappa coefficient.

Results: Ten of 14 morphologic features, including nuclear size, cellularity, prominent nucleoli in undifferentiated or poorly differentiated neuroblasts, and the number of mitotic and karyorrhectic cells (MKI), showed a significant correlation with the clinical groups (ORs between 36.9 and 10.5 and P values between < 0.001 and 0.002). In addition to the patient's age at diagnosis (OR, 7.4; 95%CI, 1.9-28.9; P = 0.002), 8 of 14 features also provided prognostic information (ORs between 35.1 and 7.9 and P values between < 0.001 and 0.039).

Conclusions: This study again confirmed the prognostic impact of the criteria used in the Shimada system and revealed that some other morphologic features, such as prominent nucleoli in undifferentiated and poorly differentiated neuroblasts, identify unfavorable tumor biology, partly independent from the patient's age at diagnosis. However, the prognostic impact of these features needs to be confirmed by analysis of a large series of neuroblastic tumors.

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