The American Journal of Surgical Pathology · 2015 · 12 citations · 16 references
MedicineOncologyPathologyCellular PathologyCytopathologyTumor PathologyBiomarkers In PathologyCancer BiomarkersTumor CharacterizationTumor CytopathologyTumor GradingTumor MarkersCorrelationHeterogeneityMicroscopic MorphologyNeuroblastoma BiologyPrognostic Tumor MarkersSurrogate Endpoints
Neuroblastoma, the most common extracranial solid tumor in infancy, shows marked biological heterogeneity. Multiple prognostic markers are combined to risk-stratify neuroblastoma patients for treatment. One marker assesses histology, dividing patients into favorable and unfavorable categories based, in part, on the mitosis-karyorrhexis index (MKI). The recommended scoring of 5000 cells is, however, time-consuming and observer-dependent, and accurate counts may not always be performed. In the present study, we investigated using MIB-1 as a surrogate marker for the MKI. Twenty-five cases of neuroblastoma, ranging from low to high MKI, were immunostained for MIB-1. A total of 375 microscopic fields were digitally captured with > 100,000 cells scored. The MIB-1 index was determined by image analysis and MKI, by manual counting of the same immunostained fields. There was a significant correlation between the MIB-1 index and MKI comparing all fields (r = 0.7869, P < 0.01) and an even better correlation comparing individual cases (r = 0.9147, P < 0.01). Using a linear regression model, a formula was generated to calculate MKI from the MIB-1 index as follows: MKI = (MIB-1 index × 0.124) + 1.412. With this formula, a low MKI corresponds to an MIB-1 index < 4.74, intermediate MKI to an MIB-1 index of 4.74 to 20.87, and high MKI to an MIB-1 index > 20.87. For comparison, the calculations were repeated using a manual MIB-1 count on the same images. Similar significant correlations were obtained, with nearly identical cutoff values for MKI categories. This approach can facilitate determination of the MKI by assessing the MIB-1 index, either by image analysis or manual counting.
16
The International Neuroblastoma Pathology Classification (the Shimada system)
Hiroyuki Shimada, Inge M. Ambros, Louis P. Dehner et al. · Cancer · 1999 · 1K citations
Hiroyuki Shimada, Jane Chatten, William A. Newton et al. · JNCI Journal of the National Cancer Institute · 1984 · 869 citations