title: MIB-1 Index as a Surrogate for Mitosis-Karyorrhexis Index in Neuroblastoma.
abstract: 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.
authors.affiliation: *Department of Pathology §Chulalongkorn GenePRO Center, Research affairs, Faculty of Medicine, Chulalongkorn University †Faculty of Science and Technology, Rajamangala University of Technology Phra Nakhon, Bangkok, Thailand ‡Division of Pathology, Hospital for Sick Children ∥Department of Pathology and Laboratory Medicine, University of Toronto, Toronto, ON, Canada.
authors.forename: Taywin
authors.initials: T
authors.lastname: Atikankul
authors.forename: Yupapin
authors.initials: Y
authors.lastname: Atikankul
authors.forename: Sakun
authors.initials: S
authors.lastname: Santisukwongchote
authors.forename: Paula
authors.initials: P
authors.lastname: Marrano
authors.forename: Shanop
authors.initials: S
authors.lastname: Shuangshoti
authors.forename: Paul S
authors.initials: PS
authors.lastname: Thorner
mesh_terms: D000974:Antibodies, Antinuclear; D000911:Antibodies, Monoclonal; D057205:Automation, Laboratory; D002675:Child, Preschool; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007150:Immunohistochemistry; D007223:Infant; D019394:Ki-67 Antigen / Q000032:analysis*; D016014:Linear Models; D008938:Mitosis; D008940:Mitotic Index; D009447:Neuroblastoma / Q000737:chemistry* / Q000473:pathology*; D011237:Predictive Value of Tests; D011379:Prognosis
chemical_list: D000974:Antibodies, Antinuclear; D000911:Antibodies, Monoclonal; D019394:Ki-67 Antigen; C440408:MIB-1 antibody