R Román1, M Verdú1,3, M Calvo 4, A Vidal3,5,,X Sanjuan 5, M Jimeno6, A Salas7, J Autonell 8, I Trias9, M González1, B García1, N Rodón1 and X Puig1,2,3.
1BIOPAT.Biopatologia Molecular, Barcelona, Spain; 2Hospital de Barcelona, Barcelona, Spain; 3Histopat Laboratoris, Barcelona, Spain; 4Statistics Department, Universitat de Barcelona, Barcelona, Spain; 5Hospital Universitari de Bellvitge, Barcelona, Spain; 6Hospital del Mar, Barcelona, Spain; 7Hospital Mútua de Terrassa, Terrasa, Spain; 8Hospital General de Vic, Vic, Spain and 9Hospital Plató, Barcelona, Spain.
High microsatellite instability (MSI-H) allows the identification of a subset of colorectal carcinomas associated with good prognosis and a higher incidence of Lynch syndrome. The aim of this work was to assess the interobserver variability and optimize our MSI-H prediction model previously published based on phenotypic features. The validation series collected from five different hospitals included 265 primary colorectal carcinomas from the same number of patients. The eight clinicopathological parameters that integrate our original model were evaluated in the corresponding centers. Homogeneity assessment revealed significant differences between hospitals in the estimation of the growth pattern, presence of Crohn-like reaction, percentage of cribriform structures, and Ki-67 positivity. Despite this observation, our model was globally able to predict MSI-H with a negative predictive value of 97.0%. The optimization studies were carried out with 615 cases and resulted in a new prediction model RERtest8, which includes the presence of tumor infiltrating lymphocytes at the expense of the percentage of cribriform structures. This refined model achieves a negative predictive value of 97.9% that is maintained even when the immunohistochemical parameters are left out, RERtest6. The high negative predictive value achieved by our models allows the reduction of the cases to be tested for MSI to less than 10%. Furthermore, the easy evaluation of the parameters included in the model renders it a useful tool for the routine practice and can reinforce other published models and the current clinical protocols to detect the subset of colorectal cancer patients bearing hereditary nonpolyposis colorectal cancers risk and/or MSI-H phenotype.