Other Genomic Models

Another model frequently used for prognostication in the metastatic RCC space is the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model, but the model is also based on clinical and laboratory correlates.4 This model was used to show that a 34-gene expression signature (ClearCode34) could improve the scheme’s accuracy. But this was undertaken in only 54 patients who were treated with tyrosine kinase inhibitors, and the tumors were analyzed as part of The Cancer Genome Atlas project.5


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Another model analyzed data from 343 patients from a placebo-controlled pazopanib registration study. In this study, measurement of 3 circulating markers (osteopontin, interleukin 6, and metalloproteinase inhibitor 1) along with 5 clinical variables performed better than the IMDC model.6

However, neither of these 2 models were independently validated.

Commentary from Invited Experts

The authors of an accompanying commentary agreed that the addition of the mutation status of the 3 genes added to the prognostic value of the MSKCC model, and that the addition of another risk category to the model improved patient distribution across the risk strata.7

They commented that prognostic models have a role in counseling patients and in designing clinical trials by providing estimates for OS and noted that currently, risk categorization has moved into treatment algorithms.7 Indeed, the combination of ipilimumab and nivolumab is indicated for the initial treatment of patients with intermediate- or poor-risk metastatic RCC.8

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Currently, the MSKCC risk model and the IMDC model use clinical and laboratory parameters for risk stratification. With the increasing use of comprehensive genomic profiling in the clinic and with the associated costs of sequencing decreasing, “now is an opportune time to integrate tumor mutational status into these prognostic models,” the authors of the commentary note.7