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New Prognostic Model More Accurately Predicts Kidney Cancer Recurrence and Survival

Andres F. Correa, MD


Researchers at Fox Chase Cancer Center have developed a predictive model—the ASSURE Kidney Cancer Nomogram—that predicts the risk of a patient’s kidney cancer coming back as well as their survival more accurately than other models currently in use. This important tool is the first to be based on data from an international randomized trial of nearly 2,000 patients led by physicians at Fox Chase.

Accurately predicting early disease progression helps identify which patients need to be followed more closely and potentially treat with adjunctive therapies. More importantly, it can spare some patients from unnecessary treatments and follow-up visits.

The American Joint Committee on Cancer tumor-node-metastasis (TNM) staging system is the foundation of cancer risk stratification. However, the TNM staging system is broad and groups patients into large categories, which means that predictions about their cancer progression are not individualized.

To try and improve accuracy for individual patients, statistical models have been developed to incorporate patients’ individual clinical and tumor characteristics—like a patient’s age and their tumor histology and grade—into the prediction model.

These models fall short in that they rely on retrospective data, which is prone to errors due to the lack of standardization in the reporting of tumor characteristics and definitions of recurrence, according to Andres F. Correa, MD, an assistant professor in the Division of Urology and Urologic Oncology at Fox Chase. Moreover, the data utilized to create this model was built based on the oncological outcomes of patients treated over many years, even decades—yet medicine and treatment options are continually advancing, adding significant bias to the predictions obtained from these models.

“When we carefully analyzed the most commonly utilized models for prediction of renal carcinoma recurrence and validated them using the ASSURE data set, we showed that the current models are actually not that superior to standard TNM staging,” Correa said.

Robert G. Uzzo, MD, MBA, FACS

To get rid of these biases and improve accuracy, Correa, along with Robert G. Uzzo, MD, MBA, FACS, interim CEO and chair of the Department of Surgical Oncology at Fox Chase and other ASSURE collaborators, developed the ASSURE RCC Prognostic Nomogram using data from the ASSURE trial. ASSURE was a phase-3 trial that assessed the efficacy of adjuvant-targeted therapy in patients with resected intermediate- and high-risk localized kidney cancer. By using clinical trial data, the researchers ensured that—unlike other models—all inputs into this model were standardized and treatment options did not vary over time.

The ASSURE model yields three predictions for patients who have undergone surgery for localized kidney cancer: progression-free survival, overall survival, and early disease progression. The model incorporates vascular invasion, histology, tumor size, tumor grade, tumor necrosis, and nodal involvement.

Most other models considered only a single cancer histology. The new model encompasses all possible histologies for kidney cancer. In fact, of the six factors included in the ASSURE model, tumor histology was found to be the strongest predictor of disease-free survival.

Finally, the researchers developed their model so that it does not require a patient’s TNM stage as a variable. Eliminating this variable makes the model easier to use in the future because TNM staging changes over time due to advances in science and changes in the disease.

The ASSURE RCC Prognostic Nomogram can be publicly accessed on the Fox Chase Cancer Nomograms website.

The model’s development is detailed in the paper “Predicting Disease Recurrence, Early Progression, and Overall Survival Following Surgical Resection for High-Risk Localized and Locally Advanced Renal Cell Carcinoma,” which was published in European Urology.