Computerized Image Analysis of Tumor Cell Nuclear Morphology Can Improve Patient Selection for Clinical Trials in Localized Clear Cell Renal Cell Carcinoma

Recurrence prediction in clear cell renal cell carcinoma using machine learning of quantitative nuclear features

The recurrence of non-metastatic renal cell carcinoma (RCC) may occur early or late after surgery. This study aimed to develop a recurrence prediction machine learning model based on quantitative nuclear morphologic features of clear cell RCC (ccRCC). We investigated 131 ccRCC patients who underwent nephrectomy (T1-3N0M0). Forty had recurrence within 5 years and 22 between 5 and 10 years; thirty-seven were recurrence-free during 5-10 years and 32 were for more than 10 years. We extracted nuclear features from regions of interest (ROIs) using a digital pathology technique and used them to train 5- and 10-year Support Vector Machine models for recurrence prediction. The models predicted recurrence at 5/10 years after surgery with accuracies of 86.4%/74.1% for each ROI and 100%/100% for each case, respectively. By combining the two models, the accuracy of the recurrence prediction within 5 years was 100%. However, recurrence between 5 and 10 years was correctly predicted for only 5 of the 12 test cases. The machine learning models showed good accuracy for recurrence prediction within 5 years after surgery and may be useful for the design of follow-up protocols and patient selection for adjuvant therapy.

External Validation of the 2003 Leibovich Prognostic Score in Patients Randomly Assigned to SORCE, an International Phase III Trial of Adjuvant Sorafenib in Renal Cell Cancer

The 2003 Leibovich score guides prognostication and selection to adjuvant clinical trials for patients with locally advanced renal cell carcinoma (RCC) after nephrectomy. We provide a robust external validation of the 2003 Leibovich score using contemporary data from SORCE, an international, randomized trial of sorafenib after excision of primary RCC.

Read how we have shown that the 2003 Leibovich score demonstrates discriminative accuracy in contemporary clear-cell and non–clear-cell RCC patient cohorts, supporting its continued use to guide discussions on patient prognosis and risk-stratification in clinical trials.