An artificial intelligence-based imaging analysis could serve as an aid in surgical planning for patients with kidney tumors.

A method to address discrepancies between predicted biological age and actual chronological age has been validated as a biomarker in predicting OS.

Current risk stratification models perform well in assessing recurrence risk in patients with non-clear cell renal cell carcinoma, researchers report.

After nephron-sparing treatment for RCC, patients with local recurrence had a higher mortality risk than patients without recurrence.

An AI-based model for analyzing images appeared better able to predict ccRCC from CT-based images than a tumor size-based model was.

In patients with renal cell carcinoma, greater abdominal adiposity and lower skeletal mass are associated with aggressive pathology.

Oncocytomas, oncocytic neoplasms of low malignant potential, and lower-stage chromophobe RCC do not recur with prolonged follow-up.

More than a quarter of patients with renal cell carcinoma on active surveillance experience spontaneous tumor regression, researchers report.

Cabozantinib has shown efficacy in the treatment of renal cell carcinoma with non-locally pretreated brain metastases, researchers report.

Researchers examined the association between BMI trajectory and outcomes in RCC, finding worse OS in patients who lost weight after diagnosis.

These findings support the potential of AI-driven histopathological analysis as a biomarker in melanoma,” study researchers wrote.

The panel is able to independently predict metastasis, local recurrence, and overall survival in patients with cutaneous squamous cell carcinoma, researchers reported.