A three-feature prediction model for metastasis-free survival after surgery of localized clear cell renal cell carcinoma

After surgery of localized renal cell carcinoma, over 20% of the patients will develop distant metastases. Our aim was to develop an easy-to-use prognostic model for predicting metastasis-free survival after radical or partial nephrectomy of localized clear cell RCC. Model training was performed on 196 patients. Right-censored metastasis-free survival was analysed using LASSO-regularized Cox regression, which identified three key prediction features. The model was validated in an external cohort of 714 patients. 55 (28%) and 134 (19%) patients developed distant metastases during the median postoperative follow-up of 6.3 years (interquartile range 3.4-8.6) and 5.4 years (4.0-7.6) in the training and validation cohort, respectively. Patients were stratified into clinically meaningful risk categories using only three features: tumor size, tumor grade and microvascular invasion, and a representative nomogram and a visual prediction surface were constructed using these features in Cox proportional hazards model. Concordance indices in the training and validation cohorts were 0.755 +/- 0.029 and 0.836 +/- 0.015 for our novel model, which were comparable to the C-indices of the original Leibovich prediction model (0.734 +/- 0.035 and 0.848 +/- 0.017, respectively). Thus, the presented model retains high accuracy while requiring only three features that are routinely collected and widely available.

Automated summary

The study aimed to develop a prognostic model for predicting metastasis-free survival after surgery of localized clear cell RCC, identifying key features such as tumor size, grade and microvascular invasion. The model demonstrated high accuracy, with concordance indices comparable to existing prediction models.