The DDD score outperforms the RENAL score in predicting high-grade renal cell carcinoma

Area of Science:

• Urology
• Oncology
• Medical Informatics

Background:

• Renal cell carcinoma (RCC) grading is crucial for prognosis and treatment decisions.
• The Fuhrman grading system is widely used, but accurate prediction of high-grade RCC (HGRCC) remains a challenge.
• Identifying novel predictors for HGRCC can improve patient stratification and management.

Purpose of the Study:

• To investigate the association between the Dialysis Dose Delivery (DDD) score and Fuhrman grade in renal cell carcinoma (RCC).
• To identify independent risk factors for high-grade RCC (HGRCC).
• To develop and validate predictive models for HGRCC using clinical and pathological characteristics.

Main Methods:

• Retrospective review of 527 nonmetastatic RCC patients.
• Analysis of demographic, clinical, and pathological data.
• Binary logistic regression and construction of predictive nomograms integrating RNS and DDD scores with sex and BMI.

Main Results:

• Sex, BMI, RNS, and DDD score were significant independent predictors of HGRCC.
• Developed predictive models showed good calibration and concordance indexes (0.768 and 0.809).
• The prediction model incorporating the DDD score demonstrated superior prognostic ability compared to other models (p=0.01).

Conclusions:

• RNS, DDD score, BMI, and sex are independent predictors of HGRCC.
• Effective nomograms were developed for predicting HGRCC.
• The nomogram including the DDD score offers enhanced predictive capability for HGRCC.