Development and validation of an integrated nomogram to predict personalized new baseline functional outcomes after...

Area of Science:

• Nephrology
• Urology
• Surgical Oncology

Background:

• Predicting renal function post-partial nephrectomy (PN) is clinically significant.
• Accurate prediction aids in personalized patient management and treatment planning.

Purpose of the Study:

• To develop a precise nomogram for predicting new baseline renal function after PN.
• The nomogram integrates pre-, intra-, and post-operative variables for personalized prediction.

Main Methods:

• A nomogram was developed using data from 213 PN cases (2014-2017) and validated on a separate cohort (67 patients).
• Multivariate Cox and LASSO regression identified key predictive factors.
• Performance was evaluated using C-index, calibration plots, and decision curve analysis.

Main Results:

• The nomogram identified age, baseline eGFR, RENAL nephrometry score, ischemia time, and acute kidney injury (AKI) as independent predictors.
• The nomogram achieved a C-index of 0.910 in the primary cohort and 0.801 in the validation cohort, demonstrating excellent calibration and clinical utility.

Conclusions:

• The developed nomogram accurately predicts personalized new baseline estimated glomerular filtration rate (eGFR) after PN.
• Early identification of at-risk patients facilitates multi-professional collaboration and timely intervention.