Significant Estimated Glomerular Filtration Rate Reduction After Robotic Partial Nephrectomy
This online nomogram predicts the loss of renal function after partial nephrectomy for renal cancer.
Research authors: Alberto Martini, Shivaram Cumarasamy, Alp Tuna Beksac, Romney Abaza, Daniel D. Eun, Akshay Bhandari, Ashok K. Hemal, James R. Porter, Ketan K. Badan
Details Formula Study characteristics Files & References
Model author
Model ID
Revision date
MeSH terms
  • Nephrectomy
  • Kidney Cancer
  • Renal Cancer
  • Acute Kidney Injury
  • Chronic Kidney Disease
  • Model type
    Cox regression (Calculation)
    No Formula defined yet
    Condition Formula

    Additional information

    The model was developed using data from 999 patients who underwent robot-assisted partial nephrectomy (RAPN). In total, 146 patients experienced significant eGFR reduction. 

    The model was fitted using cox-regression and was validated using leave-one-out cross validation

    Study Population

    Total population size: 999
    Males: {{ model.numberOfMales }}
    Females: {{ model.numberOfFemales }}

    Continuous characteristics

    Name LL Q1 Median Q3 UL Unit
    Age 51 61 68 years
    Body Mass Index 26 29 34 kg/m2
    Baseline eGFR 66 82 96 ml/min/1.73m2
    RENAL score 6 7 9 points
    Ischemia time 11 15 20 min

    Categorical characteristics

    Name Subset / Group Nr. of patients
    Race Caucasian 908
    African American 64
    Other 27
    Hypertension No 565
    Yes 426
    Charlson Comorbidity Index 0 516
    1 253
    2 153
    3 53
    ≥4 24
    Baseline GFR category 1 358
    2 459
    3a 127
    3b 46
    4 9
    Acute Kidney njury No 805
    Yes 195
    Pathological T stage 1a 798
    1b 141
    2a 10
    2b 2
    3a 48

    Related files

    Risk for ≥25% reduction from baseline estimated glomerular filtration rate is:

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    Risk for ≥25% reduction from baseline estimated glomerular filtration rate is:

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    Outcome stratification

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    Conditional information

    Result interpretation

    The nomogram predicts significant eGFR reduction ≥25% from baseline in the time-frame between 3 and 15 months after robot-assisted partial nephrectomy. 

    On internal validation, the model showed a c-statistic of 0.73

    Decision curve analysis (see image below) showed that the model contributes to clinical benefits with probabilities ≥4%

    To improve medical decision making, this model requires external validation and should be validated in open and laparoscopic patients as well. 

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    Calculations alone should never dictate patient care, and are no substitute for professional judgement. See our full disclaimer.

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