Preoperative nomogram predicting 12-year probability of metastatic renal cancer

J Urol. 2008 Jun;179(6):2146-51; discussion 2151. doi: 10.1016/j.juro.2008.01.101. Epub 2008 Apr 18.


Purpose: For patients with renal masses localized to the kidney there is currently no preoperative tool to predict the likelihood of metastatic recurrence following surgical intervention. We developed a predictive model that could be used in the preoperative setting.

Materials and methods: We pooled institutional databases from Memorial Sloan-Kettering and Mayo Clinic, and identified complete data on 2,517 patients with renal masses and no concurrent evidence of metastases who underwent radical or partial nephrectomy. Cox proportional hazard regression analyses were used to model preoperative clinical and radiographic characteristics as predictors for development of metastases following nephrectomy. Internal validation was performed with a statistical bootstrapping technique.

Results: Metastatic recurrence developed in 340 of the 2,517 patients. Median followup for patients without metastatic recurrence was 4.7 years. A nomogram was developed using preoperative characteristics to predict the 12-year likelihood of postoperative metastatic recurrence with a concordance index of 0.80. In contrast, the concordance index of preoperative TNM staging was 0.71. Size of the primary renal mass, evidence of lymphadenopathy or necrosis on preoperative imaging and the mode of presentation were important predictors for the subsequent development of metastases.

Conclusions: We present a preoperative nomogram that accurately predicts the development of metastatic recurrence following nephrectomy. This nomogram may be potentially useful to identify and counsel patients at high risk for recurrence.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Carcinoma, Renal Cell / secondary*
  • Carcinoma, Renal Cell / surgery*
  • Female
  • Humans
  • Kidney Neoplasms / pathology*
  • Kidney Neoplasms / surgery*
  • Male
  • Middle Aged
  • Nephrectomy*
  • Nomograms*
  • Predictive Value of Tests
  • Preoperative Care
  • Time Factors