Elsevier

European Urology

Volume 55, Issue 2, February 2009, Pages 287-295
European Urology

Platinum Priority – Kidney Cancer
Editorial by Christian Bolenz and Yair Lotan on pp. 296–298 of this issue
A Preoperative Prognostic Model for Patients Treated with Nephrectomy for Renal Cell Carcinoma

https://doi.org/10.1016/j.eururo.2008.07.037Get rights and content

Abstract

Background

Currently two pretreatment prognostic models with limited accuracy (65–67%) can be used to predict survival in patients with localized renal cell carcinoma (RCC).

Objective

We set out to develop a more accurate pretreatment model for predicting RCC-specific mortality after nephrectomy for all stages of RCC.

Design, setting, and participants

The data originated from a series of prospectively recorded contemporary cases of patients treated with radical or partial nephrectomy between 1984 and 2006. Model development was performed using data from 2474 patients from five centers and external validation was performed using data from 1972 patients from seven centers.

Measurements

The probability of RCC-specific mortality was modeled using Cox regression. The significance of the predictors was confirmed using competing risks analyses, which account for mortality from other causes.

Results and limitations

Median follow-up in patients who did not die of RCC-specific causes was 4.2 yr and 3.5 yr in the development and validation cohorts, respectively. The freedom from cancer-specific mortality rates in the nomogram development cohort were 75.4% at 5 yr after nephrectomy and 68.3% at 10 yr after nephrectomy. All variables except gender achieved independent predictor status. In the external validation cohort the nomogram predictions were 88.1% accurate at 1 yr, 86.8% accurate at 2 yr, 86.8% accurate at 5 yr, and 84.2% accurate at 10 yr.

Conclusions

Our model substantially exceeds the accuracy of the existing pretreatment models. Consequently, the proposed nomogram-based predictions may be used as benchmark data for pretreatment decision making in patients with various stages of RCC.

Introduction

Currently, two pretreatment prognostic models address the natural history of treated renal cell carcinoma (RCC) [1], [2]. Both predict disease recurrence after nephrectomy. Unfortunately, both are limited by relatively low accuracy (65% and 67%), which undermines the usefulness of their predictions [1], [2]. Moreover, both are limited to predictions in patients with localized RCC. To circumvent the limitations related to stage and accuracy and to address mortality, which represents a more definitive end point, we developed and internally validated a pretreatment nomogram predicting freedom from RCC-specific mortality using data from a large multi-institutional cohort. Subsequently, we used an independent validation cohort to test the accuracy of this pretreatment nomogram.

Section snippets

Study cohort

Five participating institutions contributed data from a total of 2485 patients at various stages of RCC between 1984 and 2006; this constituted the nomogram development cohort. Data from an additional 1978 patients from seven institutions were included in the external validation cohort. All patients were treated with either open radical or partial nephrectomy. All preoperative data were prospectively gathered at each center. Patient age, gender, clinical stage, presence of metastases, tumor

Results

The descriptive statistics of the nomogram development and the external validation cohorts are listed in Table 1. Within the development cohort, 650 patients (26.3%) and 565 patients (22.8%) had tumors classified as T1a and T1b. Tumor size ranged from 0.5 cm to 25 cm (mean, 6.6 cm). Metastatic disease at presentation was present in 295 patients (11.9%). Local symptoms were present in 897 patients (35.5%) versus systemic symptoms present in 453 patients (18.3%). Table 1 demonstrates minor

Discussion

Over the past 2 decades, the management options for patients with RCC of all stages have increased exponentially [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]. Despite the abundance of treatment modalities, only two prognostic models are available to assist clinicians and patients with treatment choices before therapy is determined. Both models are limited to patients with clinically localized (T1 or T2) disease [1], [2] and provide very limited accuracy (65% and

Conclusions

The current nomogram represents the most contemporary and the most accurate pretreatment prognostic model for prediction of RCC-specific mortality from 1 yr to 10 yr after nephrectomy. Its predictions may be used to provide a framework for comparisons between nephrectomy and alternative treatment modalities for all stages of RCC.

References (30)

  • C. Terrone et al.

    The role of pathology for clinical decision-making in renal cell carcinoma is increasing

    Eur Urol

    (2007)
  • I. Frank et al.

    A multifactorial postoperative surveillance model for patients with surgically treated clear cell renal cell carcinoma

    J Urol

    (2003)
  • K.R. Han et al.

    Validation of an integrated staging system toward improved prognostication of patients with localized renal cell carcinoma in an international population

    J Urol

    (2003)
  • L. Cindolo et al.

    A preoperative clinical prognostic model for non-metastatic renal cell carcinoma

    BJU Int

    (2003)
  • P.M. Grambsch et al.

    Diagnostic plots to reveal functional form for covariates in multiplicative intensity models

    Biometrics

    (1995)
  • Cited by (113)

    • Survival benefits analyses of T1a renal cell carcinoma patients treated with microwave ablation

      2021, European Journal of Radiology
      Citation Excerpt :

      According to the above results, for T1a RCC patients older than 75 years or with an age-adjusted CCI score ≥ 7 or with tumour protruding into the renal pelvis, thermal ablation can produce compromised OS or PFS outcomes due to high non-RCC mortality or RCC progression risk. Age and tumour size are generally accepted as survival prognostic indicators for RCC patients after nephrectomy, regardless of whether the RCC is localised (0.5 cm) or of the stage[26,27]. Ristau BT and Poletajew S et al. reported that the benefits in OS and CSS were attenuated for both partial nephrectomy and radical nephrectomy in patients older than 75 years[24,28].

    • Preoperative nomogram predicting 12-year probability of metastatic renal cancer – evaluation in a contemporary cohort

      2020, Urologic Oncology: Seminars and Original Investigations
      Citation Excerpt :

      Preoperative risk stratification can identify high-risk patients who are suitable candidates for neoadjuvant trials [5]. Current preoperative predictive models rely on patient and tumor characteristics on imaging to predict the risk of metastases and cancer related mortality after nephrectomy [6–13]. In a previous publication from the Mayo Clinic and our center, Raj et al. reported a preoperative nomogram for predicting the 12-year metastatic free probability (MFP) for patients with localized renal tumors.

    • Evaluation of a renal cyst/mass

      2019, Onco-Nephrology
    View all citing articles on Scopus
    View full text