Risk group assessment and clinical outcome algorithm to predict the natural history of patients with surgically resected renal cell carcinoma

J Clin Oncol. 2002 Dec 1;20(23):4559-66. doi: 10.1200/JCO.2002.05.111.

Abstract

Purpose: To create a comprehensive algorithm that can predict postoperative renal cell carcinoma (RCC) patient outcomes and response to therapy.

Patients and methods: A prospective cohort study was performed with outcome assessment on the basis of chart review of 814 patients who underwent nephrectomy between 1989 and 2000. At diagnosis, M1 or N1/N2M0 metastatic disease (M) was present in 346 patients (43%), whereas 468 patients had no metastatic disease (NM) (N0M0). On the basis of UCLA Integrated Staging System category and the presence of metastases, patients were divided into low-risk (LR), intermediate-risk (IR), and high-risk (HR) groups. Decision boxes integrating tumor-node-metastasis staging, tumor grade, and performance status were compiled for determining a patient's risk group.

Results: NM-LR patients had 91% disease-specific survival at 5 years, lower recurrence rate, and better disease-free survival compared with NM-IR and HR patients. Disease progressed in 50% of NM-HR patients. Disease-specific survival of NM-HR patients who received immunotherapy (IMT) for recurrent disease was similar to that of M-LR patients treated with cytoreductive nephrectomy and adjuvant IMT. Time from recurrence to death for NM-HR patients was inferior to that for M-LR patients. After IMT, approximately 25% of M-LR and 12% of M-IR patients had long-term progression-free survival. M-HR patients did poorly despite IMT.

Conclusion: Stratifying RCC patients into high-, intermediate-, and low-risk subgroups provides a clinically useful system for predicting outcome and provides a unique tool for risk assignment and outcome analysis. Subclassifying RCC into well-defined risk groups should allow better patient counseling and identification of both NM-HR subgroups that need adjuvant treatment and nonresponders who need alternative therapies.

MeSH terms

  • Algorithms
  • Carcinoma, Renal Cell / surgery*
  • Disease-Free Survival
  • Humans
  • Kidney Neoplasms / surgery*
  • Nephrectomy*
  • Predictive Value of Tests
  • Prospective Studies
  • Risk Assessment
  • Risk Factors
  • Survival Analysis
  • Treatment Failure
  • Treatment Outcome