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Risk Group Assessment and Clinical Outcome Algorithm to Predict the Natural History of Patients With Surgically Resected Renal Cell Carcinoma

From the Division of Urologic Oncology, Department of Urology, University of California School of Medicine, Los Angeles, CA.

Address reprint requests to Arie S. Belldegrun, MD, Department of Urology, University of California School of Medicine, 10833 Le Conte Ave, Rm 66-118 CHS, Los Angeles, CA 90095-1738; email: abelldegrun{at}mednet.ucla.edu

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
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.

	INTRODUCTION

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THE NATURAL HISTORY of renal cell carcinoma (RCC) is complex and is influenced by factors other than pathologic stage.¹ Patient- and tumor-related factors have been proposed as prognostic factors.^2-4 It is clear that the clinical behavior of RCC results from complex interactions between multiple prognostic factors. This realization has led to an increasing interest in integrated staging systems that predict outcome.^5,6 In a previous publication,⁶ we reported a novel staging system (UCLA Integrated Staging System [UISS]) that predicts patient survival by integrating the 1997 tumor-node-metastasis stage, Fuhrman’s grade, and Eastern Cooperative Oncology Group (ECOG) performance status (PS) into five categories. On the basis of the Cox model, these five categories (defined by criteria listed in Table 1) were found to faithfully stratify patients into distinct survival groups. The UISS was internally validated using a bootstrap technique. The system is versatile and flexible enough to tie together metastatic and nonmetastatic patients into the same integration. Recently, we validated the UISS again using an expanded database of patients treated at the multidisciplinary Kidney Cancer Program at the University of California, Los Angeles (UCLA) between 1989 and 2000.⁷

In this analysis, we used the UISS to create a simple and comprehensive clinical algorithm capable of predicting relevant end points for both localized and metastatic patients. This algorithm integrates the complex interaction of multiple prognostic variables to generate a simple method of stratifying patients into risk groups and prognosticate outcome and survival. Furthermore, our integrated system allows assessment of risk and survival of multiple points along the course of the disease such as at time of nephrectomy, time of recurrence, and on completion of immunotherapy.

	PATIENTS AND METHODS

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After study protocol (99-233) approval by the UCLA Institutional Review Board, a prospective cohort study was performed with outcome assessment on the basis of chart review of demographic, clinical, and pathologic data in patients with RCC treated at UCLA. Patients with bilateral disease were not included on this study. Between 1989 and 2000, 892 patients underwent nephrectomy for unilateral RCC at the UCLA Medical Center. Seventy-eight patients were excluded from the study because of either loss to follow-up (n = 10) or missing data (n = 68). The remaining 814 patients were the principal study population of this report.

At the time of diagnosis, 468 (58%) patients had no evidence of metastasis (N0M0) and 346 (42%) patients had nodal and/or distant metastasis (N1, N2, or M1). The median follow-up for patients alive at last follow-up was 30 months. The median time to death was 16 months. Fourteen nonmetastatic patients (4%) died of their disease, but the date of recurrence was missing. These patients were selectively excluded from the estimates of recurrence-free survival.

Stage was determined according to the 1997 UICC tumor-node-metastasis classification of malignant tumors.¹¹ Tumor stage was determined from surgical pathology. Node and metastasis stages were determined by clinical and/or pathologic data. RCCs were classified and graded according to the current consensus standards¹² by a small group of experienced pathologists. ECOG PS was determined at initial presentation and at each follow-up. UISS category⁶ was determined for each patient.

Patients were divided into two groups: those with no metastasis at diagnosis (designated NM) and those with nodal and/or distant metastasis at diagnosis (designated M). Five UISS categories were possible in NM patients, but only four UISS categories (II to V) were possible in M patients because, by definition, all category I patients are nonmetastatic (Table 1). UISS categories were converted into risk groups (low, intermediate, and high) defined by the 1997 tumor-node-metastasis classification, Fuhrman’s grade, and ECOG PS (Table 1). The number of subjects in each individual combination of tumor-node-metastasis stage, grade, and ECOG PS, listed in Table 1, was assessed. Categories containing fewer than 10 subjects were combined. As a result, two decision boxes were compiled for NM and M patients separately in order to permit a simple algorithmic assignment of patients into risk groups. Clinically relevant end points were determined and calculated for NM and M patients separately in order to provide a profile of outcomes that are relevant for each population of patients for prognostication, patient care, and education. Clinical end points were postulated for NM and M subjects stemming from the differences in the relevant parameters of interest of each group.

Nonmetastatic Patients
Clinical end points for patients without metastasis were overall survival, disease-specific survival, freedom from recurrence (local, systemic, or both), percentage of patients with recurrence that undergo IMT, time from recurrence to IMT, survival after IMT for early recurrence ( 6 months after nephrectomy), and survival after IMT for late recurrence (> 6 months after nephrectomy). These parameters were chosen in order to supply the user with a relevant data set to evaluate patients at clinical milestones: presurgical and postsurgical counseling and counseling on recurrence with maximal treatment possible.

Metastatic Patients
Clinical end points for patients with metastasis were overall survival, disease-specific survival, local recurrence, percentage of patients undergoing IMT, time from nephrectomy to IMT, survival after IMT, and freedom from progression after IMT. Survival was calculated from each of the following events: date of nephrectomy, date of recurrence, and date when immunotherapy was completed. The survival end point was date of death or date of last follow-up. Time from IMT to last follow-up or death was calculated starting from the date that IMT was completed.

Statistical Analysis
Survival was determined by the product-limit method of Kaplan-Meier. Comparisons between groups were performed by the log-rank method to assess the significance of the Kaplan-Meier curves; ² and Student’s t test were used when indicated. Data were analyzed using Stata version 7.0 (Stata Corp, College Station, TX).

	RESULTS

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The stratification trend across all five UISS categories and the difference between each of the UISS categories was statistically significant for both disease-specific and overall survival.⁶ The risk groups were developed on the basis of the following process: T4N0M0 patients in UISS category IV (n = 5) were combined with NM UISS category III. The overall survival of T4N0M0 patients was inferior to the rest of the high-risk NM patients (P = .045) (Table 1). No T4N0M0 patients fell into UISS V. Patients with T1 to 3N1M0, grade 2 to 4, and ECOG PS 1 (UISS III) were recategorized into UISS II because they had a prognosis similar to patients with T1 to 3N1M0 and ECOG PS = 0 (Table 1). The groups marked with an asterisk in Table 1 had less than 10 patients and were combined with adjacent groups to create three risk groups (low, intermediate, and high) for both M and NM patients. Of 486 NM patients, 128 (27%) were low-risk (NM-LR), 190 (41%) were intermediate-risk (NM-IR), and 150 (32%) were high-risk (NM-HR) patients. Of 346 M patients, 49 (14%) were low-risk (M-LR), 271 (78%) were intermediate-risk (M-IR), and 26 (8%) were high-risk (M-HR) patients. The disease-specific survival of M and NM patients stratified into low-, intermediate-, and high-risk groups is shown in Fig 1. Defining characteristics of the UISS categories (1997 tumor-node-metastasis stage, Fuhrman’s grade, and ECOG PS; Table 1) were used to develop a decision box that guides the user to the patient’s UISS risk group. A separate decision box was developed for NM (Fig 2A) and M (Fig 2B) patients. To predict the outcome of a patient with RCC, three steps must be completed. First, select the decision box that corresponds to the patient’s status at diagnosis (N0M0 or N1/N2/M1). Second, after choosing the appropriate decision box, begin at the top of the decision box and progress downward on the basis of the patient’s stage, Fuhrman’s grade, and ECOG PS. This will guide the user to the patient’s risk group (low, intermediate, or high). Third, once the appropriate risk group has been determined, the patient’s prognosis can be predicted by looking up the relevant outcomes in Tables 2 through 5: overall and disease-specific survival for M and NM patients in Table 2, local and systemic failure for NM patients in Table 3, and the effect of IMT on NM and M patients in Tables 4 and 5.

View larger version (15K): [in this window] [in a new window]   Fig 1. Disease-specific survival of the study population divided into N0M0 (NM) and N1/N2M0 or any M1 (M) patients and into the corresponding risk groups: low-risk (LR), intermediate-risk (IR), and high-risk (HR).

View larger version (34K): [in this window] [in a new window]   Fig 2. Decision box A assigns N0M0 nephrectomized patients into risk groups. Progress from top to bottom using 1977 American Joint Committee on Cancer (AJCC) T stage, Fuhrman’s grade, and ECOG PS. (B) For N1, N2, or M1 patients, start with 1977 AJCC NM stage.

View larger version (12K): [in this window] [in a new window]   Fig 3. Freedom from any failure in N0M0 (NM) patients by UISS risk groups.

View larger version (17K): [in this window] [in a new window]   Fig 4. Freedom from progression after IMT in NM patients who experienced failure 6 months (early) or more than 6 months (late) after nephrectomy.

Seven (5.5%) NM-LR patients experienced failure (all systemically). Three of them were treated with IMT (the IMT response in this group is not indicated because the small number of patients did not permit adequate power for analysis).

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
We developed an algorithm that assigns localized (NM) and metastatic (M) patients with RCC into six UISS-based risk groups, accounting for the interaction of variables that impact survival. For each of the risk groups, a relevant set of clinical outcome data was generated, including overall survival, disease-specific survival, freedom from recurrence in NM patients, outcome after recurrence in NM patients, and freedom from progression in M patients undergoing cytoreductive nephrectomy and IMT. These outcome data can be used to predict the prognosis of other patients.

NM-HR patients have a high systemic failure rate (Table 3), suggesting high risk of occult metastasis at diagnosis (ie, lesions not detected by current imaging modalities). This concept is supported by the fact that NM-HR patients have a survival similar to M-LR patients. Improvements in imaging techniques and biologic markers may help identify patients with minimal metastatic disease.

One would expect a similar survival from time of IMT between NM-HR patients treated with IMT for recurrence and in M-LR patients treated immediately after nephrectomy. Instead, NM-HR patients have a response that more closely resembles M-HR patients, suggesting that NM-HR patients who undergo surveillance after nephrectomy may be undertreated. Of patients treated with IMT for recurrence within 6 months of nephrectomy, none of the NM-IR and NM-HR patients survived for more than 2 years after IMT. Therefore, our results suggest that IMT may not provide a benefit to NM patients whose disease recurs 6 months after nephrectomy. Nevertheless, prospective controlled trails are indicated to determine the role of immediate adjuvant IMT in NM-HR patients. Studies of adjuvant interferon after nephrectomy have failed to demonstrate a benefit over nephrectomy alone.¹³

In 1978, deKernion et al published the UCLA experience with nephrectomy alone in metastatic RCC patients. At that time, the 2- and 5-year survivals were 25% and 13%, respectively.¹⁴ Our findings suggest that M-LR and M-IR patients are better off today in the era of cytoreductive nephrectomy combined with modern IMT because they have a substantial prolongation of life over historic survival rates (P = .03). The same does not hold true for M-HR patients, whose survival in the IMT era is just as poor as in historical series treated with nephrectomy alone (Table 2). A subset of our metastatic patients who underwent nephrectomy and interleukin-2–based immunotherapy were subjected to cross-sectional assessment using health-related quality-of-life (QOL) instruments.¹⁵ Compared with reference populations with chronic medical conditions or nonrenal malignancies, metastatic RCC patients were shown to suffer a transient impairment of QOL during IMT. Furthermore, patients with RCC had better QOL estimates after IMT than patients with other malignancies and a better physical function than patients with congestive heart failure.

The M-LR group is composed of two subsets of patients: N + M0 patients who undergo nephrectomy but receive IMT only on failure and M1 patients who receive IMT immediately after cytoreductive nephrectomy. Our data suggest that the role of immediate IMT after nephrectomy in N1M0 and N2M0 merits prospective evaluation, because it is possible that the outcome of the M-LR N + M0 may be further improved by adjunctive IMT. The improved results for M-LR N + M0 patients of whom the majority had lymph node dissection (Table 5) bring up questions on the therapeutic role and the appropriate extent of cytoreductive lymph node dissection when combined with adjuvant IMT. These questions can only be answered through prospective studies. Recurrences in NM patients arise predominantly at distant sites. Only one (0.4%) NM-IR patient and three (12%) NM-HR patients had disease that recurred only in the regional lymph nodes, suggesting that lymph node dissection may not offer a significant therapeutic advantage. Although these results are supported by Minervini et al,¹⁶ who also suggested that regional node dissection has a limited benefit, more data are needed to address this complex issue.

The algorithm we generated to predict patient outcome might also be used to help formulate follow-up strategies. NM-LR patients may require less intense follow-up than NM-IR and NM-HR patients. In NM patients, more emphasis should be placed on the detection of distant rather than local recurrence. In M-IR and M-HR patients, the local recurrence rate is low because of their short survival; therefore, investigations for local failure may be of limited value in these patients. Monitoring for local failure is more important in M-LR patients because they have a higher local recurrence rate.

There has been a trend toward minimally invasive and nephron-sparing surgical treatments for RCC. These include open partial nephrectomy, laparoscopic radical or partial nephrectomy, and partial renal ablation using cryotherapy and radiofrequency ablation. To adequately assess their efficacy against RCC, these modalities must be compared with conventional surgery. We feel that the current data may help with this comparison because they can be used as a standard control for open radical nephrectomy and can be used to predict local and systemic failure rates for experimental surgical therapies. The local failure rate is approximately 0% in NM-LR tumors ( 7 cm in diameter, grade 1/2, and full performance status at diagnosis) but is 4% and 8.6% in NM-IR and NM-HR tumors, respectively. Even when the complete excision is accomplished, the expected systemic failure rate is 5.5% in NM-LR, 25% in NM-IR, and 38% in NM-HR. More prospective data are required to evaluate the role of minimally invasive and nephron-sparing techniques for cytoreductive surgery before adjuvant IMT, especially in NM-IR patients.

Nevertheless, the minimal rate of local recurrence (0% to 6%) in NM-LR and NM-IR patients suggests that partial nephrectomy should be performed whenever it is technically feasible. When recurrence occurs in these patients, it is usually at distant sites and probably results from aggressive tumor biology or undetected micrometastases at diagnosis rather than from tumor size or penetration of anatomic barriers. The poor prognosis of NM patients who have recurrent disease within 6 months after nephrectomy, even when treated with IMT (Table 4), support this view. A nephron-sparing approach for NM-IR and NM-HR patients may be advantageous because 43 of 190 (23%) and 56 of 150 (37%) patients, respectively, receive IMT for recurrence. Practically, only a small subset of NM-IR and NM-HR patients (those with stage T3a) may be amenable to nephron-sparing surgery using current techniques; however, the outcome of these patients is not well defined, representing a practical dilemma similar to that for patients who undergo partial nephrectomy for clinically T1/T2 N0M0 disease and are found to have a pT3a disease with free surgical margins.

The results of IMT in M-LR and M-IR patients are encouraging. However, the poor results of IMT in M-HR patients raise questions regarding the merit of surgery and IMT in these cases. In patients with impaired ECOG PS and high metastatic burden (N2 or M1), a percutaneous biopsy may be warranted. This biopsy can determine tumor grade and therefore help identify which patents are M-HR. Because M-HR patients have a poor outcome with any therapy, unnecessary treatment can be avoided by identifying them preoperatively. Alternatively, future serum or urinary markers that tightly correlate with the presence of grade 4 RCC may assist in preoperatively selecting M-HR patients.

One limitation of this analysis is that the IMT was administered to our study population using a variety of biologic agents. Analyzing the individual IMT regimens would have resulted in underpowered analysis. In this regard, our results reflect the anticipated outcome with maximal treatment using interleukin-2–based IMT. This study is also limited by its retrospective nature. Furthermore, it represents the experience of a single institution that serves as a tertiary referral center for RCC patients. However, this limitation probably helped add power to our analyses because a large number of patients, including those with unfavorable and metastatic disease, were referred for treatment. As with all database analyses, treatments are not determined by experimental design but by factors such as physician or patient preference.

The creation of the risk categories involved combining some groups with a small sample size or similar survival. It will take a database that is one to two orders of magnitude larger to assign these rare subgroups (Table 1). Although T4N0M0 patients had inferior survival relative to the rest of the NM-HR patients, the survival of these groups did not differ from M-LR patients. Although combining T4N0M0 patients into the NM-HR risk group was ad hoc, simplistic, and perhaps mechanistic, the T4N0M0 patients remain located within the highest NM risk group; therefore, they are still categorized and prognosticated in a fashion similar to historical series.

	REFERENCES

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION REFERENCES

 
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6. Zisman A, Pantuck A, Dorey F, et al: Improved prognostication of RCC using an integrated staging system (UISS). J Clin Oncol 19: 1649-1657, 2001[Abstract/Free Full Text]

7. Zisman A, Pantuck A, Figlin R, et al: Validation of the UCLA integrated Staging System (UISS) for patients with renal cell carcinoma. J Clin Oncol 19: 3792-3793, 2001[Free Full Text]

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Submitted May 16, 2002; accepted August 12, 2002.

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