Prognostic factors in localized renal cell cancer

Transcription

1 Original Article PROGNOSTIC FACTORS IN LOCALIZED RENAL CELL CANCER KNIGHT and STADLER Prognostic factors in localized renal cell cancer David A. Knight and Walter M. Stadler Section of Hematology/Oncology, Department of Medicine, University of Chicago Medical Center, The Pritzker School of Medicine, Chicago, IL, USA KEYWORDS staging system, survival, tumour subtypes, risk groups INTRODUCTION RCC is highly heterogeneous and composed of many histological subtypes associated with widely varying patient outcomes, even in patients with apparently localized disease. For example, the probability of dying from a 2-cm grade 1 clear cell RCC might be 5%, whereas it might approach % for an 8-cm, lymph node positive, grade 4 tumour. Clinical prognostic systems serve several purposes. Perhaps most importantly, they provide patients and their healthcare providers with information on the expected outcome, to plan their personal and medical future. They also help to facilitate comparisons of outcome across different providers. Finally, with the advent of more effective systemic therapies, they will be invaluable for selecting patients for adjuvant clinical trials and will probably be helpful in assessing the relative value of systemic therapy in the peri-operative setting. In this paper the clinical prognostic systems focused on patients with surgically amenable disease will be reviewed. A review of putative molecular prognostic markers is provided by Belldegrun and Pantuck, and prognostic systems more relevant to patients undergoing systemic therapy for metastatic disease are reviewed by Eisen. TRADITIONAL STAGING SYSTEMS The first prognostic systems depended solely on the clinical assessment of disease extent, typically assessed during surgical resection of the primary tumour. The first generally accepted and validated system was the Robson modification of the Flocks and Kadesky system. Until the early 1990s the Robson staging system provided the most reliable prognostic information available [1]. In the Robson system stage 1 tumours are confined to the renal capsule. Stage 2 tumours extend through the renal capsule but do not breach Gerota s fascia. Stage 3 shows local involvement, including the renal vein or inferior vena cava (IVC) in the case of 3a, the hilar lymph nodes in the case of 3b, or both vein and node involvement in 3c disease. Stage 4 tumours show spread to local contiguous organs (4a), excluding the adrenal gland, or to distant sites (4b). Although this system reflects the anatomical extent of disease and can be used to predict prognosis with some accuracy, it has also been shown to correlate poorly with prognosis [2]. For example, patients with stage 3a disease have similar survival to some patients with stage 1 or stage 2 disease. In 1959 the American Joint Committee on Cancer (AJCC) introduced and recommended that all patients with cancer be staged using the TNM system. In this designation, T reflects the extent of the primary tumour, N the extent of regional nodal disease, and M whether metastatic disease is present. The various TNM criteria are then classified as one of four stages reflecting the patient s prognosis (Fig. 1). The AJCC reviews staging and prognosis regularly and the current 6th edition is undergoing review. The TNM staging system has been shown to accurately reflect the prognosis in RCC in many studies [3]. For example, as recently as 2005, Frank et al. [3] reported an independent validation of the 2002 AJCC updated staging system using a single cohort of 2746 patients. Using the Kaplan Meier method, 5-year cancer-specific survival rates were 97% for a, 87% for b, 71% for, 53% for, 44% for b, 37% for, and 20% for tumours. The same study reported an improvement in the 2002 classification over the 1997 system. Furthermore, many studies showed a poorer prognosis associated with locally advanced disease as described by the TNM classification. For example [4] in 2006 it was reported that the relative risk of death from RCC in, b, and disease was compared to disease. The relative risk of death of and N2 disease was 6.77 compared to and Nx disease. Several recent revisions in the AJCC TNM staging system deserve mention, as they reflect the need for continued adjustment with greater understanding of RCC prognosis. First, in an effort to better reflect survival in patients with larger localized tumours, the 1997 TNM system redefined the diameter of tumours from 2.5 cm to 7 cm. This classification was directly compared to the 1987 TNM system and determined to be better at stratifying cases according to survival [5]; Moch et al. [6] found similar results. However, although tumour size is an essential predictor of prognosis, the optimum threshold remains a subject of discussion. Specifically, in 2002, evidence had been growing to show that patients with tumours of <4 cm in diameter had better outcomes than patients with tumours >4 cm. In turn, the smaller tumours had increasingly been treated successfully with nephron-sparing surgery [7]. Therefore, was reclassified into a ( 4 cm) and b (4 7 cm). This change was validated by the study of Frank et al. [3], and in which the predictive ability of the 2002 version was shown to be better than the 1997 system. Another major change introduced with the 1997 version was that patients with tumour thrombus of the IVC above the diaphragm were classified as rather than. Those patients with tumour thrombus below the diaphragm were classified as b rather than. The modified 1997 TNM system was validated by Tsui et al. [8] in 2000, when 5-year cancer-specific survival rates for TNM stages I, II, III and IV were determined to be 91%, 74%, 67% and 32%, respectively, for 643 patients with RCC treated between 1987 and The TNM staging system is the most studied, most commonly implemented, and historically most accurate tool available for predicting RCC prognosis. As described above, several changes have been instituted in 1212 JOURNAL COMPILATION 2007 BJU INTERNATIONAL 99, doi: /j x x

2 PROGNOSTIC FACTORS IN LOCALIZED RENAL CELL CANCER FIG. 1. The TNM staging system. Primary Tumor (T) TX T0 a b Primary Tumor (T) b NX N2 Regional Lymph Nodes (N)* Distant Metastasis (M) MX M1 Tumor extends into major veins or invades adrenal gland or perinephric tissues but not beyond Gerota s fascia Tumor directly invades adrenal gland or perirenal and/or renal sinus fat but not beyond Gerota s fascia Tumor grossly extends into the renal vein or its segmental (muscle-containing) branches, or vena cava below the diaphragm Tumor grossly extends into vena cava above diaphragm or invades the wall of the vena cava Tumor invades beyond Gerota s fascia Regional lymph nodes cannot be assessed No regional lymph node metastases Metastases in a single regional lymph node Metastasis in more than one regional lymph node *Laterality does not affect the N classification. Distant metastasis cannot be assessed No distant metastasis Distant metastasis AJCC Cancer Staging Manual, Sixth Edition Kidney (Sarcomas and adenomas are not included.) Primary tumor cannot be assessed No evidence of primary tumor Tumor 7 cm or less in greatest dimension, limited to the kidney Tumor 4 cm or less in greatest dimension, limited to the kidney Tumor more than 4 cm but not more than 7 cm in greatest dimension, limited to the kidney Tumor more than 7 cm in greatest dimension, limited to the kidney STAGE GROUPING Stage I Stage II Stage III Stage IV b b Any T Any T N2 Any N PERMISSION REQUESTED FROM the American Joint Committee on Cancer (AJCC), Chicago, Illinois. The original source for this material is the AJCC Cancer Staging Manual, Sixth Edition (2002) published by Springer-Verlag New York, PERMISSION PENDING M1 the last two decades to improve this accuracy. Nevertheless, there continue to be debates about the optimum size threshold for defining disease [9,10], and appropriate classification of various degrees of renal vein and IVC involvement by tumour thrombus. Thus, the TNM staging system will probably continue to develop as these and other issues are clarified. More importantly, it is critical when reviewing older reports, conducting retrospective reviews, or reviewing older pathology reports, to specify which version of the TNM staging system is being used. INCORPORATION OF OTHER CLINICAL FACTORS Historically, the pathological extent of disease is the primary characteristic used to determine prognosis in RCC, as reflected by the TNM and Robson staging systems. However, several other factors have been shown to be relevant, and are being increasingly used to determine prognosis. For example, RCC subtypes are related to tumour aggressiveness. Chromophobic RCC, which comprises 5 10% of all RCC, has a better prognosis than other major subtypes [11,12]. This might be because it is genetically related to benign oncocytomas [13,14]. Papillary (chromophilic) RCC, the second most common RCC (10 15%), has been reported to consist of two subtypes, i.e. a more aggressive type 2 and a more indolent type 1 [15,16]. However, not all authors have been able to replicate these findings, nor have all been able to replicate the reported better outcome of papillary vs clear cell carcinomas [7,11,12,17]. Other more rare subtypes have also been reported to have differing prognosis. Collecting-duct (Bellini s) tumour is aggressive and frequently metastatic at the time of diagnosis [18]. A possible subtype of collecting-duct carcinoma is medullary carcinoma, which also has a poor prognosis. These are seen almost exclusively in young individuals with sickle cell trait or disease [19]. On the other hand, the rare multilocular variant of cystic clear cell RCC has been reported to have a favourable prognosis [20]. A more complete discussion of RCC subtypes is provided in reports by Patard et al. [12] and Cheville et al. [11]. It is likely that these various subtypes represent different diseases and as such the prognostic variables identified for the common clear cell RCC might or might not apply. JOURNAL COMPILATION 2007 BJU INTERNATIONAL 1213

3 KNIGHT and STADLER For decades it has been known that histological tumour characteristics were independent prognostic factors in RCC; many studies continue to confirm this. In 1982, Fuhrman et al. [21] determined that nuclear grade was more predictive of developing distant metastases than several other variables, including pathological stage. In 2000, Tsiu et al. [8] reported that 5-year cancer-specific survival rates correlated highly with AJCC histological grade: 89% for grade 1, 65% for grade 2, and 46% for grades 3 and 4. These results were independent of stage. More recently, Leibovich et al. [22] also found that a high nuclear grade was adversely associated with survival, a finding that was successfully incorporated into a scoring algorithm to predict survival for patients with RCC. Other studies have found similar outcomes [17]. Notably, there is some debate about interobserver reproducibility of histological grading [23]. In this context the presence of a sarcomatoid appearance should also be noted. This has been reported to be a poor prognostic factor in several studies and sarcomatoid RCC has occasionally been identified as a specific subtype. In the most recent WHO recommendations, sarcomatoid is not a specific subtype but simply reflects a poorly differentiated tumour whose histological subtype is not readily identifiable. Importantly, the term sarcomatoid or sarcomatoid features is not standardized and designation of a RCC as sarcomatoid is highly variable. Likewise, the presence of tumour necrosis has also been reported to negatively influence survival. Once again, it is difficult to standardize the definition of necrosis or percentage necrosis making it difficult to compare reports from different institutions or pathologists. Nevertheless, these histological characteristics have been incorporated into prognostic scores reported to have greater accuracy than systems, such as the TNM system, that depend mainly on tumour size and extent. As is the case for most (if not all) malignancies, clinical factors play a major role in prognosis for patients with early-stage RCC. Individual patient characteristics can also be incorporated into more conventional prognostic systems like the TNM staging system, thereby enhancing their prognostic accuracy (see below). These sophisticated tools have developed from data obtained by evaluating individual clinical factors independently. As an example, studies have shown that patients with asymptomatic, localized tumours tend to have better outcomes than those presenting with symptoms [14]. Frank et al. [17] also reported an association between the risk of RCCrelated death and the presence of symptoms for patients undergoing nephrectomy. Zisman et al. [23] reported a correlation between performance status and survival for localized RCC. Laboratory studies have also been useful as independent prognostic tools. For example, studies have shown that patients with localized RCC and an elevated platelet count have a worse survival, which remained statistically significant after controlling for other factors [24,25]. Kim et al. [26] reported that systemic symptoms of cachexia, including hypoalbuminaemia, in addition to weight loss, malaise and anorexia, were associated with worse survival. Many of these clinical and laboratory factors, along with the aforementioned histological factors, have led to the development of combined prognostic algorithms involving traditional staging systems, and detailed patient and tumour information. One such approach is the UCLA Integrated Staging System (UISS), which has been validated in several data sets. In this system the TNM stage, Fuhrman s histological tumour grade, and Eastern Cooperative Oncology Group performance status of 661 patients undergoing nephrectomy were used to develop a tool for predicting survival. Using these three characteristics, five survival stratification groups (UISS I-V) were created using univariate and multivariate analysis. Projected 5-year survival for the groups were 94% (I), 67% (II), 39% (III), 23% (IV) and 0% (V). In differentiating patient survival, the UISS system was better than stage alone [23]. The system was subsequently validated internally with an expanded database [27]. The same institution subsequently created a comprehensive clinical algorithm capable of predicting outcomes and response to therapy. Specifically, 814 patients who had nephrectomy were categorized as low-, intermediate- and high-risk groups based on their UISS stage and whether or not they had metastases. The algorithm was able to predict relevant endpoints for both localized and metastatic patients. For example, localized low-risk patients had 91% disease-specific survival at 5-years and had lower recurrence rates and better disease-free survival rates than intermediate- and high-risk patients [28]. An international multicentre study evaluating 4200 patients also validated this system [29]; e.g. for localized RCC the 5-year survival rates were 92%, 67%, and 44% for low-, intermediate- and high-risk groups, respectively. A second example that illustrates the integrated approach to RCC prognosis was developed at Memorial Sloan-Kettering Cancer Center. Early studies focused on metastatic RCC patients and will not be discussed here. However, in 2001, in an effort to predict long-term disease-free survival in patients with resected RCC, a simple nomogram was reported that predicted the likelihood of recurrence within 5 years after resection, based on several clinicopathological features including patient symptoms, histology, tumour size and pathological stage. Several modelling techniques were used and the predictions by nomogram appeared to be accurate (area under the receiver operating characteristic curve 0.74) [30]. In an effort to improve on their model, a revised postoperative nomogram for freedom from recurrence was reported on clear cell RCC, using pathological stage, Fuhrman grade, tumour size, necrosis, vascular invasion, and clinical presentation [14]. The tumour characteristics included were meant to more accurately reflect important prognostic variables reported previously. Notably, the model was externally evaluated using a validation cohort of 200 patients from Columbia. The concordance index (CoI) for the nomogram was 0.82 and thus more accurate than the previous nomogram. The CoI reflects the predictive accuracy of prognostic algorithms, where a value of 1.0 represents perfect accuracy and a score of 0.5 is consistent with random chance. The Mayo clinic in 2002 [17] reported the SSIGN (Stage, Size, Grade, Necrosis) scoring algorithm, an outcome prediction model for patients with clear cell RCC treated with radical nephrectomy. They evaluated 1800 patients and examined several clinical and pathological features at the time of diagnosis, using variables multivariately associated with RCC-related death in developing the model. Cancer-specific survival was estimated for up to 10 years of follow-up, and the predictive ability of the model was evaluated using the CoI; this was 0.84 and was validated internally using bootstrap methods. Subsequent work 1214 JOURNAL COMPILATION 2007 BJU INTERNATIONAL

4 PROGNOSTIC FACTORS IN LOCALIZED RENAL CELL CANCER has been reported in patients with metastatic RCC, which will be addressed elsewhere. Molecular technology has brought new excitement and tremendous potential to the field of prognosis. These topics will be reviewed in detail in the chapter by Belldegrun and Pantuck on molecular staging. CONCLUSION The ability to accurately predict patient outcomes is an important goal in kidney cancer. This ability will allow us to fully inform patients about their prognosis, which will permit them to make educated decisions about therapy. It also will allow us, as physicians, to stratify patients into categories that will help us to make consistent decisions about follow-up, surveillance and treatment. Also, we will be able to better direct patients into appropriate clinical trials as our understanding about a particular patient s prognosis becomes more certain. As we continue to consolidate all of the accumulating prognostic data available, from the original pathological staging systems to the future of molecular prognostic technology, we will be closer to accomplishing these goals. CONFLICT OF INTEREST None declared. REFERENCES 1 Lane BR, Kattan MW. Predicting outcomes in renal cell carcinoma. Current Opin Urol 2005; 15: Pantuck AJ, Zisman A, Belldegrun AS. The changing natural history of renal cell carcinoma. J Urol 2001; 166: Frank I, Blute ML, Leibovich BC, Cheville JC, Lohse CM, Zincke H. Independent validation of the 2002 American Joint Committee on cancer primary tumor classification for renal cell carcinoma using a large, single institution cohort. J Urol 2005; 173: Ficarra V, Martignoni G, Lohse C et al. External validation of the Mayo Clinic Stage, Size, Grade and Necrosis (SSIGN) score to predict cancer specific survival using a European series of conventional renal cell carcinoma. 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5 KNIGHT and STADLER history of patients with surgically resected renal cell carcinoma. J Clin Oncol 2002; 20: Patard JJ, Kim HL, Lam JS et al. Use of the University of California Los Angeles Integrate Staging system to predict survival in renal cell carcinoma: an international multicenter study. J Clin Oncol 2004; 22: Kattan MW, Reuter V, Motzer RJ, Katz J, Russo P. A postoperative prognostic nomogram for renal cell carcinoma. J Urol 2001; 166: 63 7 Correspondence: Walter M. Stadler, University of Chicago Medical Center, Department of Medicine, Section of Hematology/Oncology, The Pritzker School of Medicine, 5841 South Maryland Avenue, MC 2115, Chicago, IL , USA. wstadler@medicine.bsd.uchicago.edu Abbreviations: IVC, inferior vena cava; AJCC, American Joint Committee on Cancer; UISS, UCLA Integrated Staging System; CoI, concordance index JOURNAL COMPILATION 2007 BJU INTERNATIONAL