Prognostic Factors: Does It Really Matter if New Drugs for Targeted Therapy Will Be Used?

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1 european urology supplements 8 (2009) available at journal homepage: Prognostic Factors: Does It Really Matter if New Drugs for Targeted Therapy Will Be Used? Sümer Baltacı * Department of Urology, University of Ankara School of Medicine, Ek bina, M2, 06100, Sıhhıye, Ankara, Turkey Article info Keywords: Prognostic factors Renal cell carcinoma Survival Targeted therapy Abstract Context: For many years, cytokines have been utilised in treatment of metastatic renal cell carcinoma (mrcc), with limited response rates and significant side-effects. Recently, several targeted agents have demonstrated clinical efficacy in the treatment of mrcc. Objective: To discuss the applicability of previously described prognostic factors in patients with mrcc who are starting targeted therapy. Evidence acquisition: Clinical data on prognostic factors and patient stratification strategies are reviewed. Evidence synthesis: During the cytokine era, time from diagnosis to treatment, Karnofsky performance status (PS), serum lactate dehydrogenase, corrected serum calcium, and haemoglobin were the identified prognostic factors, and risk group stratifications derived from these criteria represent a standard. In contrast, the results of some studies during the targeted therapy era revealed that prognostic factors and models that were described prior to the availability of novel agents may not be entirely applicable to patients with mrcc who are starting vascular endothelial growth factor (VEGF) targeted therapy. This is important because many trials evaluating these novel agents have stratified patients using outdated models from the cytokine era. More recent prognostication models include nomograms, and they are designed to individualise therapy to improve clinical efficacy. Conclusions: Prognostic factors and patient stratification strategies for the treatment of mrcc are reviewed in the context of available clinical data. Development of reliable prognostication models or nomograms requires reassessment of clinical and biologic features of mrcc patients that are predictive of outcome. # 2008 European Association of Urology. Published by Elsevier B.V. All rights reserved. * Tel ; Fax: address: sbaltaci@hotmail.com. 1. Introduction Renal cell carcinoma (RCC) accounts for about 2 3% of all human malignancies, and > patients worldwide are diagnosed with RCC each year [1 3]. Nearly 20 30% of patients are diagnosed with metastatic disease, and a high proportion of patients (approximately 20%) with localised disease /$ see front matter # 2008 European Association of Urology. Published by Elsevier B.V. All rights reserved. doi: /j.eursup

2 european urology supplements 8 (2009) subsequently develop metastases, despite undergoing nephrectomy with curative intent [4]. For several decades, cytokine therapy with interferon-a (IFN-a) and interleukin-2 (IL-2) was the only treatment option available for patients with metastatic RCC (mrcc); however, few patients achieved complete cure by receiving immunotherapy. A recent Cochrane analysis reported that the application of IFN-a led to a median overall chance of partial remission or complete remission of only 12.9% and that the average median improvement in survival was 3.8 mo [5]. Overall response rates for mrcc patients treated with IL-2 are 15 20%, similar to those reported for IFN-a [6]. Patients with mrcc face a poor prognosis, with median survival duration in the range of 1 yr and a 2-yr survival rate of only 10 20% [7]. Approximately 10% of patients survive beyond 5 yr. Additionally, cytokine therapy may be associated with side-effects such as interstitial oedema, hypotension, tachycardia, and renal complications [7]. Because treatment with cytokines is associated with significant side-effects and response rates are limited, a number of statistical models have been proposed to identify predictors of overall survival. The determination of prognostic factors for survival in patients with advanced RCC is important in designing and interpreting phase 3 randomised clinical trials. Additionally, patient stratification into risk groups based on prognostic factors allows for optimal treatment selection and patient counselling. 2. Evidence acquisition In this article we review and discuss the applicability of previously described prognostic factors in patients with mrcc who are starting targeted therapy. Studies dealing with prognostic factors and patient stratification strategies that were defined before and after targeted therapy era are reviewed. 3. Evidence synthesis 3.1. Prognostic factors for metastatic renal cell carcinoma Motzer et al pioneered the approach to risk stratification in RCC by introducing a model in 1999 that was capable of discriminating between favourable-, intermediate-, and poor-risk patients [7]. This study included advanced RCC patients treated in 24 clinical trials between 1975 and The stratifying variables in the original cohort of 670 patients (including Table 1 Risk group stratification and survival time in metastatic renal cell carcinoma Risk stratification No. of risk factors %of patients Median survival (mo) Favourable risk 0 25% 20 Intermediate risk 1 or 2 53% 10 Poor risk >2 22% patients treated with IFN-a or IL-2) consisted of low Karnofsky performance status (PS; <80%), high serum lactate dehydrogenase (LDH; >1.5 times the upper limit of normal), low serum haemoglobin (below the lower limit of normal), high corrected calcium (>10 mg/dl), and absence of prior nephrectomy. Median survival time by risk group is shown in Table 1. Because this study consisted of patients treated with and without cytokines, a subsequent analysis was performed by Motzer et al in 2002 [8]. The subjects of this analysis were 463 patients treated with first-line IFN-a therapy in six clinical trials. The predictors remained the same except for time from diagnosis to treatment with IFN-a: <1 yr was found to be a better predictor of short-term survival compared with the absence of prior nephrectomy. The median survival times for the three prognostic groups increased to 30 mo for favourable-risk patients, 14 mo for intermediate-risk patients, and 5 mo for poorrisk patients. Despite its highly innovative nature and its impressive acceptance in the urologic and oncologic communities, the Motzer system has limitations. These include lack of consideration of variables describing the primary tumour, which may potentially undermine the accuracy of the Motzer models. In these series, only a subset of patients underwent a nephrectomy. Consequently, variables such as tumour grade, stage, and histologic subtype could not be considered. It is possible that the use of pathologic tumour characteristics could possibly decrease further or even obliterate the importance of some of the variables and could lead to more accurate prognostic schemes. Another study of 353 patients with previously untreated mrcc at the Cleveland Clinic was conducted to assess and validate the model proposed by the Memorial Sloan-Kettering Cancer Centre (MSKCC) [9]. Four of five prognostic factors (time from diagnosis to entry into the study, LDH, corrected calcium, and low haemoglobin level) identified by MSKCC were independent predictors of survival. Prior radiotherapy and sites of metastasis were also found to be additional independent prognostic factors. Thus, the MSKCC definitions of risk groups were expanded to accommodate these two additional

3 480 european urology supplements 8 (2009) prognostic factors. Using this expanded criteria, Cleveland Clinic Foundation (CCF) risk groups were identified. Favourable risk was defined as zero or one poor prognostic factor, intermediate risk was defined as two poor prognostic factors, and poor risk was defined as more than two poor prognostic factors. Median overall survival times of these groups were 26, 14.4, and 7.3 mo, respectively ( p < ) [9]. All of these risk stratification studies included previously untreated mrcc patients. In contrast, data are sparse on prognostication in previously treated patients, and only three studies have been published to date [10 12]. In 2004, the model of Motzer et al was updated in a cohort of 251 previously treated patients who failed cytokine therapy [10].The patients were treated during clinical trials of new agents given as salvage therapy. Of the five original predictors, only poor PS, anaemia, and high corrected calcium qualified for inclusion. The nature of the cohort resulted in relatively shorter median survival times of 22 mo for favourable-risk patients, 12 mo for intermediate-risk patients, and 5 mo for poor-risk patients. Another study regarding prognostic factors of mrcc after failure of immunotherapy was reported by Escudier et al [11]. This multicentre study included 300 patients who were treated with the antiangiogenic agent Neovastat after failure of immunotherapy. Prognostic features associated with shorter survival on multivariate analysis were the number of metastatic sites (more than one), time from nephrectomy to metastatic disease (<2 yr), high alkaline phosphatase (ALP), abnormal corrected calcium, and high LDH (>1.5 times the upper limit of normal). Four prognostic groups were identified. Median survival in patients with zero, one, two, or more than two adverse prognostic factors was 15.6, 11.7, 8.5, and 3.5 mo, respectively ( p < 0.001). Another study with a total number of 85 patients also evaluated prognostic factors in previously treated patients [12]. These models were proposed as a stratification scheme for candidates for targeted therapies, especially after progression to cytokine therapy. PS does not seem to be related to survival in any of these three studies, despite its established prognostic role in previously untreated patients. Alternatively, corrected calcium seems to be of major importance as a clinical prognostication marker, since it was found to improve survival in all three series of previously treated patients (Table 2) [10 12] Prognostic factors and models in the era of targeted therapy During the last 5 yr, we all know that there has been a dramatic increase in treatment options of mrcc. Table 2 Studies of prognostic factors in previously treated patients with renal cell carcinoma Associated with adverse outcome Motzer et al [10] Boumerhi et al [12] Escudier et al [11] Time from nephrectomy/ No No Yes diagnosis to metastases Haemoglobin Yes Yes No Alkaline phosphatase Yes No Yes Corrected calcium Yes Yes Yes Lactate dehydrogenase No No Yes Performance status No No No No. metastatic sites No No Yes Due to its relationship to tumour angiogenesis, the von Hippel-Lindau (VHL) hypoxia-induced factor-1a (HIF-1a) vascular endothelial growth factor (VEGF) pathway has become a major drug development target [13]. Four new drugs sorafenib, sunitinib, temsirolimus, and bevacizumab have received regulatory approval, and at least 20 additional tyrosine kinase inhibitors (TKI) with probable activity in RCC are now progressing through clinical testing [13]. Many targeted therapy trials have enrolled patients and/or have reported results according to existing classification schemas. Such schemas have been developed from patients who were treated with cytokines and/or chemotherapy, and it is unclear whether the same factors reported previously are relevant to patients who are treated with VEGFtargeted therapy. Regarding this issue, Choueiri et al performed a study consisting of 120 patients with metastatic clear-cell RCC who received anti-vegf agents (bevacizumab, sunitinib, sorafenib, axitinib) in nine prospective clinical trials at the Cleveland Clinic between October 2003 and January 2006 [14]. The MSKCC and CCF risk groups were applied to these data to investigate the applicability of these two models in patients with RCC who received VEGFtargeted therapy. All patients had undergone prior nephrectomy. Identified risk factors for progressionfree survival (PFS) at multivariate analysis were as follows: Eastern Cooperative Oncology Group (ECOG) PS (0 or 1), time from diagnosis to treatment (<2yrvs 2 yr), abnormal baseline corrected calcium, high platelet count (>300 K/ml vs 300 K/ml) and higher absolute neutrophil count (>4.5 K/ml vs 4.5 K/ml). It is noteworthy that neither the MSKCC risk score nor the CCF risk score was associated with PFS when it was considered in multivariate analysis. Based on the results of this study, the authors formed three prognostic subgroups (Table 3) [14]. One other study, reporting the updated results of a sunitinib study, showed superior efficacy in comparison with IFN-a in a multicentre, randomised phase 3 trial of patients with previously untreated metastatic

4 european urology supplements 8 (2009) Table 3 Risk group stratification and progression-free survival (PFS) in the era of targeted therapy Risk stratification Adverse prognostic factor Median PFS (mo) Favourable risk Intermediate risk 2 13 Poor risk >2 3.9 clear cell RCC [15]. Multivariate analysis of pretreatment features predictive of PFS in the sunitinib group were delay between diagnosis and treatment (1 yr vs <1 yr; p < 0.001), ECOG PS (0 vs 1 or 2; p = 0.006), and corrected calcium (10 vs >10 mg/dl; p = 0.002). Therefore, similar to the Choueiri et al s study [14], this study also revealed that some parameters of MSKCC prognostic factors, such as preoperative haemoglobin level and serum LDH level, are lacking significance at multivariate analysis [15]. The results of these studies demonstrate that prognostic factors and models that were described previously and that are often used prior to the availability of novel agents may not be entirely applicable to patients with advanced RCC who are starting VEGF therapy. This is important because clinical trials evaluating these novel compounds have stratified patients using outdated models from the cytokine era. Therefore, it is necessary to identify the contemporary clinical, laboratory, and molecular features that can be used to predict outcome in the targeted therapy era. Other prognostic parameters such as molecular factors may also be considered and analysed in targeted therapy trials. Emerging data suggest the utility of molecular markers in predicting therapeutic responses to targeted agents. In a recent report, patients with VHL gene mutations had an overall response rate to VEGF-targeted therapy of 46%, compared with 28% in those with no mutations [16]. The presence or absence of VHL mutations remained an independent prognostic factor for response, even after considering several clinical prognostic factors. Incorporating such molecular markers with patient-specific prognostic factors into user-friendly algorithms and nomograms may enable the clinician to optimise treatment for individual patients. More recently, on the basis of outcome data from the previously performed sunitinib phase 3 trial, Motzer et al developed a nomogram for predicting the probability of 12-mo PFS for patients who received sunitinib as first-line treatment for mrcc [17]. Eleven pretreatment parameters were used to determine the probability of 12-mo PFS. The nomogram is the first developed specifically to predict treatment outcomes following systematic therapy for mrcc and may provide a more individualised prognostication than models that categorise patients into risk groups; however, this nomogram is internally validated. External validation of the nomogram is warranted. Finally, at least two other problems exist regarding prognostic factors and treatment decision. Many studies regarding prognostic factors used the histologic type of clear cell as an inclusion criterion; however, RCC subtypes vary in their biologic behaviour and response to treatment, leading to varying survival among patients with tumours of differing histology. Therefore, histologic subtype should be included in prospective trials assessing prognostic parameters. Additionally, the role and/or timing of nephrectomy remain to be determined in the era of targeted therapies. 4. Conclusions The increasing number of agents and associated clinical data underscore the need for prognostication to select the optimal treatment strategy for individual patients and thereby to maximise clinical benefit from targeted agents. Prognostic factors and models that were described previously in the cytokine era may not be entirely applicable to patients who are starting targeted therapy. Reassessment of clinical and biologic features of mrcc patients that are predictive of outcome is needed during this targeted therapy era. Treatment with newly available targeted agents may be optimised if the efficacy profile of each agent is defined across different risk groups and patient subpopulations. Conflicts of interest The author has nothing to disclose. Funding support None. References [1] Kirkali Z, Tüzel E, Mungan MU. Recent advances in kidney cancer and metastatic disease. BJU Int 2001;88: [2] Surveillance epidemiology and end results. National Cancer Institute web site. [3] Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, CA Cancer J Clin 2005;55:

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