**2. Stratifying risk of recurrence**

A critical element in both the testing and effective clinical use of adjuvant therapy involves determining whether there is a high risk of disease recurrence post nephrectomy and accordingly identifying patients that are most likely to benefit from the therapy. As discussed earlier, the determination of recurrence risk is currently nonstandardized in adjuvant therapy testing. Several models and clinical nomograms have been developed to predict the risk of disease recurrence and progression, as well as evaluate additional oncological endpoints [11–19]. Examples of some validated models include the Cindolo Recurrence Risk Formula, Leibovich scoring system, Karakiewicz scoring system, Kattan nomogram, Mayo Clinic stage, size, grade, and necrosis scoring system (SSIGN), and the University of California Los Angeles Integrated Staging System (UISS) [11–19] (**Tables 1** and **2**). These systems usually incorporate information regarding different variables and various prognostic signs and indictors such as tumor size, stage and characteristics, clinical risk factors, and various other pathological features and signs for a relatively robust evaluation [11–21]. Among these models, the UISS, Kattan and SSIGN nomograms have shown relatively better discriminative accuracy in some comparative studies and hence are most commonly utilized [13, 22, 23].

In terms of a general approximation, recurrence risk can be segregated into three broad categories based on the UISS nomogram: low, intermediate and high risk [18]. These three risk groups


**Table 1.** Leibovich prognosis score.

**1. Introduction**

174 Evolving Trends in Kidney Cancer

Every year, approximately 338,000 individuals are diagnosed with kidney cancer globally, representing about 2% of all cancers [1]. Renal cell carcinoma (RCC) accounts for approximately 90% of all kidney cancers—affecting an estimated 300,000 people each year [2, 3]. Approximately 30% of kidney cancer patients represent an advanced disease stage at diagno-

The management of RCC, regardless of its histological subtype or stage, involves surgical resection of the tumor through either a radical or partial nephrectomy [6]. While surgery is not curative in cases involving metastatic disease, with localized RCC, surgical intervention is

But despite that, postsurgical recurrence of cancer is a prevalent issue in cases of localized RCC (stage 2 or 3 disease) with a 5-year relapse rate of 30–40% and, as such, surgery is insufficient for long-term disease free survival [8, 9]. Hence, even though the current standard for postoperative care continues to be radiographic surveillance, the need for effective adjuvant therapy for localized high risk for recurrence RCC would be helpful and desired by the surgical community [8–10]. In view of these findings and the effective treatment of metastatic RCC with Immunotherapy in the 1990s or more recently with targeted therapy, a strong rationale for systemic adjuvant

In this chapter, we review different treatment modalities have been used as an adjuvant therapy for nonmetastatic renal cancer postsurgical resection with emphasis on targeted therapy

A critical element in both the testing and effective clinical use of adjuvant therapy involves determining whether there is a high risk of disease recurrence post nephrectomy and accordingly identifying patients that are most likely to benefit from the therapy. As discussed earlier, the determination of recurrence risk is currently nonstandardized in adjuvant therapy testing. Several models and clinical nomograms have been developed to predict the risk of disease recurrence and progression, as well as evaluate additional oncological endpoints [11–19]. Examples of some validated models include the Cindolo Recurrence Risk Formula, Leibovich scoring system, Karakiewicz scoring system, Kattan nomogram, Mayo Clinic stage, size, grade, and necrosis scoring system (SSIGN), and the University of California Los Angeles Integrated Staging System (UISS) [11–19] (**Tables 1** and **2**). These systems usually incorporate information regarding different variables and various prognostic signs and indictors such as tumor size, stage and characteristics, clinical risk factors, and various other pathological features and signs for a relatively robust evaluation [11–21]. Among these models, the UISS, Kattan and SSIGN nomograms have shown relatively better discriminative accuracy in some comparative studies and hence are most com-

In terms of a general approximation, recurrence risk can be segregated into three broad categories based on the UISS nomogram: low, intermediate and high risk [18]. These three risk groups

sis, with an average 5-year survival rate of approximately 16% [4, 5].

considered the optimal standard of care [6, 7].

therapy exists in high risk for recurrence patients.

as becoming an option to offer patients.

**2. Stratifying risk of recurrence**

monly utilized [13, 22, 23].


**Table 2.** UISS prognosis score.

are differentiated based on the probability of survival and disease recurrence and patients, in a clinical setting, can be stratified through an independent clinical assessment of UISS components, such as tumor stage, grade, and other pathophysiological characteristics [18, 19]. While the UISS components have not been formally validated as independent recurrence risk prediction models, they are important prognostic indicators for various oncological outcomes and endpoints that are invariably linked with the risk of disease relapse [18, 19]. As such, an evaluation of tumor characteristics—particularly tumor stage—can serve as a rough guide for preliminary differentiation between high, intermediate and low risk categories in the clinical setting. [24–27] This correlation has been supported by independent studies which have reported higher recurrence free survival (RFS) rates for smaller, T1a-T1b stage tumors and lower RFS rates for larger, T3-T4 stage tumors [24–27]. Thus, patients with T1a-T2a tumors can be estimated to have lower recurrence risk while those with T3b-T4 tumors can be placed into the high-risk category [24–27]. Among these varying risk levels, currently only those who present a high risk of disease recurrence can potentially benefit from adjuvant therapy postsurgical resection of the tumor.

The incorporation of biotechnology and an improved understanding of genetic and molecular markers may potentially lead to the next major advancement in improving the predictive accuracy of relapse risk. Recent studies have reported the development of novel gene assays and have further elucidated several new biomarkers [28–31]. Nonetheless, further investigation, testing and development is required before molecular approaches can be incorporated for clinical application in an efficient and economically viable manner.

**6. Radiotherapy**

patients [45–47].

**7.1. Targeted therapy**

agents [7, 49–53].

**7.2. VHL-HIF pathway**

Radiotherapy has been used for symptoms palliation in metastatic RCC like hematuria and painful bone metastasis. Also, long-term PFS has been reported for in a subset of patients

Current Role of Adjuvant Therapy in High Risk for Recurrence Resected Kidney Cancer

http://dx.doi.org/10.5772/intechopen.78684

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One prospective, randomized study in 72 patients comparing administration of radiation of the kidney bed, and ipsilateral and contralateral lymph nodes for stages II and III RCC versus observation reported relapse rates of 48% in both groups. Forty-four percent of patients in the radiotherapy arm had significant complications that contributed to the death of 19% of

Systemic therapy for mRCC has particularly changed over the last decade with the introduction of targeted therapy and the evolvement of tyrosine kinase inhibitors (TKI) [7, 49–53]. This development has directly resulted from an improved understanding of the pathogenesis and molecular biology of RCC [49–54]. TKIs have provided a novel therapeutic approach for better managing the pathology through the inhibition of targets such as the mammalian target of rapamycin (mTOR) pathway and the vascular endothelial growth factor receptor (VEGFR), which consequently help inhibit processes that are critical for cancer progression [7, 49–53]. Particularly in cases of metastatic RCC, these inhibitors have been effective in increasing the overall survival and response rates than previously used immunotherapy and chemotherapy

Seven drugs are now approved for targeted therapy, and several others are being evaluated in clinical trials [50–53, 55]. At the molecular level, the mechanism of these drugs involves interrupting the molecular signal transduction of various signaling pathways which then ultimately affects pathogenic factors like tumor vascularity, growth and progression [50–53, 55]. Sunitinib and Pazopanib are currently the accepted standard of care for the management of metastatic RCC and are the most widely used first line agent due to their robust clinical efficacy and established toxicity profile [50–53, 55]. The current set of therapeutic agents used in targeted therapy exploit the Von Hippel-Lindau (VHL) and hypoxia-inducible factor (HIF) pathway

Clear Cell RCC (ccRCC) normally entails a biallelic inactivation of the VHL tumor suppressor gene at the 3p25-26 locus. VHL inactivation, which occurs due to factors such as mutation, hyper-methylation, or deletions, results in the formation of defective pVHL protein—ultimately leading to the activation and upregulation of HIF-1α [56, 57]. Activated HIF protein serves as a transcription factor for various pro-tumorigenic target genes such as vascular

following radiotherapy for solitary bone metastases [31].

associated with clear cell RCC pathogenesis [56, 57].

**7. Adjuvant therapy in the era of the new targeted therapy**
