Predicting Oncologic Outcomes in Renal Cell Carcinoma After Surgery

Renal mass biopsy - a practical and clinicopathologically relevant approach to diagnosis

Advancements in imaging modalities have increased the frequency of renal mass discovery. Imaging has typically been considered sufficient to guide management for a large proportion of these tumours, but renal mass biopsies (RMBs) have an increasing role in determining malignancy and can be a valuable tool for preventing unnecessary surgery in patients with benign tumours. A structured approach should be used to help to navigate the expanding repertoire of renal tumours, many of which are molecularly defined. In terms of tumour subtyping, the pathologist's strategy should focus on stratifying patients into clinically different prognostic groups according to our current knowledge of tumour behaviour, including benign, low-grade or indolent, intermediate malignant or highly aggressive. Crucial pathological features and morphological mimicry of tumours can alter the tumour's prognostic group. Thus, pathologists and urologists can use RMB to select patients with tumours at a reduced risk of progression, which can be safely managed with active surveillance within a tailored imaging schedule, versus tumours for which ablation or surgical intervention is indicated. RMB is also crucial in the oncological setting to distinguish between different high-grade tumours and guide tailored management strategies.

Renal Cell Carcinoma With Venous Tumor Thrombus Has a Predilection for the Lungs

OBJECTIVE

To investigate the association between venous tumor thrombus (VTT) and the risk of pulmonary metastases in patients with clear cell renal cell carcinoma (ccRCC).

METHODS

We queried our institutional registry for ccRCC patients undergoing radical nephrectomy (1970-2019). Cox proportional hazards regression models, adjusting for factors associated with ccRCC progression, were used to determine whether VTT was associated with pulmonary metastases.

RESULTS

Of 3410 patients studied, 1025 (30%) had VTT. Patients with VTT were more likely to present with synchronous pulmonary metastasis (20% vs 7%, P<.001). Within the VTT subset, level of VTT was not significantly associated with synchronous pulmonary metastasis (P=.3). Moreover, among patients with metastatic disease at nephrectomy (n=643), pulmonary metastases were more common in those with VTT versus those without VTT (68% vs 51%, P<.001). Further, excluding patients with synchronous pulmonary metastases, on multivariable analysis, VTT remained associated with an increased risk of developing metachronous pulmonary metastases (hazard ratio (HR) 1.31, P<.001). Interestingly, the presence of PE in the setting of VTT was also identified to be associated with an increased pulmonary metastases post-nephrectomy (HR 2.31, P<.001).

CONCLUSION

VTT is associated with disproportionately increased pulmonary metastases at presentation and post-nephrectomy in ccRCC. Further, the presence of PE at nephrectomy for VTT was associated with increased pulmonary metastases post-nephrectomy. These results support a metastatic predilection of ccRCC with VTT in the lungs.

Validation of novel grading schemes and refinement of the Leibovich risk groups for chromophobe renal cell carcinoma

BACKGROUND

Traditional grading systems have proven inadequate in stratifying chRCC patients based on recurrence risk. Recently, several novel grading schemes, including three-tiered, two-tiered, and four-tiered systems, have been proposed, but their prognostic value remains controversial and lacks external validation.

MATERIALS AND METHODS

We included 528 patients with pathologically proven chRCC (chromophobe renal cell carcinoma) from multiple medical institutions and the Cancer Genome Atlas-Kidney Chromophobe cohort. Three experienced pathologists independently reassessed the slides based on the three novel grading schemes. Survival outcomes, including disease-specific survival (DSS), recurrence-free survival (RFS), were analyzed using Kaplan-Meier methods and Cox proportional hazards regression models. The prognostic value of the original and adjusted Leibovich risk groups was compared using Harrell's C-index.

RESULTS

All grading systems demonstrated significant survival differences among their respective groups (p < 0.001 for all). However, within the four-tiered system, no significant survival disparity was observed between grade 1 and grade 2 tumors (GTG2 without necrosis) (p = 0.619 for DSS). When patients with necrosis were excluded, no survival difference was detected between CTG1 and CTG2 tumors in the three-tiered system (p = 0.870 for DSS), challenging the prognostic utility of distinguishing between these two grades. The adjusted Leibovich risk stratification (C-index = 0.840 for DSS), incorporating necrosis and tumor thrombus, demonstrated superior prognostic value compared to the original model (C-index = 0.762 for DSS), with more pronounced survival distinctions and improved predictive performance.

CONCLUSION

Our study validates the prognostic significance of recently developed grading systems for chRCC. The observed survival difference between CTG1 and CTG2 in the three-tiered system may be attributed to varying percentages of coagulative necrosis. By integrating necrosis and tumor thrombus into the Leibovich risk groups, we enhanced the model's ability to distinguish between patients and improved its predictive performance.

Survival analysis of clear cell renal cell carcinoma based on radiomics and deep learning features from CT images

PURPOSE

To create a nomogram for accurate prognosis of patients with clear cell renal cell carcinoma (ccRCC) based on computed tomography images.

METHODS

Eight hundred twenty-two ccRCC patients with contrast-enhanced computed tomography images involved in this study were collected. A rectangular region of interest surrounding the tumor was used to extract quantitative radiomics and deep-learning features, which were filtered by Cox proportional hazard regression model and least absolute shrinkage and selection operator. Then the selected features formed a fusion signature, which was assessed by Cox proportional hazard regression model method, Kaplan-Meier analysis, receiver operating characteristic curves, and concordance index (C-index) in different clinical subgroups. Finally, a nomogram constructed with this signature and clinicopathologic risk factors was assessed by C-index and survival calibration curves.

RESULTS

The fusion signature performed better than the radiomics signature. Then we combined this signature and 2 clinicopathologic risk factors. This nomogram showed an increase of about 20% in C-index values when compared to clinical nomogram in both datasets. Its prediction probability was also in good agreement with the actual ratio.

CONCLUSION

The proposed fusion nomogram provided a noninvasive and easy-to-use model for survival prognosis of ccRCC patients in future clinical use, without the requirement to perform a detailed segmentation for radiologists.

Deep learning-based prediction of tumor aggressiveness in RCC using multiparametric MRI: a pilot study

OBJECTIVE

To investigate the value of multiparametric magnetic resonance imaging (MRI) as a non-invasive method to predict the aggressiveness of renal cell carcinoma (RCC) by developing a convolutional neural network (CNN) model and fusing it with clinical characteristics.

METHODS

Multiparametric abdominal MRI was performed on 47 pathologically confirmed RCC patients between 2019 and 2023. Preoperative MRI was performed on all patients to assess their clinical characteristics. The CNN model was developed and validated to assess the predictive value of b value images, combined b value images, apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and their parametric maps for RCC aggressiveness. The least absolute shrinkage and selection operator (LASSO) regression was used to identify clinical features highly correlated with RCC aggressiveness. These clinical features were combined with selected b values to develop a fusion model. All models were evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

A total of 47 patients (mean age, 56.17 ± 1.70 years; 37 men, 10 women) were evaluated. LASSO regression identified renal sinus/perirenal fat invasion, tumor stage, and tumor size as the most significant clinical features. The combined b values of b = 0,1000 achieved an area under the curve (AUC) of 0.642 (95% CI: 0.623-0.661), and b = 0,100,1000 achieved an AUC of 0.657 (95% CI: 0.647-0.667). The fusion model combining clinical features with b = 0,1000 yielded the highest performance with an AUC of 0.861 (95% CI: 0.667-0.992), demonstrating superior predictive accuracy compared to the other models.

CONCLUSION

Deep learning using a CNN fusion model, integrating multiple b value images and clinical features, could effectively promote the preoperative prediction of tumor aggressiveness in RCC patients.

Evaluation of American Urological Association Renal Cell Carcinoma Risk Groups for Chromophobe Renal Cell Carcinoma

OBJECTIVE

To develop and compare various models for risk stratification in chromophobe renal cell carcinoma (chrRCC). Models have been developed to predict progression-free (PFS) and cancer-specific survival (CSS) following surgery for localized renal cell carcinoma (RCC). Notably, chromophobe RCC (chrRCC) is not included in American Urological Association (AUA) risk stratification, as nuclear grading is not recommended.

METHODS

We queried our institutional registry to identify patients managed surgically for unilateral, sporadic, M0, chrRCC from 1970-2012. AUA risk groups were defined using reported criteria, excluding grade, and were compared to the Mayo system incorporating nodal involvement, perinephric/renal sinus fat invasion, and sarcomatoid differentiation. PFS and CSS were estimated using the Kaplan-Meier method. Predictive ability was summarized using c-indexes from Cox proportional hazard regression models.

RESULTS

A total of 257 patients were identified. Thirty-nine patients experienced disease progression at a median 30 months (IQR 5.0-84) and 25 died from chrRCC at a median 34 months (IQR 15-79) following surgery. PFS and CSS rates at 10 years after surgery were 84% and 90%, respectively. C-indexes for modified AUA and Mayo risk groups were similar at 0.76 and 0.75, respectively, for PFS, and 0.77 and 0.76, respectively for CSS.

CONCLUSION

The modified AUA and Mayo risk stratification systems have similarly robust c-indexes for PFS and CSS in chrRCC. These models can be used to counsel patients based on pathologic features, inform clinicians on appropriate follow-up pathways, and identify patients at risk of disease progression for enrollment in adjuvant systemic therapy trials.

Prognostic factors and prognostic model of non-metastatic clear cell renal cell carcinoma

INTRODUCTION

Although there are some established prognostic evaluation models for clear cell renal cell carcinoma (ccRCC), more robust postoperative prognostic evaluation model is urgently needed. Our study intends to explore new clinical and pathological prognostic factors related to non-metastatic ccRCC, which help to establish a better prognostic risk evaluation model in non-metastatic ccRCC.

PATIENTS AND METHODS

A retrospective cohort study was conducted in non-metastatic ccRCC patients spanning from 2010 to 2018. Clinical and pathological factors of these patients were collected. Cox regression analysis was employed to assess the relationship between these factors and disease-free survival (DFS), and a nomogram risk prediction model was also constructed.

RESULTS

A total of 1467 patients were ultimately included, comprising 994 men (67.8%), with 800 patients aged between 40 and 60 years old (54.5%), and 80 patients (5.5%) experiencing relapse or metastasis of ccRCC within three years after operation. The follow-up duration ranged from 39 to 146 months. Univariate and multivariate Cox regression analysis identified five independent prognostic factors of DFS (P < 0.05) including sex, tumor maximum diameter, T stage, lactate dehydrogenase (LDH), and basophils. Leveraging these five factors, we established a prognostic evaluation model demonstrating good predictive efficacy.

CONCLUSION

Male, tumor maximum diameter, T stage, LDH, and basophils serve as prognostic indicators for DFS in patients with non-metastatic ccRCC. Patients with high scores based on our model exhibit an elevated likelihood of recurrence or metastasis, thereby potentially selecting postoperative patients with high risk for adjuvant therapy.

Oncologic surveillance after surgical treatment for clinically localized kidney cancer: UroCCR study n. 129

BACKGROUND

In 2021, the EAU Guidelines implemented a novel, expert opinion-based follow-up scheme, with a three-risk-category system for clear cell (cc) and non-cc renal cell carcinoma (non-ccRCC) after surgery with curative intent. We aimed to validate the novel follow-up scheme and provide data-driven recurrence estimates according to risk groups, to confirm or implement the oncologic surveillance strategy.

METHODS

We identified 5,320 patients from a prospectively maintained database involving 28 French referral centers. The risk of recurrence, as either loco-regional or distant, was evaluated with the Kaplan-Meier method for each group (low- intermediate- or high-risk) according to ccRCC or non-ccRCC histology. The noncumulative distribution of recurrences was graphically investigated through the LOWESS smoother.

RESULTS

Two thousand two hundred ninety-three (58%), 926 (23%), and 738 (19%) had low-, intermediate, and high-risk ccRCC, and 683 (50%), 297 (22%), and 383 (28%) had low-, intermediate, and high-risk non-ccRCC, respectively. Median follow-up for survivors was 46 months. Overall, 661 patients experienced recurrence. Over time, the noncumulative risk of recurrence was approximately 10% for low-risk cc-RCC, non-ccRCC, and intermediate-risk non-ccRCC, with non-significant difference among the three recurrence functions (P=0.9). At 5-year, time point after which imaging should be de-intensified to biennial, the noncumulative risks of recurrence were: for intermediate risk ccRCC and non-ccRCC: 15% and 11%, respectively; for high-risk ccRCC and non-ccRCC: 24% and 8%, respectively. Among high-risk non-ccRCC patients there were 9 recurrences at 3-month. There was no significant difference between the recurrence function of high-risk non-ccRCC patients with negative imaging at 3-month and the one of intermediate-risk ccRCC (P=0.3).

CONCLUSIONS

Given the relatively low recurrence risk of patients with intermediate-risk non-ccRCC, those individuals could be followed up with a similar strategy to the low-risk category. Similarly, patients with high-risk non-ccRCC with negative imaging at 3-month, could be followed up similarly to intermediate-risk ccRCC after the 3-month time point.

Incidence and predictors of ipsilateral local recurrence following partial nephrectomy

PURPOSE

Ipsilateral local recurrence (LR) after partial nephrectomy (PN) for renal cell carcinoma (RCC) may result from a metachronous tumor or PN bed recurrence. To date, literature has predominantly reported ipsilateral LRs collectively, although the pathophysiology and prognostic implications of these event may be distinct. We sought to assess variables associated with LR and evaluated associations of LR with metastasis and death from RCC.

MATERIALS AND METHODS

We identified adults undergoing PN for unilateral, sporadic, localized RCC from 2000 to 2019 using a prospectively maintained, single institution registry. LR was defined as new, enhancing tumor within/near the PN bed on MRI/CT. Cox proportional hazards models were used to create a preoperative risk score for LR and to examine the association of LR with metastasis and CSS following PN among patients with clear cell RCC.

RESULTS

In a cohort of 2,164 PNs, 106 true LRs were identified, for a 10-year incidence of 6.2%. A preoperative risk score for LR based on age, symptoms, solitary kidney, complex tumor necessitating open partial nephrectomy, and cT stage was created (c-index = 0.73). Postoperatively, positive margins, pT stage, and clear cell subtype were associated with LR. Notably, 21% (23/106) of patients with LR presented with synchronous metastases. Following LR, 5-year metastasis-free and cancer-specific survival were 64% and 71%, respectively. LR remained associated with metastasis (HR 6.25; P < 0.001) and death from RCC (HR 1.93; P = 0.03) on multivariable analysis.

CONCLUSIONS

We developed a preoperative risk score to identify patients at risk for LR following PN. LR was an independent risk factor for metastasis and death from RCC. Further study is warranted to determine whether treatment of LR improves oncologic outcomes.

Prognostic models for predicting oncological outcomes after surgical resection of a nonmetastatic renal cancer: A critical review of current literature

Prognostic models can be valuable for clinicians in counseling and monitoring patients after the surgical resection of nonmetastatic renal cell carcinoma (nmRCC). Over the years, several risk prediction models have been developed, evolving significantly in their ability to predict recurrence and overall survival following surgery. This review comprehensively evaluates and critically appraises current prognostic models for nm-RCC after nephrectomy. The last 2 decades have witnessed a notable increase in the development of various prognostic risk models for RCC, incorporating clinical, pathological, genomic, and molecular factors, primarily using retrospective data. Only a limited number of these models have been developed using prospective data, and their performance has been less effective than expected when applied to broader, real-life patient populations. Recently, artificial intelligence (AI), especially machine learning and deep learning algorithms, has emerged as a significant tool in creating survival prediction models. However, their widespread application remains constrained due to limited external validation, a lack of cost-effectiveness analysis, and unconfirmed clinical utility. Although numerous models that integrate clinical, pathological, and molecular data have been proposed for nm-RCC risk stratification, none have conclusively demonstrated practical effectiveness. As a result, current guidelines do not endorse a specific model. The ongoing development and validation of AI algorithms in RCC risk prediction are crucial areas for future research.

Development and External Validation of Nomograms for Predicting Disease-Free Survival and Overall Survival in Patients with cT1-ccRCC After Partial Nephrectomy: A Multicenter Retrospective Study

BACKGROUND

To develop a novel nomogram for predicting 2-year and 5-year disease-free survival (DFS) and overall survival (OS) in patients with cT1-clear cell renal cell carcinoma (ccRCC) undergoing partial nephrectomy (PN).

METHODS

A retrospective study was conducted across five urological centers, including 940 patients who underwent PN for cT1N0M0-ccRCC. Four centers were randomly selected to constitute the training group, while the remaining center served as the testing group. We employed the LASSO and multivariate Cox regression to develop new nomograms. The 1,000 bootstrap-corrected c-index, net reclassification improvement (NRI) and receiver operating characteristic curve were employed to compare the predictive abilities of new nomograms with the widely used UUIS and SSIGN models. Finally, the novel nomograms underwent external validation.

RESULTS

The training group included 714 patients, while the testing group consisted of 226 patients. The bootstrap-corrected c-indexes for the DFS and OS model were 0.870 and 0.902, respectively. In the training cohort, the AUC for the DFS and OS models at 2 years and 5 years were 0.953, 0.902, 0.988, and 0.911, respectively. These values were also assessed in the testing cohort. The predictive capabilities of the new nomograms surpassed those of the UUIS and SSIGN models (NRI > 0). Decision curve analysis demonstrated that the novel nomograms provide greater net benefits compared to the UUIS and SSIGN models.

CONCLUSIONS

Our novel nomograms demonstrated strong predictive ability for forecasting oncological outcomes in cT1-ccRCC patients after PN. These user-friendly nomograms are simple and convenient for clinical application, providing tangible clinical benefits.

Tumor contour irregularity on preoperative CT predicts prognosis in renal cell carcinoma: a multi-institutional study

Background

Radiology-based prognostic biomarkers play a crucial role in patient counseling, enhancing surveillance, and designing clinical trials effectively. This study aims to assess the predictive significance of preoperative CT-based tumor contour irregularity in determining clinical outcomes among patients with renal cell carcinoma (RCC).

Methods

We conducted a retrospective multi-institutional review involving 2218 patients pathologically diagnosed with RCC. The training and internal validation sets included patients at Zhongshan Hospital between January 2009 and August 2019. The external test set comprised patients from the First Affiliated Hospital, Zhejiang University School of Medicine (January 2016 to January 2018), the Xiamen Branch of Zhongshan Hospital (November 2017 to June 2023), and the Cancer Imaging Archive. The contour irregularity degree (CID), quantified as the ratio of irregular cross-sections to the total tumor cross-sections, was analyzed for its prognostic relevance across different subgroups of RCC patients. A novel CID-based scoring system was developed, and its predictive efficacy was evaluated and compared with existing prognostic models.

Findings

The CID exhibited significant discriminatory power in predicting overall survival (OS), recurrence-free survival (RFS), and disease-specific survival (DSS) among patients with RCC tumors measuring 3 cm or larger (all p < 0.001). Multivariate analyses confirmed the CID as an independent prognostic indicator. Notably, the CID augmented prognostic stratification among RCC patients within distinct risk subgroups delineated by SSIGN models and ISUP grades. The CID-based nomogram (C-Model) demonstrated robust predictive performance, with C-index values of 0.88 (95%CI: 0.84-0.92) in the training set, 0.92 (95%CI: 0.88-0.98) in the internal validation set, and 0.86 (95%CI: 0.81-0.90) in the external test set, surpassing existing prognostic models.

Interpretation

Routine imaging-based assessment of the CID serves as an independent prognostic factor, offering incremental prognostic value to existing models in RCC patients with tumors measuring 3 cm or larger.

Funding

This study was funded by grants from National Natural Science Foundation of China; Shanghai Municipal Health Commission; China National Key R&D Program and Science and Technology Commission of Shanghai Municipality.

Contemporary Management of Renal Cell Carcinoma: A Review for General Practitioners in Oncology

Renal cell carcinoma accounts for a significant proportion of cancer diagnoses in Canadians. Over the past several years, the management of renal cell cancers has undergone rapid changes in all prognostic risk categories, resulting in improved oncologic outcomes. Novel strategies for metastatic disease make use of the synergy between checkpoints and angiogenesis inhibition. Moreover, combination checkpoint inhibition has demonstrated durable efficacy in some patients. Adjuvant immunotherapy has recently shown a survival benefit for the first time in select cases. Significant efforts are underway to explore new compounds or combinations for later-line diseases, such as inhibitors of hypoxia-inducible factors and radiolabeled biomolecules targeting tumor antigens within the neoplastic microenvironment for precise payload delivery. In this manuscript, we provide a comprehensive review of the available data addressing key therapeutic areas pertaining to systemic therapy for metastatic and localized disease, review the most relevant prognostic tools, describe local therapies and management of CNS disease, and discuss practice-changing trials currently underway. Finally, we focus on some of the practical aspects for general practitioners in oncology caring for patients with renal cell carcinoma.

Renal cell carcinoma

The landscape of the management of renal cell carcinoma has evolved substantially in the last decade, leading to improved survival in localised and advanced disease. We review the epidemiology, pathology, and diagnosis of renal cell carcinoma and discuss the evidence for current management strategies from localised to metastatic disease. Developments in adjuvant therapies are discussed, including use of pembrolizumab-the first therapy to achieve overall survival benefit in the adjuvant setting. The treatment of advanced disease, including landmark trials that have established immune checkpoint inhibition as a standard of care, are also reviewed. We also discuss the current controversies that exist surrounding the management of metastatic renal cell carcinoma, including the use of risk assessment models for disease stratification and treatment selection for frontline therapy. Management of non-clear cell renal cell carcinoma subtypes is also reviewed. Future directions of research, including a discussion of ongoing clinical trials and the need for reliable biomarkers to guide treatment in kidney cancer, are also highlighted.

A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.

Clinical outcome predictors for metastatic renal cell carcinoma: a retrospective multicenter real-life case series

Over the last decades, the therapeutic armamentarium of metastatic renal cell carcinoma (mRCC) has been revolutionized by the advent of tyrosin-kinase inhibitors (TKI), immune-checkpoint inhibitors (ICI), and immune-combinations. RCC is heterogeneous, and even the most used validated prognostic systems, fail to describe its evolution in real-life scenarios. Our aim is to identify potential easily-accessible clinical factors and design a disease course prediction system. Medical records of 453 patients with mRCC receiving sequential systemic therapy in two high-volume oncological centres were reviewed. The Kaplan-Meier method and Cox proportional hazard model were used to estimate and compare survival between groups. As first-line treatment 366 patients received TKI monotherapy and 64 patients received ICI, alone or in combination. The mean number of therapy lines was 2.5. A high Systemic Inflammation Index, a BMI under 25 Kg/m2, the presence of bone metastases before systemic therapy start, age over 65 years at the first diagnosis, non-clear-cell histology and sarcomatoid component were correlated with a worse OS. No significant OS difference was observed between patients receiving combination therapies and those receiving exclusively monotherapies in the treatment sequence. Our relapse prediction system based on pathological stage and histological grade was effective in predicting the time between nephrectomy and systemic treatment. Our multicentric retrospective analysis reveals additional potential prognostic factors for mRCC, not included in current validated prognostic systems, suggests a model for disease course prediction and describes the outcomes of the most common therapeutic strategies currently available.

Development and validation of a nomogram to predict recurrence for clinical T1/2 clear cell renal cell carcinoma patients after nephrectomy

OBJECTIVE

To develop and validate a nomogram for predicting recurrence-free survival (RFS) for clinical T1/2 (cT1/2) clear cell renal cell carcinoma (ccRCC) patients after nephrectomy.

METHODS

Clinicopathological and survival data from 1289 cT1/2 ccRCC patients treated at the Second Hospital of Tianjin Medical University between 2017 and 2020 were included. Cox regression analysis was used to identify independent risk factors in 902 and 387 ccRCC patients in the training and validation cohorts, respectively, and construct the nomogram. The performance of the nomogram was assessed through calibration plots, time-dependent receiver operating characteristic (ROC) curves, C-index (concordance-index), and decision curve analysis (DCA). Kaplan-Meier curves were used to evaluate the probability of RFS in patients with different recurrence risks.

RESULTS

Age, tumor size, surgical approach, Fuhrman grade, and pT3a upstage were identified as independent predictors of RFS. The area under the curve (AUC) for the 3-year and 5-year RFS ROC curves were 0.791 and 0.835 in the training cohort, and 0.860 and 0.880 in the validation cohort. The DCA and calibration plots demonstrated the optimal application and excellent accuracy of the nomogram for predicting 3-year and 5-year RFS. Kaplan-Meier curves revealed significant differences in RFS among the three risk groups in both the training and validation cohorts. Clinically, the developed nomogram provides a more precise tool for risk stratification, enabling tailored postoperative management and surveillance strategies, ultimately aiming to improve patient outcomes.

CONCLUSIONS

We developed a nomogram for predicting RFS in cT1/2 ccRCC patients after nephrectomy with high accuracy. The clinical implementation of this nomogram can significantly enhance clinical decision-making, leading to improved patient outcomes and optimized resource utilization in the management of ccRCC.

Clear cell and non-clear cell renal cell carcinoma in young adults: clinicopathological features, survival outcomes and prognostic factors

OBJECTIVES

Renal cell carcinoma (RCC) is infrequent among young adults. Few studies reported the outcome of RCC in young adults by pathological subtypes. The purpose of this study was to explore the clinicopathological features, survival outcomes and prognostic factors of young adult patients with clear cell (CCRCC) and non-clear cell renal cell carcinoma (NCCRCC).

METHODS

This study included young adult patients aged 18-40 years who were diagnosed as renal cell carcinoma (RCC) between 2012 and 2022 at Peking University Third Hospital. All patients underwent either partial nephrectomy or radical nephrectomy, and some received adjuvant therapy. A comparative analysis was performed to investigate the differences in clinicopathological characteristics between the cohort of CCRCC and NCCRCC. Kaplan-Meier survival analysis was utilized to plot survival curves for young adults with RCC. The univariate and multifactorial prognostic analyses were conducted using the log-rank test and COX proportional hazards model.

RESULTS

A total of 300 RCC patients aged 18-40 years were performed, of which 201 were diagnosed with CCRCC (67%) and 99 were diagnosed with NCCRCC(33%). The NCCRCC included 29 cases (9.7%) of chromophobe RCC, 28 cases (9.3%) of MiT family translocation RCC, 22 cases (7.3%) of papillary RCC, 11 cases (3.7%) of low malignant potential multifocal cystic RCC, and 6 cases of unclassified RCC (2.0%), 2 cases of mucinous tubule and spindle cell carcinoma (0.7%), and 1 case of FH-deficient RCC (0.3%).The mean age was 33.4 ± 6.1 years old. The overall and progression free 5-year survival rate was 99.1 and 95.3%, respectively. The NCCRCC cohort demonstrated a statistically significant decrease in progression-free survival (PFS) rate when compared to the CCRCC cohort (p < 0.001). There was no statistically significant difference observed in overall survival (OS) (p = 0.069). Pathological stage was a significant independent predictor for OS (p = 0.045). Pathological stage and nuclear grade were both independent predictors for PFS (p = 0.020; p = 0.005).

CONCLUSIONS

The clinical and pathological features of young adults diagnosed with CCRCC exhibit notable distinctions from those of NCCRCC patients. The survival outcome was significantly influenced by the pathological stage, while both the nuclear grade and pathological stage had a significant impact on tumor progression. This study offered significant contributions to the understanding of the clinicopathological characteristics and prognostic determinants of renal cell carcinoma (RCC) in young adults.

Perioperative systemic treatments in renal cell carcinoma

In this review, we aim to provide a comprehensive assessment of the evolving landscape of the perioperative management in renal cell carcinoma (RCC), emphasizing its dynamic and intricate nature. We explore academic and clinical insights into the perioperative treatment paradigm of RCC. Up-to-date treatment options are discussed and the evolving role of neoadjuvant and adjuvant therapy in RCC is highlighted.

Predicting Recurrence After Radical Surgery for High-Risk Renal Cell Carcinoma: Development and Internal Validation of the "TOWARDS" Score

BACKGROUND

Considering the reported greater benefits of immunotherapy and its unignorable adverse events in adjuvant therapy for high-risk renal cell carcinoma (hrRCC), accurate prediction may optimize drug use.

METHODS

The primary objective of this study was to generate a score-based prognostic model of recurrence-free survival in hrRCC. The study retrospectively evaluated 456 patients at two institutions who underwent radical surgery for nonmetastatic pT3-4 and/or N1-2 or pT2 and G4 disease. Clinical variables deemed universally available were selected through backward stepwise analysis and fitted by a multivariable Cox proportional hazards regression model. A point-based score was derived from regression coefficients. Discrimination, calibration, and decision curve analyses were conducted to evaluate predictive performance. Internal validation with bootstrapping was performed to correct for optimism.

RESULTS

The mean follow-up period was 55.3 months, and the median follow-up period was 28.0 months. During the follow-up period, the recurrence rate was 48.2% (n = 220) during a median of 75.7 months. Stepwise variable selection retained age, Eastern Cooperative Oncology Group (ECOG) performance status, presence or absence of symptoms, size of the primary tumor, pathologic T stage, pathologic N stage, tumor grade, and histology. Subsequently, the TOWARDS score (range 0-53) was developed from these variables. Internal validation showed an optimism-corrected C-index of 0.723 and a calibration slope of 0.834. The decision curve analysis showed the superiority of this score over the University of California, Los Angeles (UCLA) Integrated Staging System and GRade, Age, Nodes, and Tumor score.

CONCLUSIONS

The authors' novel TOWARDS scoring model had good accuracy for predicting disease recurrence in patients with hrRCC, and the clinical practicability was superior to that of the existing models.

Role of clinicopathological variables in predicting recurrence and survival outcomes after surgery for non-metastatic renal cell carcinoma: Systematic review and meta-analysis

Renal cell carcinoma (RCC) represents 2% of all diagnosed malignancies worldwide, with disease recurrence affecting 20% to 40% of patients. Existing prognostic recurrence models based on clinicopathological features continue to be a subject of controversy. In this meta-analysis, we summarized research findings that explored the correlation between clinicopathological characteristics and post-surgery survival outcomes in non-metastatic RCC patients. Our analysis incorporates 99 publications spanning 140 568 patients. The study's main findings indicate that the following clinicopathological characteristics were associated with unfavorable survival outcomes: T stage, tumor grade, tumor size, lymph node involvement, tumor necrosis, sarcomatoid features, positive surgical margins (PSM), lymphovascular invasion (LVI), early recurrence, constitutional symptoms, poor performance status (PS), low hemoglobin level, high body-mass index (BMI), diabetes mellitus (DM) and hypertension. All of which emerged as predictors for poor recurrence-free survival (RFS) and cancer-specific survival. Clear cell (CC) subtype, urinary collecting system invasion (UCSI), capsular penetration, perinephric fat invasion, renal vein invasion (RVI) and increased C-reactive protein (CRP) were all associated with poor RFS. In contrast, age, sex, tumor laterality, nephrectomy type and approach had no impact on survival outcomes. As part of an additional analysis, we attempted to assess the association between these characteristics and late recurrences (relapses occurring more than 5 years after surgery). Nevertheless, we did not find any prediction capabilities for late disease recurrences among any of the features examined. Our findings highlight the prognostic significance of various clinicopathological characteristics potentially aiding in the identification of high-risk RCC patients and enhancing the development of more precise prediction models.

Predictive Model of CK7 Expression in Patients With Clear Cell Renal Cell Carcinoma by Combined Multimodal Ultrasound Diagnostic Techniques: A Retrospective Study

OBJECTIVE

The aim of the work described here was to develop and validate a predictive model for cytokeratin 7 (CK7) expression in clear cell renal cell carcinoma (ccRCC) patients by combining multimodal ultrasound diagnostic techniques.

METHODS

This retrospective study enrolled 157 surgically confirmed ccRCC patients. All patients underwent pre-operative multimodal ultrasound diagnostic examinations, including B-mode ultrasound (US), color Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS). The patients were randomly divided into a training group (103 cases) and a testing group (54 cases). Univariate and multivariate logistic regression analyses were performed in the training group to identify independent indicators associated with CK7 positivity. These indicators were included in the predictive model. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the model's discriminative ability and accuracy. Decision curve analysis (DCA) and nomogram visualization were used to assess the clinical utility of the predictive model.

RESULTS

Univariate logistic regression analysis revealed that US and CDFI observations were not correlated with CK7 expression and could not predict it. Multivariate logistic regression analysis identified age (odds ratio [OR] = 0.953, 95% confidence interval [CI]: 0.909-0.999), wash-in pattern (OR = 0.180, 95% CI: 0.063-0.513) and enhancement homogeneity (OR = 11.610, 95% CI: 1.394-96.675) as independent factors related to CK7 positivity in ccRCC. Incorporating these variables into the predictive model resulted in areas under the receiver operating characteristic curve of 0.812 (95% CI: 0.711-0.913) for the training group and 0.792 (95% CI: 0.667-0.924) for the testing group. The calibration curve and DCA revealed that the model had good accuracy and clinical utility of the model.

CONCLUSION

The combination of multimodal ultrasound diagnostic techniques in constructing a predictive model for CK7 expression in ccRCC patients has significant predictive value.

UroPredict: Machine learning model on real-world data for prediction of kidney cancer recurrence (UroCCR-120)

Renal cell carcinoma (RCC) is most often diagnosed at a localized stage, where surgery is the standard of care. Existing prognostic scores provide moderate predictive performance, leading to challenges in establishing follow-up recommendations after surgery and in selecting patients who could benefit from adjuvant therapy. In this study, we developed a model for individual postoperative disease-free survival (DFS) prediction using machine learning (ML) on real-world prospective data. Using the French kidney cancer research network database, UroCCR, we analyzed a cohort of surgically treated RCC patients. Participating sites were randomly assigned to either the training or testing cohort, and several ML models were trained on the training dataset. The predictive performance of the best ML model was then evaluated on the test dataset and compared with the usual risk scores. In total, 3372 patients were included, with a median follow-up of 30 months. The best results in predicting DFS were achieved using Cox PH models that included 24 variables, resulting in an iAUC of 0.81 [IC95% 0.77-0.85]. The ML model surpassed the predictive performance of the most commonly used risk scores while handling incomplete data in predictors. Lastly, patients were stratified into four prognostic groups with good discrimination (iAUC = 0.79 [IC95% 0.74-0.83]). Our study suggests that applying ML to real-world prospective data from patients undergoing surgery for localized or locally advanced RCC can provide accurate individual DFS prediction, outperforming traditional prognostic scores.

Surgical Management and Oncologic Outcomes of Renal Cell Carcinoma and Inferior Vena Caval Thrombi With Aggressive Histologic Variants

OBJECTIVE

To characterize the surgical management, perioperative, and cancer-specific outcomes, and the influence of aggressive histologic variants (AHV) on operative management among patients with renal cell carcinoma (RCC) and inferior vena cava (IVC) thrombus. RCC with rhabdoid and/or sarcomatoid differentiation, which we defined as AHV, portends a worse prognosis. AHV can be associated with a desmoplastic reaction which may complicate resection.

METHODS

We reviewed patients undergoing radical nephrectomy and IVC thrombectomy between 1990 and 2020. Comparative statistics were employed as appropriate. Survival analysis was performed according to the Kaplan-Meier method, and intergroup analysis performed with log-rank statistics. Multivariable cox proportional hazards regression was used to assess the effect of AHV, age, thrombus level, vena cavectomy, metastases, and medical comorbidities on recurrence and overall survival (OS).

RESULTS

Ninety-four of 403 (23.3%) patients had AHV, including 43 (46%) rhabdoid, 39 (41%) sarcomatoid, and 12 (13%) with both. AHV were more likely to present with advanced disease; however, increased perioperative complications or decreased OS were not observed. Median (IQR) survival was 16.7 (4.8-47) months without AHV and 12.6 (4-29) months with AHV (P = .157). Sarcomatoid differentiation was independently associated with worse OS (HR = 2.016, CI 1.38-2.95, P <.001), whereas rhabdoid alone or with sarcomatoid demonstrated similar OS (P = 0.063).

CONCLUSION

RCC and IVC thrombus with AHV are more likely to present with metastatic disease, and sarcomatoid differentiation is associated with a worse OS. Resection of tumors with and without AHV have similar perioperative complications, suggesting that surgery can be safely accomplished in patients with RCC and IVC thrombus with AHV.

Predicting recurrence and survival in patients with non-metastatic renal-cell carcinoma after nephrectomy: a prospective population-based study with multicenter validation

BACKGROUND

Accurate prognostication of oncological outcomes is crucial for the optimal management of patients with renal cell carcinoma (RCC) after surgery. Previous prediction models were developed mainly based on retrospective data in the Western populations, and their predicting accuracy remains limited in contemporary, prospective validation. We aimed to develop contemporary RCC prognostic models for recurrence and overall survival (OS) using prospective population-based patient cohorts and compare their performance with existing, mostly utilized ones.

METHODS

In this prospective analysis and external validation study, the development set included 11  128 consecutive patients with non-metastatic RCC treated at a tertiary urology center in China between 2006 and 2022, and the validation set included 853 patients treated at 13 medical centers in the USA between 1996 and 2013. The primary outcome was progression-free survival (PFS), and the secondary outcome was OS. Multivariable Cox regression was used for variable selection and model development. Model performance was assessed by discrimination [Harrell's C-index and time-dependent areas under the curve (AUC)] and calibration (calibration plots). Models were validated internally by bootstrapping and externally by examining their performance in the validation set. The predictive accuracy of the models was compared with validated models commonly used in clinical trial designs and with recently developed models without extensive validation.

RESULTS

Of the 11  128 patients included in the development set, 633 PFS and 588 OS events occurred over a median follow-up of 4.3 years [interquartile range (IQR) 1.7-7.8]. Six common clinicopathologic variables (tumor necrosis, size, grade, thrombus, nodal involvement, and perinephric or renal sinus fat invasion) were included in each model. The models demonstrated similar C-indices in the development set (0.790 [95% CI 0.773-0.806] for PFS and 0.793 [95% CI 0.773-0.811] for OS) and in the external validation set (0.773 [0.731-0.816] and 0.723 [0.731-0.816]). A relatively stable predictive ability of the models was observed in the development set (PFS: time-dependent AUC 0.832 at 1 year to 0.760 at 9 years; OS: 0.828 at 1 year to 0.794 at 9 years). The models were well calibrated and their predictions correlated with the observed outcome at 3, 5, and 7 years in both development and validation sets. In comparison to existing prognostic models, the present models showed superior performance, as indicated by C-indices ranging from 0.722 to 0.755 (all P <0.0001) for PFS and from 0.680 to 0.744 (all P <0.0001) for OS. The predictive accuracy of the current models was robust in patients with clear-cell and non-clear-cell RCC.

CONCLUSIONS

Based on a prospective population-based patient cohort, the newly developed prognostic models were externally validated and outperformed the currently available models for predicting recurrence and survival in patients with non-metastatic RCC after surgery. The current models have the potential to aid in clinical trial design and facilitate clinical decision-making for both clear-cell and non-clear-cell RCC patients at varying risk of recurrence and survival.

Low nuclear expression of HIF-hydroxylases PHD2/EGLN1 and PHD3/EGLN3 are associated with poor recurrence-free survival in clear cell renal cell carcinoma

BACKGROUND

Hypoxia inducible factors, HIF-1α and HIF-2α, and their main regulators, the prolyl hydroxylase domain proteins (PHDs), mediate cellular response to hypoxia and contribute to tumor progression in clear cell renal cell carcinoma (ccRCC). These biomarkers may improve the value of traditional histopathological features in predicting disease progression after nephrectomy for localized ccRCC and guide patient selection for adjuvant treatments.

PATIENTS AND METHODS

In this study, we analyzed the associations of PHD2 and PHD3 with histopathological tumor features and recurrence-free survival (RFS) in a retrospective cohort of 173 patients who had undergone surgery for localized ccRCC at Helsinki University Hospital (HUH), Finland. An external validation cohort of 191 patients was obtained from Turku University Hospital (TUH), Finland. Tissue-microarrays (TMA) were constructed using the primary tumor samples. Clinical parameters and follow-up information from 2006 to 2019 were obtained from electronic medical records. The cytoplasmic and nuclear expression of PHD2, and PHD3 were scored based on immunohistochemical staining and their associations with histopathological features and RFS were evaluated.

RESULTS

Nuclear PHD2 and PHD3 expression in cancer cells were associated with lower pT-stage and Fuhrman grade compared with negative nuclei. Patients with positive nuclear expression of PHD2 and PHD3 in cancer cells had favorable RFS compared with patients having negative tumors. The nuclear expression of PHD2 was independently associated with a decreased risk of disease recurrence or death from RCC in multivariable analysis. These results were observed in both cohorts.

CONCLUSIONS

The absence of nuclear PHD2 and PHD3 expression in ccRCC was associated with poor RFS and the nuclear expression of PHD2 predicted RFS regardless of other known histopathological prognostic factors. Nuclear PHD2 and PHD3 are potential prognostic biomarkers in patients with localized ccRCC and should be further investigated and validated in prospective studies.

2018 Leibovich prognostic model for renal cell carcinoma: Performance in a large population with special consideration of Black race

BACKGROUND

The 2018 Leibovich prognostic model for nonmetastatic renal cell carcinoma (RCC) combines clinical, surgical, and pathologic factors to predict progression-free survival (PFS) and cancer-specific survival (CSS) for patients with clear cell (ccRCC), papillary (pRCC), and chromophobe (chRCC) histology. Despite high accuracy, <1% of the original cohort was Black. Here, the authors examined this model in a large population with greater Black patient representation.

METHODS

By using a prospectively maintained RCC institutional database, patients were assigned Leibovich model risk scores. Survival outcomes included 5-year and 10-year PFS and CSS. Prognostic accuracy was determined using area under the curve (AUC) analysis and calibration plots. Black patient subanalyses were conducted.

RESULTS

In total, 657 (29%) of 2295 patients analyzed identified as Black. Declines in PFS and CSS were observed as scores increased. Discrimination for ccRCC was strong for PFS (AUC: 5-year PFS, 0.81; 10-year PFS, 0.78) and for CSS (AUC: 5-year CSS, 0.82; 10-year CSS, 0.74). The pRCC AUC for PFS was 0.74 at 5 years and 0.71 at 10 years; and the AUC for CSS was 0.74 at 5 years and 0.70 at 10 years. In chRCC, better performance was observed for CSS (AUC at 5 years, 0.75) than for PFS (AUC: 0.66 at 5 years; 0.55 at 10 years). Black patient subanalysis revealed similar-to-improved performance for ccRCC at 5 years (AUC: PFS, 0.79; CSS, 0.87). For pRCC, performance was lower for PFS (AUC at 5 years, 0.63) and was similar for CSS (AUC at 5 years, 0.77). Sample size limited Black patient 10-year and chRCC analyses.

CONCLUSIONS

The authors externally validated the 2018 Leibovich RCC prognostic model and found optimal performance for ccRCC, followed by pRCC, and then chRCC. Importantly, the results were consistent in this large representation of Black patients.

PLAIN LANGUAGE SUMMARY

In 2018, a model to predict survival in patients with renal cell carcinoma (kidney cancer) was introduced by Leibovich et al. This model has performed well; however, Black patients have been under-represented in examination of its performance. In this study, 657 Black patients (29%) were included, and the results were consistent. This work is important for making sure the model can be applied to all patient populations.

Patients with high nuclear grade pT1-ccRCC are more suitable for radical nephrectomy than partial nephrectomy: a multicenter retrospective study using propensity score

BACKGROUND

Partial nephrectomy (PN) is usually recommended for T1 stage clear cell renal cell carcinoma (ccRCC) regardless of the nuclear grades. However, the question remains unresolved as to whether PN is non-inferior to RN in patients with T1-ccRCC at higher risk of recurrence. In fact, we found that patients with high nuclear grades treated with PN had poorer prognosis compared with those treated with radical nephrectomy (RN). Therefore, this study was designed to evaluate the associations of PN and RN in the four nuclear grade subsets with oncologic outcomes.

METHODS

A retrospective study was conducted in three Chinese urological centers that included 1,714 patients who underwent PN or RN for sporadic, unilateral, pT1, N0, and M0 ccRCC without positive surgical margins and neoadjuvant therapy between 2010 and 2019. Associations of nephrectomy type with local ipsilateral recurrence, distant metastases, and all-cause mortality (ACM) were evaluated using the Kaplan-Meier method and multivariable Cox proportional hazards regression models after overlap weighting (OW).

RESULTS

A total of 1675 patients entered the OW cohort. After OW, in comparison to PN, RN associated with a reduced risk of local ipsilateral recurrence in the G2 subset (HR = 0.148, 95% CI 0.046-0.474; p < 0.05), G3 subset (HR = 0.097, 95% CI 0.021-0.455; p < 0.05), and G4 subset (HR = 0.091, 95% CI 0.011-0.736; p < 0.05), and resulting in increased five-year local recurrence-free survival rates of 7.0%, 17.9%, and 36.2%, respectively. An association between RN and a reduced risk of distant metastases in the G4 subset (HR = 0.071, 95% CI 0.016-0.325; p < 0.05), with the five-year distant metastases-free survival rate increasing by 33.1% was also observed. No significant difference in ACM between PN and RN was identified.

CONCLUSIONS

Our findings substantiate that opting for RN, as opposed to PN, is more advantageous for local recurrence-free survival and distant metastases-free survival in patients with high nuclear grade (especially G4) pT1-ccRCC. We recommend placing a heightened emphasis on enhancing preoperative nuclear grade assessment, as it can significantly influence the choice of surgical plan.

TRIAL REGISTRATION

This study was registered at Chinese Clinical Trial Registry (ID: ChiCTR2200063333).

Prediction of clinically significant recurrence after partial nephrectomy. Data from the Cancer Registry of Norway with more than five years of follow-up

OBJECTIVE

To determine recurrence incidence after partial nephrectomy (PN) for renal cell carcinoma and identify predictors for local recurrence (LR) and metastasis.

MATERIAL AND METHODS

We retrospectively evaluated a cohort of 524 patients from the Cancer Registry of Norway, who underwent PN between January 2014 and December 2015 and were followed-up for >6 years. Patient demographics and pathological characteristics were correlated with recurrence and progression-free survival using Kaplan-Meier and Cox regression analyses.

RESULTS

Median patient age was 64 years, and the median tumour size was 2.6 cm. A positive surgical margin (PSM) was observed in 11% of the cases, while the LR and metastasis rates were 3.4% and 3.2%, respectively. PSM (hazard ratio [HR], 55.4; 95% confidence interval [CI], 12.55-244.6), tumour number (HR, 45.4; 95% CI, 6.5-316.1) and stage (HR, 33.5; 95% CI, 5.4-205.3) were independent predictors for LR. Undetermined margin status was also a risk factor for LR. Tumour stage (HR, 41.05; 95% CI, 8.52-197.76), tumour necrosis (HR, 1.3; 95% CI, 0.4-4.31) and age (HR, 1.07; 95% CI, 1.01-1.14) were predictors for metastasis.

CONCLUSIONS

Both local and distant recurrences after PN were rare, and the pT stage was a common predictor. PSM or indeterminate surgical margin and tumour number were LR predictors, while age at surgery and the presence of tumour necrosis predicted metastasis.

The incidence, pathogenesis, and management of non-clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is the most common type of kidney cancer and is divided into two distinct subtypes, clear cell renal cell carcinoma (ccRCC) and non-clear cell renal cell carcinoma (nccRCC). Although many treatments exist for RCC, these are largely based on clinical trials performed in ccRCC and there are limited studies on the management of nccRCC. Non-clear cell RCC consists of multiple histological subtypes: papillary, chromophobe, translocation, medullary, collecting duct, unclassified, and other rare histologies. Due to variations in pathogenesis and therapeutic response, therapy should be tailored to specific variant histologies. For patients with localized nccRCC, surgical resection remains the gold standard. In the metastatic setting, the standard of care has yet to be clearly defined, and most guidelines recommend clinical trial participation. General therapeutic options include immunotherapy, either as monotherapy or in combination, targeted therapies such as vascular endothelial growth factor tyrosine kinase inhibitors and MET inhibitors, and chemotherapy in certain subtypes. Here we present a review of the incidence and pathogenesis of the various subtypes, as well as available clinical data to support therapeutic recommendations for these subtypes. We also highlight currently available clinical trials in nccRCC and future directions in investigating novel treatment modalities tailored to patients with variant histology.

Prognostication for surgically treated papillary renal cell carcinoma: which model is the optimal choice?

Tweetable abstract Surgically treated papillary renal cell carcinoma shows distinct prognosis and needs specific prognostic models for counseling, follow-up and high-risk patient identification. Our goal is to summarize and compare currently recommended models.

The emerging landscape of neo/adjuvant immunotherapy in renal cell carcinoma

Adjuvant and neoadjuvant therapies that reduce the risk of renal cell carcinoma (RCC) recurrence remain an area of unmet need. Advances have been made in metastatic RCC recently by leveraging PD-1/PD-L1 immune checkpoint inhibitors (ICIs). These agents are currently being investigated in the adjuvant and neoadjuvant settings to determine if intervention early in the disease trajectory offers a clinically meaningful benefit. While a disease-free survival benefit has been demonstrated with pembrolizumab, results from other ICI studies have not been positive to date. More mature data from these studies are needed to determine whether there is a survival benefit to ICIs in the curative-intent setting. The success of ICIs has also ushered a new wave of studies combining ICIs with other agents such as targeted therapies and vaccines, which are in early stages of investigation. We review the current state of adjuvant/neoadjuvant therapy in RCC and highlight opportunities for ongoing study.

Adjuvant therapy for renal cell carcinoma: A systematic review of current landscape and future directions

The advent of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) has been transformative for the treatment of advanced renal cell carcinoma (RCC). Their efficacy post-surgical resection remains a contentious point. Various phase 3 RCTs have assessed their potency. Amongst evaluated agents, sunitinib and pembrolizumab have demonstrated notable disease-free survival benefits. Sunitinib's potential is diminished due to absence of clear overall survival (OS) benefits and side-effect profile. Pembrolizumab shows better tolerance, conclusive OS data are forthcoming. This scenario underscores the pressing need for advanced risk stratification methods and discovery of novel biomarkers. Existing strategies, largely pre-dating TKI and ICI therapeutic era, lack sufficient accuracy in predicting relapse-risk. Our review offers a comprehensive analysis of key phase 3 RCTs, focusing on TKIs, mTOR-inhibitors, and ICIs for adjuvant RCC treatment. The intent is to shed light on the intricate landscape of RCC treatment, guiding future research directions for optimizing patient outcomes.

Preoperative prognostic model for localized and locally advanced renal cell carcinoma: Michinoku Japan Urological Cancer Study Group

BACKGROUND

The Modified International Metastatic Renal Cell Carcinoma Dataset Consortium model (mIMDC) is a preoperative prognostic model for pT3cN0M0 renal cell carcinoma (RCC). This study aimed to validate the mIMDC and to construct a new model in a localized and locally advanced RCC (LLRCC).

METHODS

A database was established (the Michinoku Japan Urological Cancer Study Group database) consisting of 79 patients who were clinically diagnosed with LLRCC (cT3b/c/4NanyM0) and underwent radical nephrectomy from December 2007 to May 2018. Using univariable and multivariable analyses, we retrospectively analyzed disease-free survival (DFS) and overall survival (OS) in this database, constructed a new prognostic model according to these results, and estimated the model fit using c-index on the new and mIMDC models.

RESULTS

Independent poorer prognostic factors for both DFS and OS include the following: ≥ 1 Eastern Cooperative Oncology Group performance status, 2.0 mg/dL C-reactive protein, and > upper normal limit of white blood cell count. The median DFS in the favorable (no factor), intermediate (one factor), and poor-risk group (two or three factors) was 76.1, 14.3, and 4.0 months, respectively (P < 0.001). The 3-year OS in the favorable, intermediate, and poor-risk group were 92%, 44%, and 0%, respectively (P < 0.001). The c-indices of the new and mIMDC models were 0.67 and 0.60 for DFS (P = 0.060) and 0.74 and 0.63 for OS (P = 0.012), respectively.

CONCLUSION

The new preoperative prognostic model in LLRCC can be used in patient care and clinical trials.

Validation and comparison of prognostic value of different preoperative systemic inflammation indices in non-metastatic renal cell carcinoma

BACKGROUND

Several preoperative systemic inflammation indices have been proven to be correlated with the prognosis of patients diagnosed with non-metastatic renal cell carcinoma (RCC). However, these indices are currently not included in the main prognostic models, and few studies have compared the prognostic efficacy of different preoperative systemic inflammation indices.

PATIENTS AND METHODS

This retrospective study reviewed patients diagnosed with non-metastatic RCC who underwent nephrectomy at West China Hospital of Sichuan University from 2011 to 2013. Different preoperative systemic inflammation indices (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], monocyte-to-lymphocyte ratio [MLR], systemic immune-inflammation index [SII], and systemic inflammation response index [SIRI]) were calculated. Logistic regression was used to explore the relationship between systemic inflammation indices and clinical characteristics, and Cox regression was used to identify independent prognostic factors of overall survival (OS). The concordance index (c-index) was also calculated.

RESULTS

A total of 820 patients were included in the study, with a median follow-up of 78 months. Higher levels of NLR (> 3.04), PLR (> 147), MLR (> 0.32), SII (> 700), and SIRI (> 1.27) were found to be associated with more advanced tumor stage, higher Furman grade, and larger tumor size. In multivariate Cox regression, NLR, PLR, MLR, SII, and SIRI were identified as independent prognostic factors, and SII had the highest and most significant hazard ratio and the largest c-index.

CONCLUSION

In conclusion, various systemic inflammation indices were found to be associated with poorer OS. Among them, SII exhibited the highest predictive efficacy, suggesting its potential inclusion as a component in future prognostic models.

Prognostic value of preoperative microscopic hematuria in patients with non-metastatic renal cell carcinoma who underwent nephrectomy

BACKGROUND

Microscopic hematuria is associated with various urinary system diseases and is commonly used for the diagnosis of these conditions. Its prognostic role in non-metastatic renal cell carcinoma (RCC) patients who underwent nephrectomy remains unclear.

PATIENTS AND METHODS

A retrospective analysis of non-metastatic RCC patients who underwent nephrectomy in West China Hospital of Sichuan University from 2011 to 2013 was performed. Significant microscopic hematuria (SMH), defined as a threshold with a significant impact on disease-free survival (DFS) and overall survival (OS), was determined by Kaplan-Meier curves and the Maximally Selected Log-Rank Statistic. Kaplan-Meier curves were then used to estimate patients' DFS and OS, and the log-rank test was used to examine statistical significance. Logistic regression was utilized to identify clinical-pathological factors associated with SMH, while Cox regression was employed to determine independent factors of survival.

RESULTS

A total of 773 patients were included, and 20 red blood cells per high-power field was identified as the cutoff of SMH, of which 90 patients had preoperative SMH (11.6%) and 683 patients (88.4%) did not. Larger tumor size (OR = 1.10 [per cm], 95% CI 1.01-1.19, p = 0.036) and higher Fuhrman grade (grade 3 vs. grade 1-2, OR = 1.76, 95% CI 1.09-2.83, p = 0.02; grade 4 vs. grade 1-2, OR = 2.15, 95% CI 0.73-6.31, p = 0.164) were predictors of SMH. Compared to non-SMH patients, SMH patients had poorer DFS (HR = 3.16, 95% CI 2.07-4.83, p < 0.001) and OS (HR = 2.11, 95% CI 1.34-3.32, p = 0.001).

CONCLUSION

In summary, preoperative SMH is associated with larger tumor size and higher Fuhrman grade, and it is also independently correlated with poorer DFS and OS in non-metastatic RCC patients who underwent nephrectomy.

Validity of a multiphase CT-based radiomics model in predicting the Leibovich risk groups for localized clear cell renal cell carcinoma: an exploratory study

OBJECTIVE

To develop and validate a multiphase CT-based radiomics model for preoperative risk stratification of patients with localized clear cell renal cell carcinoma (ccRCC).

METHODS

A total of 425 patients with localized ccRCC were enrolled and divided into training, validation, and external testing cohorts. Radiomics features were extracted from three-phase CT images (unenhanced, arterial, and venous), and radiomics signatures were constructed by the least absolute shrinkage and selection operator (LASSO) regression algorithm. The radiomics score (Rad-score) for each patient was calculated. The radiomics model was established and visualized as a nomogram by incorporating significant clinical factors and Rad-score. The predictive performance of the radiomics model was evaluated by the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA).

RESULTS

The AUC of the triphasic radiomics signature reached 0.862 (95% CI: 0.809-0.914), 0.853 (95% CI: 0.785-0.921), and 0.837 (95% CI: 0.714-0.959) in three cohorts, respectively, which were higher than arterial, venous, and unenhanced radiomics signatures. Multivariate logistic regression analysis showed that Rad-score (OR: 4.066, 95% CI: 3.495-8.790) and renal vein invasion (OR: 12.914, 95% CI: 1.118-149.112) were independent predictors and used to develop the radiomics model. The radiomics model showed good calibration and discrimination and yielded an AUC of 0.872 (95% CI: 0.821-0.923), 0.865 (95% CI: 0.800-0.930), and 0.848 (95% CI: 0.728-0.967) in three cohorts, respectively. DCA showed the clinical usefulness of the radiomics model in predicting the Leibovich risk groups.

CONCLUSIONS

The radiomics model can be used as a non-invasive and useful tool to predict the Leibovich risk groups for localized ccRCC patients.

CRITICAL RELEVANCE STATEMENT

The triphasic CT-based radiomics model achieved favorable performance in preoperatively predicting the Leibovich risk groups in patients with localized ccRCC. Therefore, it can be used as a non-invasive and effective tool for preoperative risk stratification of patients with localized ccRCC.

KEY POINTS

• The triphasic CT-based radiomics signature achieves better performance than the single-phase radiomics signature. • Radiomics holds prospects in preoperatively predicting the Leibovich risk groups for ccRCC. • This study provides a non-invasive method to stratify patients with localized ccRCC.

Antiglomerular Basement Membrane Disease Possibly Triggered by Undiagnosed Renal Cell Carcinoma: A Case Report

Antiglomerular basement membrane (anti-GBM) disease is a rare, small-vessel vasculitis that affects the capillary beds of the kidneys and lungs. Although exceedingly rare, several case reports have described anti-GBM disease with a concurrent cancer diagnosis, suggesting a possible correlation between these 2 conditions. Herein, we describe the first known case to our knowledge of a woman in her early 60s with simultaneous anti-GBM disease and clear cell renal cell carcinoma, in which the tumor was thought to have been the substrate for anti-GBM disease. We believe that renal cell carcinoma may have contributed to the production of anti-GBM autoantibodies and, thus, anti-GBM disease. The concurrence of these 2 conditions complicated the treatment of the patient, who was hemodialysis-dependent at the time of hospital discharge. This report highlights the importance of considering anti-GBM disease as a potential diagnosis in patients with acute kidney failure, and how important it is to identify both clear cell renal cell carcinoma and anti-GBM disease at an early stage to improve outcomes.

Serum uric acid and triglycerides in clear cell renal cell carcinoma: A restrospective cross-sectional study

The available evidence on the relationship between serum uric acid and triglycerides in clear cell renal cell carcinoma (ccRCC) is limited. The objective of this study is to investigate whether there is an independent association between serum uric acid and triglycerides in ccRCC, while adjusting for other variables. This cross-sectional study involved 1018 participants with ccRCC, who were admitted to a hospital in China from December 1st, 2013 to January 1st, 2023. The main independent variable investigated was serum uric acid, which was measured at baseline. The dependent variable was triglycerides. Covariates considered in this study included age, sex, body mass index, smoking status, hypertension, diabetes, coronary disease, High-density lipoprotein cholesterol, Low-density lipoprotein cholesterol, Total cholesterol, Blood urea nitrogen, and Creatinine. The study included 1018 participants with an average age of 56.92 ± 10.88 years old, and approximately 68% of them were male. The fully-adjusted linear regression analysis indicated a positive association between serum uric acid levels (100μmol/L) and triglyceride levels (mmol/L) after adjusting for confounding factors (β = 0.13, 95% CI [0.07, 0.18]). Furthermore, a smooth curve was constructed between serum uric acid and triglycerides based on the fully-adjusted model. In patients with ccRCC, there was a positive association between serum uric acid and triglycerides.

Development and External Validation of a Novel Nomogram Predicting Cancer-specific Mortality-free Survival in Surgically Treated Papillary Renal Cell Carcinoma Patients

BACKGROUND

Accurate prediction of cancer control outcomes in renal cell carcinoma (RCC) patients is important for counselling, follow-up planning, and selection of appropriate adjuvant trial designs.

OBJECTIVE

To develop and externally validate a novel contemporary population-based model for predicting cancer-specific mortality-free survival (CSM-FS) in surgically treated papillary RCC (papRCC) patients and to compare it with established risk categories (Leibovich 2018).

DESIGN, SETTING, AND PARTICIPANTS

Within the Surveillance, Epidemiology, and End Results database (2004-2019), we identified surgically treated papRCC patients (n = 3978). The population was randomly divided into development (50%, n = 1989) and external validation (50%, n = 1989) cohorts. Of the external validation cohort, 97% (n = 1930) of patients were included in a head-to-head comparison of the Leibovich 2018 risk categories addressing nonmetastatic patients.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Univariable Cox regression models tested the statistical significance in the prediction of CSM-FS. The most parsimonious model with the best validation metrics was selected as the multivariable nomogram. Accuracy, calibration, and decision curve analyses (DCAs) tested the Cox regression-based nomogram, as well as the Leibovich 2018 risk categories in the external validation cohort.

RESULTS AND LIMITATIONS

Age at diagnosis, grade, T stage, N stage, and M stage qualified for inclusion in the novel nomogram. In external validation, the accuracy of the novel nomogram was 0.83 at 5 yr and 0.80 at 10 yr. In nonmetastatic patients, 5- and 10-yr accuracy of the novel nomogram was 0.77 and 0.76, respectively. Conversely, 5- and 10-yr accuracy of the Leibovich 2018 risk categories was 0.70 and 0.66, respectively. The novel nomogram exhibited smaller departures from ideal predictions in calibration plots and higher net benefit in DCAs, when it was compared with the Leibovich 2018 risk categories. Limitations include the retrospective nature of the study, absence of a central pathological review, and inclusion of only North American patients.

CONCLUSIONS

The novel nomogram may represent a valuable clinical aid, when papRCC CSM-FS predictions are required.

PATIENT SUMMARY

We developed an accurate tool to predict death due to papillary kidney cancer in a North American population.

Meta-analysis of perioperative immunotherapy in renal cell carcinoma: Available, but the jury is still out

INTRODUCTION

While surgical management of renal cell carcinoma (RCC) is curative for many patients, others may relapse and could benefit from adjuvant treatments. Immune checkpoint inhibitors (ICI) have been proposed as a potential adjuvant therapy for improving survival in these patients, but the benefit/risk ratio of ICI in the perioperative setting remains unclear.

METHODS

A systematic review and a meta-analysis of phase III trials of perioperative ICI (anti PD1/PD-L1 alone or in combination with anti-CTLA4 agents) in RCC was conducted.

RESULTS

The analysis included results from 4 phase III trials, comprising 3,407 patients. ICI did not show a significant increase in disease-free survival (Hazard Ratio [HR] 0.85; 95% confidence interval [CI] 0.69-1.04; p: 0.11) or overall survival [OS] (HR 0.73; 95% CI 0.40-1.34; p: 0.31). High-grade adverse events were more frequent in the immunotherapy arm (OR 2.65; 95% CI 1.53-4.59; p: <0.001), and high-grade treatment-related adverse events were 8 times more frequent in the experimental arm (OR: 8.07; 95% CI: 3.14-20.75; p: <0.001). Subgroup analyses showed statistically significant differences favoring the experimental arm in females (HR: 0.71; 95 CI 0.55-0.92; p: 0.009), in sarcomatoid differentiation (HR: 0.60 95% CI 0.41-0.89; p: 0.01), and PD-L1 positive tumors (HR HR: 0.74; 95% CI 0.61-0.90; p: 0.003). No significant effect was found in patients according to age, type of nephrectomy (radical vs. partial), and stage (M1 without evidence of disease vs. M0 patients).

CONCLUSION

Our comprehensive meta-analysis generally suggests that immunotherapy does not confer a survival advantage in the perioperative setting for RCC, with the exception of one positive study. While the overall results are not statistically significant, individual patient factors and other variables may play a role in determining who benefits from immunotherapy. Therefore, despite the mixed findings, immunotherapy may still be a viable treatment option for certain patients, and further studies are needed to determine which patient subgroups would be most likely to benefit.

SLUG and SNAIL as Potential Immunohistochemical Biomarkers for Renal Cancer Staging and Survival

Renal cell carcinoma (RCC) is the deadliest urological neoplasm. Up to date, no validated biomarkers are included in clinical guidelines for the screening and follow up of patients suffering from RCC. Slug (Snail2) and Snail (Snail1) belong to the Snail superfamily of zinc finger transcriptional factors that take part in the epithelial-mesenchymal transition, a process important during embryogenesis but also involved in tumor progression. We examined Slug and Snail immunohistochemical expression in patients with different stages of renal cell carcinomas with the aim to investigate their potential role as staging and prognostic factors. A total of 166 samples of malignant renal cell neoplasms were analyzed using tissue microarray and immunohistochemistry. Slug and Snail expressions were evaluated qualitatively (presence or absence), in nuclear and cytoplasmic cell compartments and compared in relation to clinical parameters. The Kaplan-Meier survival analysis showed the impact of the sarcomatoid component and Slug expression on the survival longevity. Cox regression analysis separated Slug as the only independent prognostic factor (p = 0.046). The expression of Snail was associated with higher stages of the disease (p = 0.004), especially observing nuclear Snail expression (p < 0.001). All of the tumors that had metastasized showed nuclear immunoreactivity (p < 0.001). In clear cell RCC, we showed a significant relationship between a high nuclear grade and nuclear Snail expression (p = 0.039). Our results suggest that Slug and Snail could be useful immunohistochemical markers for staging and prognosis in patients suffering from various RCCs, representing potential targets for further therapy strategies of renal cancer.

Adjuvant immunotherapy for locally advanced renal cell carcinoma

INTRODUCTION

Locally advanced renal cell carcinoma (RCC) presents a therapeutic challenge due to 20-40% relapse risk post-nephrectomy. There has been substantial interest in utilizing immunotherapy interrupting the PD-1/PD-L1 axis in the perioperative space, especially in the adjuvant setting, in order to minimize such risk.

AREAS COVERED

We conducted a PubMed search using the terms 'adjuvant' and 'RCC.' We begin by examining landmark studies in the postoperative space for locally advanced RCC, with special emphasis on immunotherapeutic biologics. Important considerations are outlined in an effort to explain the conflicting data on the benefit of adjuvant immunotherapy as well as to adequately assess the magnitude of potential benefit of the recently approved adjuvant pembrolizumab. Relevant contemporary challenges and opportunities as well as future directions of the field are also discussed.

EXPERT OPINION

Systemic immunotherapy with monoclonal antibodies targeting the PD-1/PD-L1 axis likely holds promise, either alone or potentially in combinations, in minimizing recurrence risk for locally advanced RCC. However, emphasis on post-protocol care, robust endpoint selection, and continued work and validation on predictive biomarkers are needed to confidently select those patients that may benefit the most and minimize biologic and financial toxicity.

Comparison and validation of different risk models for papillary renal cell carcinoma

BACKGROUND

Several prognostic algorithms were specifically or nonspecifically used for papillary renal cell carcinoma (PRCC). No consensus was reached upon their efficacy of discrimination. We aim to compare the stratifying ability of current models or systems in predicting the risk of recurrence of PRCC.

METHODS

A PRCC cohort consisting of 308 patients from our institution and 279 patients from The Cancer Genome Atlas (TCGA) was generated. With ISUP grade, TNM classification, UCLA Integrated Staging System (UISS), STAGE, SIZE, GRADE AND NECROSIS (SSIGN), Leibovich model and VENUSS system, recurrence-free survival (RFS), disease-specific survival (DSS) and overall survival (OS) were studied using Kaplan-Meier method and concordance index (c-index) was compared. Differences between risk groups in gene mutation and infiltration of inhibitory immune cells were studied with TCGA database.

RESULTS

All the algorithms were able to stratify patients in RFS as well as DSS and OS (all P < 0.001). VENUSS score and risk group generally had the highest and balanced c-index (0.815 and 0.797 for RFS). ISUP grade, TNM stage and Leibovich model had the lowest c-indexes in all analysis. Among the 25 most frequently mutated genes in PRCC, eight had different mutation frequency between VENUSS low- and intermediate-/high-risk patients and mutated KMT2D and PBRM1 resulted in worsened RFS (P = 0.053 and P = 0.007). Increased Treg cells in tumors of intermediate-/high- risk patients were also identified.

CONCLUSIONS

VENUSS system showed better predictive accuracy in RFS, DSS and OS compared with SSIGN, UISS and Leibovich risk models. VENUSS intermediate-/high-risk patients had increased frequency of mutation in KMT2D and PBRM1 and increased infiltration of Treg cells.

The Impact of Metastasectomy on Survival Outcomes of Renal Cell Carcinoma: A 10-Year Single Center Experience

OBJECTIVES

The role of surgical metastasectomy (MST) in solitary or oligometastasis from renal cell carcinoma (RCC) and its impact on survival outcomes remains poorly addressed. We evaluated the impact of MST on overall survival (OS) in patients with oligometastatic (m)RCC.

MATERIALS AND METHODS

The institutional renal cancer prospective database was examined for cases treated with partial or radical nephrectomy who developed metastatic disease during follow-up. Patients with evidence of clinical metastasis at first diagnosis were excluded. Patients considered unfit for MST received systemic treatment (ST); all others received MST. The impact of MST vs. the ST only cohort was assessed with the Kaplan-Meier method. Age, gender, bilaterality, histology, AJCC stage of primary tumor, surgical margins, local vs. distant metastasis and MST were included in univariable and multivariable regression analyses to assess the predictors of OS.

RESULTS

Overall, at a median follow-up of 16 months after primary treatment, 168 patients with RCC developed asynchronous metastasis at the adrenal gland, lung, liver, spleen, peritoneal, renal fossa, bone, nodes, brain and thyroid gland. Nine patients unfit for any treatment were excluded. The site of metastasis was treated with surgical MST (77/159, 48.4%), with or without previous or subsequent ST, while 82/159 cases (51.2%) received ST only. The 2-year, 5-year and 10-year OS probabilities were 93.8%, 82.8% and 79.5%, respectively. After multivariable analysis, MST and the primary tumor AJCC stage were independent predictors of OS probabilities (p = 0.019 and p = 0.035, respectively). After Kaplan-Meier analysis, MST significantly improved OS probabilities versus patients receiving ST (p < 0.001).

LIMITATIONS

The main drawbacks of our research were the small sample size from a single-tertiary referral institution, as well as the absent or different ST lines in the cohort of patients receiving MST.

CONCLUSIONS

When an NED status is achievable, surgical MST of mRCC significantly impacts OS, delaying and not precluding further subsequent ST.

Recent Advances in the Management of Clear Cell Renal Cell Carcinoma: Novel Biomarkers and Targeted Therapies

Renal cell carcinoma (RCC) belongs to a heterogenous cancer group arising from renal tubular epithelial cells. Among RCC subtypes, clear cell renal cell carcinoma (ccRCC) is the most common variant, characterized by high aggressiveness, invasiveness and metastatic potential, features that lead to poor prognosis and high mortality rate. In addition, diagnosis of kidney cancer is incidental in the majority of cases, and this results in a late diagnosis, when the stage of the disease is advanced and the tumor has already metastasized. Furthermore, ccRCC treatment is complicated by its strong resistance to chemo- and radiotherapy. Therefore, there is active ongoing research focused on identifying novel biomarkers which could be useful for assessing a better prognosis, as well as new molecules which could be used for targeted therapy. In this light, several novel targeted therapies have been shown to be effective in prolonging the overall survival of ccRCC patients. Thus, the aim of this review is to analyze the actual state-of-the-art on ccRCC diagnosis, prognosis and therapeutic options, while also reporting the recent advances in novel biomarker discoveries, which could be exploited for a better prognosis or for targeted therapy.

Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma

Within the Surveillance, Epidemiology, and End Results database (2000–2019), we identified 5522 unilateral surgically treated non-metastatic chromophobe kidney cancer (chRCC) patients. This population was randomly divided into development vs. external validation cohorts. In the development cohort, the original Leibovich 2018 and GRANT categories were applied to predict 5- and 10-year cancer-specific survival (CSS). Subsequently, a novel multivariable nomogram was developed. Accuracy, calibration and decision curve analyses (DCA) tested the Cox regression-based nomogram as well as the Leibovich 2018 and GRANT risk categories in the external validation cohort. The accuracy of the Leibovich 2018 and GRANT models was 0.65 and 0.64 at ten years, respectively. The novel prognostic nomogram had an accuracy of 0.78 at ten years. All models exhibited good calibration. In DCA, Leibovich 2018 outperformed the novel nomogram within selected ranges of threshold probabilities at ten years. Conversely, the novel nomogram outperformed Leibovich 2018 for other values of threshold probabilities. In summary, Leibovich 2018 and GRANT risk categories exhibited borderline low accuracy in predicting CSS in North American non-metastatic chRCC patients. Conversely, the novel nomogram exhibited higher accuracy. However, in DCA, all examined models exhibited limitations within specific threshold probability intervals. In consequence, all three examined models provide individual predictions that might be suboptimal and be affected by limitations determined by the natural history of chRCC, where few deaths occur within ten years from surgery. Further investigations regarding established and novel predictors of CSS and relying on large sample sizes with longer follow-up are needed to better stratify CSS in chRCC.

Post nephrectomy management of localized renal cell carcinoma. From risk stratification to therapeutic evidence in an evolving clinical scenario

Standard treatment for localized non-metastatic renal cell carcinoma (RCC) is radical or partial nephrectomy. However, after radical surgery, patients with stage II-III have a substantial risk of relapse (around 35%). To date a unique standardized classification for the risk of disease recurrence still lack. Moreover, in the last years great attention has been focused in developing systemic therapies with the aim of improving the disease-free survival (DFS) of high-risk patients, with negative results from adjuvant VEGFR-TKIs. Therefore, there is still a need for developing effective treatments for radically resected RCC patients who are at intermediate/high risk of relapse. Recently, interesting results came from immune-checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 pathway, with a significant benefit in terms of disease-free survival from adjuvant pembrolizumab. However, the conflicting results of diverse clinical trials investigating different ICI-based regimens in the adjuvant setting, together with the still immature data on the overall survival advantage of immunotherapy, requires careful considerations. Furthermore, several questions remain unanswered, primarily regarding the selection of patients who could benefit the most from immunotherapy. In this review, we have summarized the main clinical trials investigating adjuvant therapy in RCC, with a particular focus on immunotherapy. Moreover, we have analyzed the crucial issue of patients' stratification according to the risk of disease recurrence, and we have described the possible future prospective and novel agents under evaluation for perioperative and adjuvant therapies.

CXCR3 Expression Is Associated with Advanced Tumor Stage and Grade Influencing Survival after Surgery of Localised Renal Cell Carcinoma

BACKGROUND

Surgery is the standard treatment in localized renal cell carcinoma (RCC). Pembrolizumab is now approved for adjuvant therapy in high-risk patients. However, inhomogeneity of studies gives ambiguity which patient benefit most from adjuvant therapy. A high infiltration of CD8⁺ T cells is known to be linked with poor prognosis in RCC. CXCR3 is a key player of CD8⁺ T cell differentiation and infiltration. We aimed to evaluate CXCR3 as a potential marker for predicting recurrence.

METHODS

CXCR3 and immune cell subsets (CD4, CD8, CD68 and FoXP3) were measured on RCC samples by multiplex immunofluorescence (mIF) staining. Cellular localization of CXCR3 was evaluated using single-cell RNA analysis on a publicly available dataset.

RESULTS

Tumor samples of 42 RCC patients were analyzed, from which 59.5% were classified as clear-cell RCC and of which 20 had recurrence. Single-cell RNA analysis revealed that CXCR3 was predominantly expressed in intratumoral T cells and dendritic cells. CXCR3 expression was higher in advanced tumors stages (p = 0.0044) and grade (p = 0.0518), correlating significantly with a higher CD8⁺ T cell expression (p < 0.001). Patients with CXCR3^high RCCs had also a significant shorter RFS compared to CXCR3^low (median: 78 vs. 147 months, p = 0.0213). In addition, also tumor stage pT3/4 (p < 0.0001) as well as grade G3/4 (p = 0.0008) negatively influenced RFS.

CONCLUSION

CXCR3^high cell density was associated with high T cell infiltration and advanced tumor stage, worsening RFS in surgically resected RCC patients. Beside its prognostic value, CXCR3 might be a predictive biomarker to guide therapy decision for adjuvant therapy in localized RCC.