Predicting Oncologic Outcomes in Renal Cell Carcinoma After Surgery

doi:10.1016/j.eururo.2018.01.005

European Urology

Volume 73, Issue 5, May 2018, Pages 772-780

https://doi.org/10.1016/j.eururo.2018.01.005 Get rights and content

Abstract

Background

Predicting oncologic outcomes is important for patient counseling, clinical trial design, and biomarker study testing.

Objective

To develop prognostic models for progression-free (PFS) and cancer-specific survival (CSS) in patients with clear cell renal cell carcinoma (ccRCC), papillary RCC (papRCC), and chromophobe RCC (chrRCC).

Design, setting, and participants

Retrospective cohort review of the Mayo Clinic Nephrectomy registry from 1980 to 2010, for patients with nonmetastatic ccRCC, papRCC, and chrRCC.

Intervention

Partial or radical nephrectomy.

Outcome measurements and statistical analysis

PFS and CSS from date of surgery. Multivariable Cox proportional hazards regression was used to develop parsimonious models based on clinicopathologic features to predict oncologic outcomes and were evaluated with c-indexes. Models were converted into risk scores/groupings and used to predict PFS and CSS rates after accounting for competing risks.

Results and limitations

A total of 3633 patients were identified, of whom 2726 (75%) had ccRCC, 607 (17%) had papRCC, and 222 (6%) had chrRCC. Models were generated for each histologic subtype and a risk score/grouping was developed for each subtype and outcome (PFS/CSS). For PFS, the c-indexes were 0.83, 0.77, and 0.78 for ccRCC, papRCC, and chrRCC, respectively. For CSS, c-indexes were 0.86 and 0.83 for ccRCC and papRCC. Due to only 22 deaths from RCC, we did not assess a multivariable model for chrRCC. Limitations include the single institution study, lack of external validation, and its retrospective nature.

Conclusions

Using a large institutional experience, we generated specific prognostic models for oncologic outcomes in ccRCC, papRCC, and chrRCC that rely on features previously shown—and validated—to be associated with survival. These updated models should inform patient prognosis, biomarker design, and clinical trial enrollment.

Patient summary

We identified routinely available clinical and pathologic features that can accurately predict progression and death from renal cell carcinoma following surgery. These updated models should inform patient prognosis, biomarker design, and clinical trial enrollment.

Introduction

Renal cell carcinoma (RCC) represents a common urologic malignancy, with almost 64 000 cases and 14 400 deaths expected in 2017 [1]. While there is a strong association between pathologic stage and the risk of death [2], stage alone is insufficient to inform prognosis for most patients. Indeed, it has been shown that beyond American Joint Committee on Cancer (AJCC) stage other important factors to consider include manner of presentation, histology, grade, and associated findings such as the presence of histologic tumor necrosis or sarcomatoid features [3], [4], [5]. This variability in the behavior of RCC suggests the need for better methods to guide prognostication following surgery.

To this end, there have been numerous preoperative and postoperative nomograms designed for different outcomes in RCC [4], [5], [6], [7], [8], [9], [10]. Unfortunately, there are limitations with this myriad of models for risk prediction. Perhaps the most significant limitations have been the use of AJCC staging as a predictor of outcome and the failure to consider primary histology. While staging of RCC has been relatively constant, over the lifetime of the AJCC staging manual there have been subtle changes—such as the subdivision of cT1 into cT1a and cT1b with the advent of the seventh edition [11]—in the staging of RCC, which raises questions about the long-term applicability of models based on a given AJCC staging edition. Furthermore, while some models have been validated, their clinical utility has been limited by a dearth of functional tools for application in routine practice. Lastly, and most importantly, risk models to date have largely focused on clear cell RCC (ccRCC), neglecting the significant subset of patients with nonclear cell histologies [12]. Therefore, we sought to generate prognostic models for progression and death from RCC, accounting for all major histologic subtypes, and to operationalize these models into an easy-to-use clinical application.

Section snippets

Materials and methods

After obtaining Institutional Review Board approval, the Mayo Clinic Nephrectomy Registry was queried to identify binephric patients treated with radical or partial nephrectomy between 1980 and 2010 for sporadic, unilateral, nonmetastatic RCC. Clinical features abstracted included age at surgery, year of surgery, sex, race, presence of symptoms at diagnosis, smoking status, body mass index, Eastern Cooperative Oncology Group performance status, Charlson comorbidity score, preoperative estimated

Results

A total of 3633 patients were identified, of whom 2726 (75%) were diagnosed with ccRCC, while 607 (17%) had papRCC, and 222 (6%) had chromophobe (chrRCC). Of the remaining patients (excluded from analysis), clear cell papillary RCC was present in 32 (1%), RCC not otherwise specified in 31 (1%), collecting duct in seven (< 1%), and other rare subtypes in eight (< 1%). Clinicopathologic features for ccRCC, papRCC, and chrRCC are summarized in Table 1.

Discussion

Using a large institutional experience with RCC, we have generated prognostic models for each of the three most common RCC subtypes—ccRCC, papRCC, and chrRCC. These models are based on routine clinicopathologic information that is readily available following surgical resection and that does not rely upon the current AJCC staging manual. These models performed well, with excellent discrimination, and retained their ability to stratify patients by outcomes after accounting for the competing risk

Conclusions

Using a large institutional experience with pathologic rereview, we identified features associated with progression and death from RCC that are specific to histologic subtype and take into account known differences in predictive features within a given histology. Furthermore, our model does not rely on current AJCC staging, a purposeful choice in order to limit obsolescence as updated staging guidelines are put forth. Finally, each model had excellent discrimination, stratified patient

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Predictive Model of CK7 Expression in Patients With Clear Cell Renal Cell Carcinoma by Combined Multimodal Ultrasound Diagnostic Techniques: A Retrospective Study
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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.
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.
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.
The combination of multimodal ultrasound diagnostic techniques in constructing a predictive model for CK7 expression in ccRCC patients has significant predictive value.
Surgical Management and Oncologic Outcomes of Renal Cell Carcinoma and Inferior Vena Caval Thrombi With Aggressive Histologic Variants
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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.
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).
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).
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.
Adjuvant therapy for renal cell carcinoma: A systematic review of current landscape and future directions
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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.
Antiglomerular Basement Membrane Disease Possibly Triggered by Undiagnosed Renal Cell Carcinoma: A Case Report
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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.
Meta-analysis of perioperative immunotherapy in renal cell carcinoma: Available, but the jury is still out
2023, Urologic Oncology: Seminars and Original Investigations
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.
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.
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).
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.
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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.
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).
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.
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.
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.
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Platinum Priority – Kidney CancerEditorial by Umberto Capitanio, Alessandro Larcher, Francesco Montorsi and Pierre Karakiewiczc on pp. 781–782 of this issuePredicting Oncologic Outcomes in Renal Cell Carcinoma After Surgery

Abstract

Background

Objective

Design, setting, and participants

Intervention

Outcome measurements and statistical analysis

Results and limitations

Conclusions

Patient summary

Introduction

Section snippets

Materials and methods

Results

Discussion

Conclusions

J Urol

J Urol

Eur Urol

J Urol

Eur Urol

Hum Pathol

Grade, and Necrosis (SSIGN) Score for clear cell renal cell carcinoma in contemporary patients. Eur Urol

J Urol

Hum Pathol

Clin Genitourin Cancer

J Urol

Cancer statistics, 2017

Cancer J Clin

The International Society of Urological Pathology (ISUP) grading system for renal cell carcinoma and other prognostic parameters

Am J Surg Pathol

Prediction of progression after radical nephrectomy for patients with clear cell renal cell carcinoma: a stratification tool for prospective clinical trials

Cancer

Platinum Priority – Kidney Cancer
Editorial by Umberto Capitanio, Alessandro Larcher, Francesco Montorsi and Pierre Karakiewiczc on pp. 781–782 of this issue
Predicting Oncologic Outcomes in Renal Cell Carcinoma After Surgery