Validation of the current prognostic models for nonmetastatic renal cell carcinoma after nephrectomy in Chinese population: a 15-year single center experience

Prognostic analysis of postoperative clinically nonmetastatic renal cell carcinoma

Objectives

To investigate the survival characteristics of postoperative nonmetastatic renal cell carcinoma (RCC) patients, and the predictive value of a prognostic model.

Materials and Methods

We retrospectively evaluated data from 1202 postoperative nonmetastatic RCC patients who were treated between 1999 and 2012 at West China Hospital, Sichuan University (Chengdu, China). In addition, we also evaluated data relating to 53 205 cases acquired from the Surveillance, Epidemiology, and End Results (SEER) program. Survival analysis was performed on the cases, and subgroups, using the Kaplan‐Meier and Cox regression methods. The concordance index of the Stage Size Grade Necrosis (SSIGN), Leibovich, and the UCLA integrated staging system, scores was determined to evaluate the accuracy of these outcome prediction models.

Results

The 5‐year overall survival rate for RCC cases in West China Hospital was 87.6%; this was higher than that observed for SEER cases. Survival analysis identified several factors that exerted significant influence over prognosis, including the time of surgery, Eastern Cooperative Oncology Group performance status, tumor stage, size, nuclear differentiation, pathological subtypes, along with necrotic and sarcomatoid differentiation. Moreover tumor stage, size, and nuclear grade were all identified as independent predictors for both our cases and those from the SEER program. Patient groups with advanced RCC, and poorly differentiated RCC subgroups, were both determined to have a poor prognosis. The SSIGN model yielded the best predictive value as a prognostic model, followed by the Leibovich, and UCLA integrated staging system; this was the case for our patients, and for sub‐groups with a poor prognosis.

Conclusion

The prognosis of RCC was mostly influenced by tumor stage, size, and nuclear differentiation. SSIGN may represent the most suitable prognostic model for the Chinese population.

J. Risk models for patients with localised renal cell carcinoma

INTRODUCTION

We conducted a retrospective analysis of our series to assess the factors that influenced disease-free survival (DFS) and cancer-specific survival (CSS) for patients with localised renal cell carcinoma (RCC). We also created our own risk groups.

MATERIAL AND METHODS

Between January 1990 and December 2012, 596 patients underwent surgery for localised RCC (clear cell, papillary or chromophobe). Using Cox regression models, we analysed the clinical-pathological variables that influenced DFS and CSS and designed risk groups for DFS and CSS with the variables.

RESULTS

The median follow-up for the series was 5.96 years. By the end of the study, 112 patients (18.8%) had a recurrence of the disease, with DFS rates of 82%, 77% and 72% at 5, 10 and 15 years, respectively. The independent factors that influenced DFS in the multivariate study were the following: A Furhman grade of 3-4, haematuria, lymphocytic or vascular invasion, the presence of tumour necrosis and a disease stage pT3-pT4. Furthermore, by the end of the study, 57 patients (9.6%) died due to renal cancer, with CSS rates of 92%, 86% and 83% at 5, 10 and 15 years, respectively. The independent factors that influenced CSS in the multivariate study were the following: A Furhman grade of 3-4, perinephric fat invasion and the presence of tumour necrosis.

CONCLUSIONS

Factors in addition to the disease stage pT3-pT4 in patients with localised RCC are important, such as the presence of haematuria and lymphocytic or vascular invasion for DFS. A Furhman grade of 3-4 and the presence of tumour necrosis are especially relevant for DFS and CSS.

Accuracy capabilities comparisons between Karakiewicz, Kattan and Cindolo nomograms in predicting outcomes for renal cancer carcinoma: A systematic review and meta-analysis

INTRODUCTION

Several prognostic models have been proposed to predict outcomes of patients affected by renal cell carcinoma. We analyze the discriminative capabilities of Karakiewicz, Kattan and Cindolo nomograms and perform a meta-analysis to yield pooled area under the receiver operator curves (AUCs) for model comparison. The end points of interest were disease-recurrence free survival (DFS) and cancer-specific survival (CSS).

METHODS

An electronic search of the Medline and Embase was undertaken until July 2014. The AUC value, total number of patients, number of disease recurrence, and cancer-related deaths were extracted from the included references. AUCs of the models were converted to odds ratios (ORs). For the meta-analysis, ln(OR) was used for data pooling. For each nomogram, the combined OR was transformed back to a converted AUC (cAUC).

RESULTS

A total of 16 studies were identified including 26 710 patients. The derived comparison of cAUC values revealed better predictive capability of DFS for the postoperative Karakiewicz nomogram versus Kattan nomogram (p < 0.01), but not versus Cindolo (p = 0.432) and between Cindolo versus Kattan (p = 0.03). The Mantel-Haenszel derived comparison of cAUC values revealed better predictive capability for the preoperative Karakiewicz nomogram versus the Kattan nomogram (p < 0.01) and versus the Cindolo model (p < 0.01), but also between the postoperative Karakiewicz model versus the Kattan model (p < 0.01) and the Cindolo model (p < 0.01). The Kattan model showed better discriminative capability versus the Cindolo model (p < 0.01).

CONCLUSIONS

The predictive abilities of the pre- and postoperative Karakiewicz models are higher than Kattan or Cindolo in predicting DFS and CSS.

Decision curve analysis and external validation of the postoperative Karakiewicz nomogram for renal cell carcinoma based on a large single-center study cohort

PURPOSE

To predict outcome of patients with renal cell carcinoma (RCC) who undergo surgical therapy, risk models and nomograms are valuable tools. External validation on independent datasets is crucial for evaluating accuracy and generalizability of these models. The objective of the present study was to externally validate the postoperative nomogram developed by Karakiewicz et al. for prediction of cancer-specific survival.

METHODS

A total of 1,480 consecutive patients with a median follow-up of 82 months (IQR 46-128) were included into this analysis with 268 RCC-specific deaths. Nomogram-estimated survival probabilities were compared with survival probabilities of the actual cohort, and concordance indices were calculated. Calibration plots and decision curve analyses were used for evaluating calibration and clinical net benefit of the nomogram.

RESULTS

Concordance between predictions of the nomogram and survival rates of the cohort was 0.911 after 12, 0.909 after 24 months and 0.896 after 60 months. Comparison of predicted probabilities and actual survival estimates with calibration plots showed an overestimation of tumor-specific survival based on nomogram predictions of high-risk patients, although calibration plots showed a reasonable calibration for probability ranges of interest. Decision curve analysis showed a positive net benefit of nomogram predictions for our patient cohort.

CONCLUSION

The postoperative Karakiewicz nomogram provides a good concordance in this external cohort and is reasonably calibrated. It may overestimate tumor-specific survival in high-risk patients, which should be kept in mind when counseling patients. A positive net benefit of nomogram predictions was proven.

Prognostic factors of overall survival in renal cancer patients - single oncological center study

INTRODUCTION

The clinical course of renal cancer remains difficult to predict. Attempts to appoint new independent prognostic factors (IPFs) and comparisons of already identified ones among populations are inevitable to develop more effective prognostic instruments. The aim of this study was to evaluate IPFs of overall survival in a given population of patients with renal cancer.

MATERIALS AND METHODS

Retrospective analysis of 148 patients with renal cancer treated at the Oncological Institute in Cracow from 2000 to 2007 was performed. Mean follow-up was 51 months. Using the log-rang test, a group of clinicopathological and biochemical features was analyzed in respect to their influence on overall survival. Results were presented as Kaplan-Meier curves. Final identification of IPFs was made by multivariate Cox regression analysis.

RESULTS

Overall survival rate at 1, 2, and 5-year follow-up was 58.8%, 38.2%, and 21.4%, respectively. The set of identified IPFs consisted of performance status, smoking history, hemoglobin concentration, anatomical staging, tumor grade, and the presence of microvascular invasion. It was confirmed that only nephrectomy increases significantly overall survival.

CONCLUSIONS

Apart from smoking history, the role of all other IPFs identified in our study is well documented in the literature. Smoking history seems to be a new IPF with strong negative impact on survival in patients with RCC.

External validation of a pre-operative prognostic nomogram for renal cell carcinoma in two patient populations: a retrospective cohort study

The aim of this study was to establish the discriminating accuracy of Kanao's pre-operative nomogram for renal cell carcinoma in predicting cause-specific survival among representative patients who underwent nephrectomy. Patients originated from two centers: Chiba University Hospital (n= 151) and Chiba Cancer Center (n = 91). We validated the predictive accuracy, which was assessed using Harrell's concordance-index. The concordance-index values were 0.692 and 0.834 for Chiba University Hospital and Chiba Cancer Center, respectively, although it was 0.822 for the combined data sets. Results of external validation were different at each cohort. We constructed calibration plots of Kanao's nomogram and confirmed the tendency at each institution. Inconsistency of results among two centers makes it difficult to reach a valid conclusion. Therefore, the predictive accuracy of Kanao's nomogram was not settled. Clinicians need to confirm the predictive accuracy of Kanao's nomogram and construct calibration plots when applying this nomogram to different patient populations.

Prognostic models for renal cell carcinoma recurrence: external validation in a Japanese population

The aim of the present study was to compare the accuracy of three prognostic models in predicting recurrence-free survival among Japanese patients who underwent nephrectomy for non-metastatic renal cell carcinoma (RCC). Patients originated from two centers: Chiba University Hospital (n = 152) and Chiba Cancer Center (n = 65). The following data were collected: age, sex, clinical presentation, Eastern Cooperative Oncology Group performance status, surgical technique, 1997 tumor-node-metastasis stage, clinical and pathological tumor size, histological subtype, disease recurrence, and progression. Three western models, including Yaycioglu's model, Cindolo's model and Kattan's nomogram, were used to predict recurrence-free survival. Predictive accuracy of these models were validated by using Harrell's concordance-index. Concordance-indexes were 0.795 and 0.745 for Kattan's nomogram, 0.700 and 0.634 for Yaycioglu's model, and 0.700 and 0.634 for Cindolo's model, respectively. Furthermore, the constructed calibration plots of Kattan's nomogram overestimated the predicted probability of recurrence-free survival after 5 years compared with the actual probability. Our findings suggest that despite working better than other predictive tools, Kattan's nomogram needs be used with caution when applied to Japanese patients who have undergone nephrectomy for non-metastatic RCC.

The Karakiewicz nomogram is the most useful clinical predictor for survival outcomes in patients with localized renal cell carcinoma

BACKGROUND

Outcomes after surgical removal of localized renal cell carcinoma (RCC) are variable. There have been multiple prognostic nomograms and risk groups developed for estimation of survival outcomes, with different models in use for evaluating patient eligibility in ongoing trials of adjuvant therapy. The authors aimed to establish the most useful prognostic model for patients with localized RCC to guide trial design, biomarker research, and clinical counseling.

METHODS

A total of 390 consecutive patients who underwent nephrectomy for sporadic localized RCC in a tertiary institution (1990-2006) with 65 months median follow-up were retrospectively evaluated. The Karakiewicz nomogram, the Kattan nomogram, the Sorbellini nomogram, and the Leibovich model were compared in predicting survival outcomes (overall survival, cancer-specific survival, and freedom from recurrence) using likelihood analysis, adequacy indices, decision curve analysis, calibration, and concordance indices.

RESULTS

Overall, the Karakiewicz nomogram outperformed the Kattan nomogram, the Sorbellini nomogram, and the Leibovich model. Highly improved accuracy was seen using the Karakiewicz nomogram in survival prediction, using likelihood ratio analysis in bivariate models including the competing prognostic models. The Karakiewicz nomogram showed higher adequacy and concordance indices and improved clinical benefit relative to all other nomograms. All 4 models were reasonably calibrated. Exploratory comparisons of prespecified discretized Karakiewicz nomograms and the SORCE trial recruitment criteria (a discretized Leibovich model) of high-risk patients favored the discretized Karakiewicz nomograms.

CONCLUSIONS

The Karakiewicz nomogram was shown to be superior to the other tested nomograms and risk groups in predicting survival outcomes in localized RCC. Routine integration of this model into trial design and biomarker research should be considered.

Factors affecting outcome in renal cell carcinoma

PURPOSE OF REVIEW

To review the latest status on prognostic factors in renal cell carcinoma (RCC).

RECENT FINDINGS

Many predictive and prognostic factors can help differentiate between favorable and unfavorable RCC phenotypes. There currently exist several clinical and/or pathological, and biological factors, which have been exclusively tested and used in predictive and prognostic models. Nonetheless, the search for highly informative and reliable factors of disease characteristics and progression continues.

CONCLUSION

Over the last decade, an increase occurred in the number of models that can predict the treated natural history of RCC. Many of these novel models and previously developed models are tested in a head-to-head fashion, with the intent of identifying the most accurate and valuable tools for clinical practice. Novel prognostic factors and more up-to-date models are urgently needed for patients with metastatic RCC, especially in the era of targeted therapies. This should represent the focus of contemporary prognostic modeling in RCC.

Urinary collecting system invasion is no independent prognostic factor in renal cell carcinoma

OBJECTIVES

To assess the specific impact of urinary collecting system (UCS) invasion on the long-term prognosis of patients with renal cell carcinoma (RCC).

METHODS

We evaluated 1,678 patients with complete information about UCS invasion of their primary RCC who had undergone renal surgery between 1990 and 2005 in two high volume centers (MH Hannover and Marburg, Germany); the mean follow-up was 5.4 years.

RESULTS

Hundred and forty-nine (8.9%) patients demonstrated collecting system invasion. These patients incurred a significant increase in the likelihood of cancer-related death (HR 1.7, 95% CI: 1.4-2.0; P < 0.001), their median 5-year tumor-specific survival rate was 45% as opposed to 73% for patients without UCS invasion (P < 0.001). UCS invasion was significantly associated with tumor stage, grade, lymph node, and visceral metastasis at diagnosis but not with age, gender, histologic subtype, or body mass index. However, using multivariate analysis, UCS invasion disqualified as individual prognostic factor for RCC, neither for localized nor for advanced disease.

CONCLUSION

Facing the results of this large trial, we do not support the inclusion of UCS invasion into upcoming TNM staging systems. In contrast, future research should focus on novel molecular markers expressed by the tumor and/or specific immunological characteristics of patients with RCC which could improve prediction of RCC-associated prognosis.