Validation by calibration of the UCLA integrated staging system prognostic model for nonmetastatic renal cell carcinoma after nephrectomy

Risk models for recurrence and survival after kidney cancer: a systematic review

OBJECTIVE

To systematically identify and compare the performance of prognostic models providing estimates of survival or recurrence of localized renal cell cancer (RCC) in patients treated with surgery with curative intent.

MATERIALS AND METHODS

We performed a systematic review (PROSPERO CRD42019162349). We searched Medline, EMBASE and the Cochrane Library from 1 January 2000 to 12 December 2019 to identify studies reporting the performance of one or more prognostic model(s) that predict recurrence-free survival (RFS), cancer-specific survival (CSS) or overall survival (OS) in patients who have undergone surgical resection for localized RCC. For each outcome we summarized the discrimination of each model using the C-statistic and performed multivariate random-effects meta-analysis of the logit transformed C-statistic to rank the models.

RESULTS

Of a total of 13 549 articles, 57 included data on the performance of 22 models in external populations. C-statistics ranged from 0.59 to 0.90. Several risk models were assessed in two or more external populations and had similarly high discriminative performance. For RFS, these were the Sorbellini, Karakiewicz, Leibovich and Kattan models, with the UCLA Integrated Staging System model also having similar performance in European/US populations. All had C-statistics ≥0.75 in at least half of the validations. For CSS, they the models with the highest discriminative performance in two or more external validation studies were the Zisman, Stage, Size, Grade and Necrosis (SSIGN), Karakiewicz, Leibovich and Sorbellini models (C-statistic ≥0.80 in at least half of the validations), and for OS they were the Leibovich, Karakiewicz, Sorbellini and SSIGN models. For all outcomes, the models based on clinical features at presentation alone (Cindolo and Yaycioglu) had consistently lower discrimination. Estimates of model calibration were only infrequently included but most underestimated survival.

CONCLUSION

Several models had good discriminative ability, with there being no single 'best' model. The choice from these models for each setting should be informed by both the comparative performance and availability of factors included in the models. All would need recalibration if used to provide absolute survival estimates.

Radiotherapy and Renal Cell Carcinoma: A Continuing Saga

Renal cell carcinoma (RCC) is one of the most aggressive malignancies of the genito-urinary tract, having a poor prognosis especially in patients with metastasis. Surgical resection remains the gold standard for localized renal cancer disease, with radiotherapy (RT) receiving much skepticism during the last decades. However, many studies have evaluated the role of RT, and although renal cancer is traditionally considered radio-resistant, technological advances in the RT field with regards to modern linear accelerators, as well as advanced RT techniques have resulted in breakthrough therapeutic outcomes. Additionally, the combination of RT with immune checkpoint inhibitors and targeted agents may maximize the clinical benefit. This review article focuses on the role of RT in the therapeutic management of renal cell carcinoma.

[Impact of molecular signatures on the choice of systemic treatment for metastatic kidney cancer]

The standard of care for metastatic clear cell renal cell carcinoma (mccRCC) has changed dramatically over the past decades thanks to the increasing number of treatments: anti-VEGFR tyrosine kinase inhibitors (TKI), mTOR inhibitors and immune checkpoint inhibitors (ICI): anti PD(L)-1 used as monotherapy or in combination with anti CTLA-4 or anti angiogenic therapies. In the face of rising therapeutic options, the question of the therapeutic sequences arises: which treatment for which patient? Actually, there is a lack of predictive biomarkers. A greater understanding of the cancer biology and its interaction with the microenvironment has allowed the development of genomic signatures which could perhaps be used as predictive biomarker. This review will give an insight on some robust genomic signatures assessed in mccRCC and will have a closer look at BIONIKK phase II trial, which is the first trial to adapt treatments according to the molecular characteristics of the tumor in the context of mccRCC.

Development and Validation of a Nomogram Predicting the Prognosis of Renal Cell Carcinoma After Nephrectomy

Objective

To develop and validate a nomogram for predicting the overall survival (OS) of renal cell carcinoma (RCC) patients after nephrectomy.

Materials and Methods

In total, 488 patients with RCC who underwent nephrectomy at the Urology Department of the First Hospital of Shanxi Medical University between January 2013 and December 2018 were randomly divided into a development cohort (n = 344) and a validation cohort (n = 144). The development cohort was used to build a prediction model, and the validation cohort was used for validation. Single-factor and multifactor analyses were carried out with R software, and the nomogram, calibration chart, ROC curve and C index were constructed.

Results

The median follow-up time of the development and validation cohorts was 34 months. The total 3-year and 5-year survival rates of the development cohort were 93.3% and 91.6%, respectively; those of the validation cohort were 92.4% and 91.0%, respectively. Cox univariate analysis of the development cohort showed that age, type 2 diabetes mellitus (T2DM), smoking history, type of surgery, T stage, N stage, M stage and Fuhrman nuclear grade were prognostic factors for OS in RCC patients undergoing nephrectomy. Cox multivariate analysis showed that T2DM, smoking history and T stage were independent prognostic factors for OS in RCC patients undergoing nephrectomy (P < 0.05). According to the univariate and multivariate analyses, a nomogram was constructed. In the development cohort, the C index of predicted OS was 0.875 (95% CI, 0.820-0.930). The calibration curve of the 3-year and 5-year survival rates showed that the predicted value of the nomogram was consistent with the actual observed value. The area under the 3-year and 5-year survival ROC curves was 0.861 and 0.901, respectively. In the validation cohort, the C index was 0.880 (95% CI, 0.778-0.982). The calibration curve of the 3-year and 5-year survival rates showed that the predicted value of the nomogram was consistent with the actual observed value. The area under the 3-year and 5-year survival ROC curves was 0.813 and 0.799, respectively.

Conclusion

We developed and verified a new and accurate nomogram with available clinicopathological data that can effectively predict the OS of RCC patients after nephrectomy.

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.

[Follow-up of renal cell carcinoma in a nonmetastatic stage]

Postoperative follow-up care after curative surgery or ablative treatment is the standard of care in patients with nonmetastatic renal cell carcinoma. The goal is to identify and treat postoperative complications and local recurrences early on. Follow-up investigations and their relevance are widely acknowledged and validated and patients undergoing follow-up seem to benefit from a longer survival in nonmetastatic renal cell carcinoma. Hence there is no consensus on a standardized follow-up strategy. The most disputed question is around the frequency of the investigations and the duration of the follow-up. Without an evidence-based follow-up protocol, urologists should carry out an individualized, potentially lifelong follow-up regimen, which also includes the patients' needs and perspectives.

RETRACTED: Recommandations françaises du Comité de Cancérologie de l’AFU – Actualisation 2018–2020 : prise en charge du cancer du reinFrench ccAFU guidelines – Update 2018–2020: Management of kidney cancer

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). Cet article est retiré de la publication à la demande des auteurs car ils ont apporté des modifications significatives sur des points scientifiques après la publication de la première version des recommandations. Le nouvel article est disponible à cette adresse: DOI:10.1016/j.purol.2019.01.004. C’est cette nouvelle version qui doit être utilisée pour citer l’article. This article has been retracted at the request of the authors, as it is not based on the definitive version of the text because some scientific data has been corrected since the first issue was published. The replacement has been published at the DOI:10.1016/j.purol.2019.01.004. That newer version of the text should be used when citing the article.

Is there a role for adjuvant therapy after surgery in "high risk for recurrence" kidney cancer? An update on current concepts

Background

Although surgical resection remains the standard of care for localized kidney cancers, a significant proportion of patients experience systemic recurrence after surgery and hence might benefit from effective adjuvant therapy. So far, several treatment options have been evaluated in adjuvant clinical trials, but only a few have provided promising results. Nevertheless, with the recent development of targeted therapy and immunomodulatory therapy, a series of clinical trials are in progress to evaluate the potential of those novel agents in the adjuvant setting. In this paper, we provide a narrative review of the progress in this field, and we summarize the results from recent adjuvant trials that have been completed.

Methods

A literature search was conducted. The primary search strategy at the medline, Cochrane reviews, and http://ClinicalTrials.gov/databases included the keywords "adjuvant therapy," "renal cell carcinoma," and "targeted therapy or/and immunotherapy."

Conclusions

Data from the s-trac study indicated that, in the "highest risk for recurrence" patient population, disease-free survival was increased with the use of adjuvant sunitinib compared with placebo. The assure trial showed no benefit for adjuvant sunitinib or sorafenib in the "intermediate- to high-risk" patient population. The ariser (adjuvant girentuximab) and protect (adjuvant pazopanib) trials indicated no survival benefit, but subgroup analyses in both trials recommended further investigation. The inconsistency in some of the current results can be attributed to a variety of factors pertaining to the lack of standardization across the trials. Nevertheless, patients in the "high risk of recurrence" category after surgery for their disease would benefit from a discussion about the potential benefits of adjuvant treatment and enrolment in ongoing adjuvant trials.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.

Contemporary external validation of the Leibovich model for prediction of progression after radical surgery for clear cell renal cell carcinoma

OBJECTIVE

The aim of this study was to externally validate in an up-to-date setting the predictive ability of the model for recurrence after radical treatment of clear cell renal cell carcinoma (CCRCC) published by Leibovich in 2003.

MATERIALS AND METHODS

The study included a total of 386 consecutive patients with CCRCC between January 1997 and May 2013, treated with partial or radical nephrectomy. All patients were scored with points between 0 and 11, and further subdivided into low-, intermediate- and high-risk groups according to the original paper. Well-recognized statistical methods for the evaluation of Cox's proportional hazard-based prognostic models were applied. To validate the discriminative ability, Harrell's concordance (c) index and hazard ratios (HRs) between risk groups were used, and calibration was graphically explored.

RESULTS

The 10 year recurrence-free survival rates for the low-, intermediate- and high-risk groups were 87.3%, 63.8% and 19.8%, respectively Harrell's c index was 0.864. The HRs across risk groups for the intermediate- and high-risk groups were 5.29 and 21.56, respectively, with the low-risk group as a reference category. A gross comparison of the survival estimates between the patients showed an overall similarity. However, differences within the intermediate- and high-risk groups were seen in the first year of follow-up.

CONCLUSIONS

The Leibovich model seems to discriminate well between risk groups, but for the intermediate- and high-risk groups the calibration is not optimal. This study validates the model in a present-day Nordic patient population. The model can be used as a risk stratification tool for follow-up after radical treatment of CCRCC.

Adjuvant therapy for renal cell carcinoma: past, present, and future

At the present time, the standard of care for patients who have received nephrectomy for localized renal cell carcinoma (RCC) is radiographic surveillance. With a number of novel targeted agents showing activity in the setting of metastatic RCC, there has been great interest in exploring the potential of the same agents in the adjuvant setting. Herein, we discuss the evolution of adjuvant trials in RCC, spanning from the immunotherapy era to the targeted therapy era. Pitfalls of current studies are addressed to provide a context for interpreting forthcoming results. Finally, we outline avenues to incorporate promising investigational agents, such as PD-1 (programmed death-1) inhibitors and MNNG transforming gene inhibitors, in future adjuvant trials.

Role of radiation therapy for renal tumors

Renal cell carcinoma (RCC) is an aggressive malignancy that carries a poor prognosis, especially in patients presenting with advanced stage. Primary treatment for localized RCC is surgical resection however, a significant number of patients still develop locoregional and distant metastasis after curative resection. In metastatic disease, radiation therapy (RT) has been used for palliation routinely for brain and other extracranial lesions with respectable response rates. However, RT for primary RCC has questionable benefit. In this article, the authors discuss the evidence with regards to the role of RT in primary RCC either as a primary treatment, adjuvant treatment, or preoperatively to improve resection outcomes. In addition, novel RT techniques such as stereotactic body radiation therapy and its use in RCC management are also addressed. Finally, the authors discuss the techniques and doses of RT for primary RCC.

Aquaporin-1 protein levels elevated in fresh urine of renal cell carcinoma patients: potential use for screening and classification of incidental renal lesions

INTRODUCTION AND OBJECTIVES

There are over 65,000 new cases of renal cell carcinoma (RCC) each year, yet there is no effective clinical screening test for RCC. A single report claimed no overlap between urine levels of aquaporin-1 (AQP1) in patients with and without RCC (Mayo Clin Proc. 85:413, 2010). Here, we used archived and fresh RCC patient urine to validate this report.

METHODS

Archived RCC, fresh prenephrectomy RCC, and non-RCC negative control urines were processed for Western blot analysis. Urinary creatinine concentrations were quantified by the Jaffe reaction (Nephron 16:31, 1976). Precipitated protein was dissolved in 1x SDS for a final concentration of 2  μg/µL creatinine.

RESULTS

Negative control and archived RCC patient urine failed to show any AQP1 protein by Western blot analysis. Fresh RCC patient urine is robustly positive for AQP1. There was no signal overlap between fresh RCC and negative control, making differentiation straightforward.

CONCLUSIONS

Our data confirms that fresh urine of patients with RCC contains easily detectable AQP1 protein. However, archival specimens showed an absence of detectable AQP1 indistinguishable from negative control. These findings suggest that a clinically applicable diagnostic test for AQP1 in fresh urine may be useful for detecting RCC.

Assessing the accuracy and generalizability of the preoperative and postoperative Karakiewicz nomograms for renal cell carcinoma: results from a multicentre European and US study

OBJECTIVE

To assess the accuracy and generalizability of the pre- and postoperative Karakiewicz nomograms for predicting cancer-specific survival (CSS) in patients with renal cell carcinoma (RCC).

PATIENTS AND METHODS

This retrospective study included 3231 patients from European and US centres, who were treated by radical or partial nephrectomy for RCC between 1992 and 2010. Prognostic scores for each patient were calculated and the primary endpoint was CSS. Discriminating ability was assessed by Harrell's c-index for censored data. The 'validation by calibration' method proposed by Van Houwelingen was used for checking the calibration of covariate effects. Calibration was graphically explored.

RESULTS

Local and systemic symptoms were present in 23.2% and 9.1% of the patients, respectively. The median follow-up (FU) was 49 months. At the last FU, 408 cancer-related deaths were recorded, Kaplan-Meier estimates of CSS (with 95% confidence intervals [CIs]) at 5 and 10 years were 0.86 (0.84-0.87) and 0.77 (0.75-0.80), respectively. Both nomograms discriminated well. Stratified c-indices for CSS were 0.784 (95% CI 0.753-0.814) for the preoperative nomogram, and 0.842 (95% CI 0.816-0.867) for the postoperative one, with a significant difference between the two values (P < 0.001). The covariate-based predictions on our data for both nomograms were valid. The calibration plots showed no relevant departures from ideal predictions.

CONCLUSIONS

The results suggest that the postoperative Karakiewicz nomogram discriminates substantially better than the preoperative one. These nomogram-based predictions may be used as benchmark data for pretreatment and postoperative decision-making in patients at various stages of RCC.

Serum amino acid levels as a biomarker for renal cell carcinoma

PURPOSE

Prognosis in renal cell carcinoma is dependent on tumor stage at presentation, with significant differences in survival between early and late stage disease. Currently to our knowledge no screening tests or biomarkers have been identified for the early detection of kidney cancer. Therefore, we investigated whether serum amino acid profiles are a potentially useful biomarker in patients with renal cell carcinoma.

MATERIALS AND METHODS

The concentrations of 26 amino acids were determined in serum taken preoperatively from 189 patients with renal cell carcinoma, and from 104 age and sex matched controls.

RESULTS

Statistically significant changes were observed in patient levels of 15 amino acids, with 13 being decreased and 2 being increased. A logistic regression model using 8 amino acids including cysteine, ornithine, histidine, leucine, tyrosine, proline, valine and lysine was created to distinguish cases from controls. A receiver operator curve based on this model had an area under the curve of 0.81. This same model also had predictive value in terms of overall survival and tumor recurrence in patients with renal cell carcinoma.

CONCLUSIONS

Our findings suggest that serum amino acid levels may be useful as a screening tool for the identification of individuals with renal cell carcinoma and the prediction of outcomes.

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.

Breaking through a plateau in renal cell carcinoma therapeutics: development and incorporation of biomarkers

With the Food and Drug Administration approval of 6 novel targeted agents since December 2005 and limited comparative trials to discern relative efficacy, the treatment of metastatic renal cell carcinoma (RCC) has become immensely complex. The research community must look to novel ways in which to identify appropriate candidates for selected targeted therapies; one potential strategy is the use of clinical and molecular biomarkers. A growing body of knowledge-related von Hippel Lindau-driven pathways in this disease has highlighted the potential role of hypoxia-inducible factor subtypes in distinguishing RCC patients clinically. Techniques applied in other malignancies, such as gene expression and proteomic profiling, may also ultimately allow for clinical stratification. An emerging understanding of immunologic phenomena that may affect cancer progression (i.e., tumor infiltration by CD68 lymphocytes, memory T-cells, etc.) has unveiled a number of other potential biomarkers of response. Several vascular endothelial growth factor receptor-directed therapies classically thought to function as antiangiogenics may also have complex effects upon the tumor microenvironment including the associated immune cell milieu. As such, immunologic parameters could potentially predict response to current therapies. Finally, clinical biomarkers, such as hypertension, may predict the efficacy of several currently available targeted agents, although implementation of such biomarkers remains challenging. Herein, the clinical relevance of putative RCC biomarkers is examined in detail.

[Significance of anemia as an independent prognostic factor in patients with renal cell carcinoma]

BACKGROUND AND OBJECTIVE

The aim of this study was to analyze the significance of anemia as well as other prognostic factors influencing survival in patients with renal cell carcinoma (RCC).

PATIENTS AND METHODS

A retrospective review of data of 316 patients who underwent surgery between 1970 and 2003 was performed. Most important known prognostic factors of RCC were investigated.

RESULTS

Most of patients had T1b-T2, low nuclear grade and single tumours. In 8.2% and 9% of cases, lymph node and metastatic dissemination were detected at the time of diagnosis, respectively. At the beginning, most frequent symptoms were hematuria and pain, with anemia (Hb >10g/dl) in 69 patients. After a median follow-up of 50 months, 24.1% of patients had a recurrence. From these, more than 50% developed recurrence within one year after nephrectomy. Advanced tumours (T3-4) consisted of high nuclear grade (III-IV) tumours, larger size tumours, with necrosis and vascular infiltration in surgical specimen, as well as lymph node and metastatic dissemination. In multivariate analysis, anemia, time to recurrence, type of treatment for recurrence as well as lymph node dissemination were independent factors of cancer specific survival.

CONCLUSION

Anemia seems to be a marker of recurrence and progression in patients with renal cell carcinoma undergoing nephrectomy. From our point of view, anemia could be considered a significantly high mortality rate for renal cancer in these patients.

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

OBJECTIVES

To explore the applicability of the current prognostic models for nonmetastatic renal cell carcinoma in the Chinese population based on a single center experience.

METHODS

Clinical and pathological variables of 653 nonmetastatic renal cell carcinoma patients were retrospectively reviewed. Seven models were used to predict the prognosis, including the Yaycioglu model, the Cindolo model, the University of California Los Angeles Integrated Staging System model, the stage, size, grade, and necrosis model, the Kattan nomogram, the Sorbellini nomogram and the Karakiewicz nomogram. Three different end-points were used for validation, including overall survival, cancer-specific survival, and recurrence-free survival. Survival was estimated using the Kaplan-Meier method. Discriminating ability was assessed using the Harrell's concordance-index.

RESULTS

At the last follow up, 159 patients had died due to various causes, and disease recurrence occurred in 156 patients. The discriminating ability of all models was confirmed in the Chinese population. Nomograms discriminate better than algorithms, regardless of end-points. The Kattan nomogram was the most accurate, with the highest concordance-indexes of 0.752, 0.793 and 0.841 for overall survival, cancer-specific survival, and recurrence-free survival, respectively.

CONCLUSIONS

The current prognostic models were developed and validated entirely based on Caucasian populations. This study defines the general applicability of the models for Chinese patients with nonmetastatic renal cell carcinoma treated with nephrectomy. The Kattan model was found to be the most accurate. The Cindolo model performed well in some situations, although only including clinical presentation and size of tumor. Therefore, models should be chosen according to different environments and purposes.