The critical impact of tumor size in predicting cancer special survival for T3aM0M0 renal cell carcinoma: A proposal of an alternative T3aN0M0 stage

[Predicting the 3-year tumor-specific survival in patients with T3a non-metastatic renal cell carcinoma]

OBJECTIVE

To predict the 3-year cancer-specific survival (CSS) of patients with non-metastatic T3a renal cell carcinoma after surgery.

METHODS

A total of 336 patients with pathologically confirmed T3a N0-1M0 renal cell carcinoma (RCC) who underwent surgical treatment at the Department of Urology, Peking University Third Hospital from March 2013 to February 2021 were retrospectively collected. The patients were randomly divided into a training cohort of 268 cases and an internal validation cohort of 68 cases at an 4 ∶ 1 ratio. Using two-way Lasso regression, variables were selected to construct a nomogram for predicting the 3-year cancer-specific survival (CSS) of the patients with T3aN0-1M0 RCC. Performance assessment of the nomogram included evaluation of discrimination and calibration ability, as well as clinical utility using measures such as the concordance index (C-index), time-dependent area under the receiver operating characteristic curve [time-dependent area under the curve (AUC)], calibration curve, and decision curve analysis (DCA). Risk stratification was determined based on the nomogram scores, and Kaplan-Meier survival analysis and Log-rank tests were employed to compare progression-free survival (PFS) and cancer-specific survival (CSS) among the patients in the different risk groups.

RESULTS

Based on the Lasso regression screening results, the nomogram was constructed with five variables: tumor maximum diameter, histological grading, sarcomatoid differentiation, T3a feature, and lymph node metastasis. The baseline data of the training and validation sets showed no statistical differences (P>0.05). The consistency indices of the column diagram were found to be 0.808 (0.708- 0.907) and 0.903 (0.838-0.969) for the training and internal validation sets, respectively. The AUC values for 3-year cancer-specific survival were 0.843 (0.725-0.961) and 0.923 (0.844-1.002) for the two sets. Calibration curves of both sets demonstrated a high level of consistency between the actual CSS and predicted probability. The decision curve analysis (DCA) curves indicated that the column diagram had a favorable net benefit in clinical practice. A total of 336 patients were included in the study, with 35 cancer-specific deaths and 69 postoperative recurrences. According to the line chart, the patients were divided into low-risk group (scoring 0-117) and high-risk group (scoring 119-284). Within the low-risk group, there were 16 tumor-specific deaths out of 282 cases and 36 postoperative recurrences out of 282 cases. In the high-risk group, there were 19 tumor-specific deaths out of 54 cases and 33 post-operative recurrences out of 54 cases. There were significant differences in progression-free survival (PFS) and cancer-specific survival (CSS) between the low-risk and high-risk groups (P < 0.000 1).

CONCLUSION

A nomogram model predicting the 3-year CSS of non-metastatic T3a renal cell carcinoma patients was successfully constructed and validated in this study. This nomogram can assist clinicians in accurately assessing the long-term prognosis of such patients.

Oncologic Outcomes and Predictors in Patients with Stage PT3aNxM0 Renal Cell Carcinoma Following Radical Nephrectomy

OBJECTIVE

The objective of this study is to evaluate oncologic outcomes in patients with PT3aNxM0 renal cell carcinoma following radical nephrectomy and also to investigate these outcomes in each specific subgroup of PT3a renal cell carcinoma and to determine predictive factors of recurrence, metastasis, and mortality.

MATERIALS AND METHODS

In this retrospective cohort study, we included 94 patients with stage PT3a renal cell carcinoma who had undergone radical nephrectomy from 2011 to 2016. All patients who had survived had at least 60 months of follow-up. Demographic and clinical data were collected; univariable and multivariable Cox proportional hazards regression analysis was performed to identify predictors of metastasis, recurrence, and cancer-related mortality.

RESULTS

Patients' mean age was 58.07 ± 11.17 years and 62/94 (65.9%) were male. The mean follow-up time was 48.1 ± 25.5 months. Forty-three patients (45.7%) had experienced cancer-related mortality. The mean cancer-specific survival time was 60.94 months and the mean metastasis-free and local recurrence-free survival times were 57.06 and 88.72 months, respectively. Metastasis and local recurrence had occurred in 42 (44.6%) and 4 (4.25%) patients, respectively. After performing multivariate analysis, higher nuclear Fuhrman's grade (P < .001) and simultaneous involvement of the renal vein and perinephric fat (P < .001) were found to be predictive of cancerrelated mortality. Advanced nuclear Fuhrman's grade was the only independent predictor of metastasis (P=.001).

CONCLUSION

Based on our results, advanced nuclear Fuhrman's grade and sarcomatoid change can independently predict mortality in patients with stage PT3aNxM0 renal cell carcinoma. Close monitoring during the follow-up period is recommended in patients with the mentioned risk factors.

Association of Extrarenal Invasion Patterns and Tumor Size with the Differences in Survival Outcomes of T3a Renal Cell Carcinoma: A Proposal Modified T3a Stage System is Needed

Objective

T3a renal cell carcinoma (RCC) did not consider tumor size and different extrarenal invasion patterns in the current TNM staging system. Here, we want to investigate the association of survival outcomes with different extrarenal invasion patterns and tumor size of T3a RCC.

Methods

We identified T3a RCC patients from the Surveillance, Epidemiology, and End Results database in 2004–2015. The extrarenal invasion patterns included renal vein invasion, renal sinus/peri-sinus fat invasion, or perinephric fat invasion. Cox proportional hazards models and Fine and Gray models were used to estimate overall survival (OS) and cancer-specific survival (CSS), and the hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. C-index is used to evaluate the predictive ability of the model. Restricted cubic splines were used to estimate the HRs of tumor size on the risk of OS and CSS.

Results

In total, 4834 T3a RCC patients were included in the analysis. Of them, 1403 (29%) present isolated extrarenal invasion pattern, while 1403 (71%) were any combined invasion pattern, which was associated with a higher risk of lymph-node/distant metastasis and a worse OS and CSS compared with isolated extrarenal invasion pattern, but a comparable CSS and OS were observed between each isolated invasion pattern. In restricted cubic splines, a non-linear shape was observed for the association between the tumor size and OS and CSS, compared with the smallest tumor size group (≤4cm), the adjusted HR of the largest tumor size group (≥10cm) was 1.59 for all-cause mortality, and 2.27 for tumor-specific mortality, respectively. However, in a cohort of T3a RCC with a combined invasion pattern, tumor size is not an independent risk factor for prognosis. Finally, the model added two covariates of tumor size and invasion patterns that could improve the predictive ability of OS and CSS for T3a patients (c-index: +1.2%, +1.3%, respectively).

Conclusion

Tumor size and extrarenal invasion type are valid parameters of the OS and CSS for T3a RCC patients and need to be considered for the next generation of the T-stage system.

Comparison of prognosis between patients undergoing radical nephrectomy versus partial nephrectomy for renal cell carcinoma ≤7 cm T3aN0/xM0: Survival benefit is biased toward partial nephrectomy

BACKGROUND

There is limited and controversial evidence on the prognosis of partial nephrectomy (PN) versus radical nephrectomy (RN) in patients with T3aN0/xM0 renal cell carcinoma (RCC) upstaged from clinical T1 RCC. In this study, we aimed to assess the prognosis difference following PN versus RN in patients with ≤7 cm T3aN0/xM0 RCC.

METHODS

From the Surveillance, Epidemiology, and End Results database, a total of 3196 patients receiving treatment of PN/RN for ≤7 cm T3aN0/xM0 RCC with only extrarenal fat extension in 2010-2017 were identified. An inverse probability of treatment weighting (IPTW)-adjusted cause-specific Cox model with hazard ratio (HR) and 95% confidence interval (CI) was used for overall survival (OS) and cancer-specific survival (CSS) analyses. Sensitivity analysis was based on the propensity score matching of PN and RN groups and from the dataset of 2010-2013.

RESULTS

A total of 872 patients underwent PN, compared with 2324 undergoing RN. After IPTW adjustment, there was no significant difference in preoperative baseline characteristics between the PN and RN cohorts. Patients who underwent RN had worse OS (HR_{IPTW-adjusted} , 1.46; 95% CI, 1.16-1.84; p = 0.001) and comparable CSS (HR_{IPTW-adjusted} , 1.03; 95% CI, 0.64-1.66; p = 0.890) than those receiving PN in all cohorts and subgroups with T3a RCC of ≤4 cm and perinephric fat extension. Further, in patients with 4-7 cm T3a RCC with perinephric-fat invasion and all sizes of T3a RCC with sinus/perisinus fat extension, PN led to comparable OS and CSS. Sensitivity analyses validated these results.

CONCLUSION

PN provides comparable CSS and OS or even better OS than RN for patients with RCC ≤7 cm T3aN0/xM0. Although our study has some limitations, our results indicated that PN might oncologically safe for clinical T1 RCC, even confirmed a pathologically T3a upstaging post-PN.

Clinical significance of novel DNA methylation biomarkers for renal clear cell carcinoma

OBJECTIVE

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor characterized by the highest mortality rate of the genitourinary cancers, and, therefore, new diagnostic and/or prognostic biomarkers are urgently needed.

METHODS

Based on genome-wide DNA methylation profiling in 11 pairs of ccRCC and non-cancerous renal tissues (NRT), the methylation at regulatory regions of ZNF677, FBN2, PCDH8, TFAP2B, TAC1, and FLRT2 was analyzed in 168 renal tissues and 307 urine samples using qualitative and quantitative methylation-specific PCR (MSP).

RESULTS

Significantly higher methylation frequencies for all genes were found in ccRCC tissues compared to NRT (33-60% vs. 0-11%). The best diagnostic performance demonstrated a panel of ZNF677, FBN2, PCDH8, TFAP2B & TAC1 with 82% sensitivity and 96% specificity. Hypermethylation of ZNF677 and PCDH8 in the tissue samples was significantly related to numerous adverse clinicopathologic parameters. For the urine-based ccRCC detection, the highest diagnostic power (AUC = 0.78) was observed for a panel of ZNF677 & PCDH8 (with or without FBN2 or FLRT2) with 69-78% sensitivity and 69-80% specificity, albeit with lower values in the validation cohort. Besides, methylation of PCDH8 was significantly related to higher tumor stage and fat invasion in the study and validation cohorts. Moreover, PCDH8 was strongly predictive for OS (HR, 5.7; 95% CI 1.16-28.12), and its prognostic power considerably increased in combination with ZNF677 (HR, 12.5; 95% CI 1.47-105.58).

CONCLUSION

In summary, our study revealed novel, potentially promising DNA methylation biomarkers of ccRCC with the possibility to be applied for non-invasive urine-based ccRCC detection and follow-up.

Development and validation of a nomogram to predict postoperative cancer-specific survival of patients with nonmetastatic T3a renal cell carcinoma

PURPOSE

To establish a nomogram for the prediction of postoperative cancer-specific survival (CSS) in patients with nonmetastatic T3a renal cell carcinoma (RCC).

METHODS

The Surveillance, Epidemiology, and End Results database were searched for patients with pT3aN0-1M0 RCC between 2010 and 2018. The patients were randomly stratified into the training and verification group (7:3 ratio). Using Cox regression analysis, the predictors for the CSS in the training group were integrated to establish the nomogram for predicting the 3-year and 5-year CSS. Harrell's concordance index (C-index), time-dependent receiver operating characteristic curve, decision curve analysis, and Kaplan-Meier survival analysis were used to evaluate the nomogram performance.

RESULTS

A total of 5,791 pT3aN0-1M0 RCC cases with eligible data were selected from the Surveillance, Epidemiology, and End Results database. Age, tumor size, surgery type, Fuhrman grade, histological type, sarcomatoid, N stage, and invasion patterns were identified as the significant predictors for CSS to establish the nomogram. The C-indices of the nomogram were 0.774 (95% CI: 0.753-0.795) and 0.777 (95% CI: 0.745-0.809) for the training and verification group, respectively. The calibration of the nomogram revealed consistency between the predicted and observed survival. The area under the 3-year and 5-year CSS receiver operating characteristic curves were 0.773 and 0.786 in the training group, respectively. Decision curve analysis showed the optimal application of the model in clinical decision-making. According to the cutoff values of prognostic indices, patients with low-risk showed better CSS than those with high-risk in both training and verification groups (both P< 0.0001).

CONCLUSION

The current nomogram could effectively predict the CSS of patients with nonmetastatic T3a RCC, and could be used to identify patients who might need a compact interval of follow-up and postoperative adjuvant systemic treatment. The limitations included the retrospective nature, absence of external validation, and several unmeasured variables related to the selection bias of surgery type. The results should be interpreted with caution.