Comparison of different prediction tools for the risk of intravesical recurrence after radical nephroureterectomy for upper tract urothelial carcinoma: a propensity-matched analysis

Objective To compare the predictive performance of the current clinical prediction models for predicting intravesical recurrence (IVR) after radical nephroureterectomy (RNU) in patients with upper tract urothelial carcinoma (UTUC). Methods We retrospectively analysed upper tract urothelial carcinoma patients who underwent radical nephroureterectomy in our centre from January 2009 to December 2019. We used the propensity score matching (PSM) method to adjust the confounders between the IVR and non-IVR groups. Additionally, Xylinas’ reduce model and full model, Zhang’s model, and Ishioka’s risk stratification model were used to retrospectively calculate predictions for each patient. Receiver operating characteristic (ROC) curves were generated, and the areas under the curves (AUCs) were compared to identify the method with the highest predictive value. Zesults We included 217 patients with a median follow-up of 41 months, of which 57 had IVR. After PSM analysis, 52 pairs of well-matched patients were included in the comparative study. No significant difference was found in clinical indicators besides hydronephrosis. The model comparison showed that the AUCs of the reduced Xylinas’ model for 12 months, 24 months, and 36 months were 0.69, 0.73, and 0.74, respectively, and those of the full Xylinas’ model were 0.72, 0.75, and 0.74, respectively. The AUC of Zhang’s model for 12 months, 24 months, and 36 months was 0.63, 0.71, and 0.71, respectively, the performance of Ishioka’s model is that the AUC of 12 months, 24 months and 36 months was 0.66, 0.71, and 0.74, respectively. Conclusion The external verification results of the four models show that more comprehensive data and a larger sample size of patients are needed to strengthen the models’ derivation and updating procedure, to better apply them to different populations (AU)

Comparison of different prediction tools for the risk of intravesical recurrence after radical nephroureterectomy for upper tract urothelial carcinoma: a propensity-matched analysis.

OBJECTIVE: To compare the predictive performance of the current clinical prediction models for predicting intravesical recurrence (IVR) after radical nephroureterectomy (RNU) in patients with upper tract urothelial carcinoma (UTUC). METHODS: We retrospectively analysed upper tract urothelial carcinoma patients who underwent radical nephroureterectomy in our centre from January 2009 to December 2019. We used the propensity score matching (PSM) method to adjust the confounders between the IVR and non-IVR groups. Additionally, Xylinas' reduce model and full model, Zhang's model, and Ishioka's risk stratification model were used to retrospectively calculate predictions for each patient. Receiver operating characteristic (ROC) curves were generated, and the areas under the curves (AUCs) were compared to identify the method with the highest predictive value. RESULTS: We included 217 patients with a median follow-up of 41 months, of which 57 had IVR. After PSM analysis, 52 pairs of well-matched patients were included in the comparative study. No significant difference was found in clinical indicators besides hydronephrosis. The model comparison showed that the AUCs of the reduced Xylinas' model for 12 months, 24 months, and 36 months were 0.69, 0.73, and 0.74, respectively, and those of the full Xylinas' model were 0.72, 0.75, and 0.74, respectively. The AUC of Zhang's model for 12 months, 24 months, and 36 months was 0.63, 0.71, and 0.71, respectively, the performance of Ishioka's model is that the AUC of 12 months, 24 months and 36 months was 0.66, 0.71, and 0.74, respectively. CONCLUSION: The external verification results of the four models show that more comprehensive data and a larger sample size of patients are needed to strengthen the models' derivation and updating procedure, to better apply them to different populations.

Prognostic value of the systemic immune-inflammation index in patients with upper tract urothelial carcinoma after radical nephroureterectomy.

BACKGROUND: To investigate the prognostic significance of the systemic immune-inflammation index (SII) for patients with upper tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU) and develop nomogram models for predicting overall survival (OS), intravesical recurrence (IVR), and extra-urothelial recurrence (EUR). METHODS: We retrospectively studied the clinical and pathological features of 195 patients who underwent RNU for UTUC. All patients were randomly divided into a training cohort (99 cases) and a validation cohort (96 cases). The training cohort was used to develop nomogram models, and the models were validated by the validation cohort. The least absolute shrinkage and selection operator (LASSO) regression and Cox regression were performed to identify independent predictors. The concordance index (C-index), receiver operator characteristics (ROC) analysis, and calibration plot were used to evaluate the reliability of the models. The clinical utility compared with the pathological T stage was assessed using the net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). RESULTS: SII was an independent risk factor in predicting OS and EUR. The C-index values of the nomogram predicting OS, IVR, and EUR were 0.675, 0.702, and 0.756 in the training cohort and 0.715, 0.756, and 0.713 in the validation cohort. A high level of SII was correlated with the invasion of the mucosa, muscle layer of the ureter, nerves, vessels, and fat tissues. CONCLUSION: We developed nomogram models to predict the OS, IVR, and EUR of UTUC patients. The efficacy of these models was substantiated through internal validation, demonstrating favorable discrimination, calibration, and clinical utility. A high level of SII was associated with both worse OS and shorter EUR-free survival.

A novel nomogram for predicting extraurothelial recurrence in patients with upper urinary tract urothelial carcinoma after radical nephroureterectomy.

PURPOSE: We aimed to establish and validate a nomogram for extraurothelial recurrence (EUR) after radical nephroureterectomy (RNU) for upper urinary tract urothelial carcinoma (UTUC). METHODS: The data of 521 patients with UTUC after RNU from 2 medical centers were retrospectively studied and were used as training cohort (n = 301) and external validation cohort (n = 220). We used the least absolute shrinkage and selection operator (LASSO) to select variables for multivariable Cox regression, and included independent risk factors into nomogram models predicting EUR-free survival (EURFS). Multiple parameters were used to validate the nomogram, including the concordance index (C-index), the calibration plots, the time-dependent receiver-operator characteristics curve (ROC), and the decision curve analysis (DCA). Patients were stratified into three risk groups according to total points calculated by nomograms. The differences of EURFS in each group were analyzed by the Kaplan-Meier analysis. RESULTS: Four variables were screened through LASSO regression. Bladder cancer history, Ki-67, lymphovascular invasion (LVI), and pathological T stage were shown to be independent predictive factors for EUR. The C-indexes of the model were 0.793 and 0.793 in training and validation cohorts, respectively. In comparison with prediction based on categorized pathological T stage, the DCA curves for 5-year EUR exhibited better performance. The 5-year EURFS rates were 92.2%, 63.8%, and 36.2% in patients stratified to the low-, medium-, and high-risk group. CONCLUSION: Our study provided a new nomogram to predict the probability of EUR in UTUC patients underwent RNU, with perfect performance in discrimination ability and clinical net benefit. The application of the model may help urologists to choose proper treatment and monitoring.

Do patients with metastatic renal cell carcinoma obtain survival benefits from cytoreductive nephrectomy? A population-based study.

PURPOSE: This study aimed to explore the value of cytoreductive nephrectomy (CN) and develop nomograms to predict the prognosis of metastatic renal cell carcinoma (mRCC) patients with receiving radiology therapy or/and chemotherapy (RT/&CT). METHODS: Clinical data of patients with mRCC between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Prognostic nomograms were constructed to predict the overall survival (OS) and cancer-specific survival (CSS) probability for 1-, 3-, and 5- years in patients with mRCC. A series of validation methods were used to validate the accuracy and reliability of the model, including area under the receiver operating curve (AUC), consistency index (C-index), calibration curve, and decision curve analysis (DCA). RESULTS: 1394 patients were enrolled in this study. All patients were randomly divided into the training cohort (n = 976) and the validation cohort (n = 418). In the training cohort, multivariate Cox regression analysis suggested that pathology grade, histology type, T stage, N stage, surgery, and distant metastasis were independent risk factors for OS and CSS. The AUC and C-index were both over 0.65 in both cohorts, indicating that the nomograms for OS and CSS had satisfactory discriminative power. The calibration curves revealed that the predictive nomograms had a good consistency between the observed and the predicted survival. CONCLUSION: This study provided evidence that mRCC patients underwent RT/&CT could gain survival benefits from CN. The prognostic nomogram constructed in our study is reliable and practical, may help guide clinical strategies in the treatment of mRCC.