Developing a nomogram for predicting intravesical recurrence after radical nephroureterectomy: a retrospective cohort study of mainland Chinese patients

Development and external validation of a novel nomogram to predict intravesical recurrence after radical nephroureterectomy: a multicenter study

OBJECTIVE

This study aimed to establish and validate nomograms to predict the probability of intravesical recurrence (IVR) after radical nephroureterectomy (RNU) for upper urinary tract epithelial carcinoma (UTUC).

METHODS

Clinical data of 528 patients with UTUC after RNU were collected from two medical centers between 2009 and 2020. We used the least absolute shrinkage and selection operator (LASSO) regression to select variables for multivariable Cox regression analysis in the training cohort and included independent risk factors into nomogram models predicting IVR-free survival (IVRFS). Another center was applied as the external cohort to validate the predictive accuracy and discriminative ability of the nomogram by performing area under the receiver operating curve (AUC), consistency index (C-index), and calibration curve.

RESULTS

History of bladder cancer, tumor size, preoperative urine cytology, postoperative instillation, Ki-67, and platelet-to-lymphocyte ratio (PLR) were identified as independent risk factors for IVR. The prognosis model including these predictors demonstrated excellent discriminatory performance in both the training cohort (C-index, 0.814) and external validation cohort (C-index, 0.748). The calibration plots of the nomogram revealed good consistency in both cohorts. Finally, patients could be classified into two risk groups based on scores obtained from the nomogram, with significant differences in IVRFS.

CONCLUSION

Our study provided a reliable nomogram for predicting the probability of IVR in patients with UTUC after RNU. Risk stratification based on this model may assist urologists make optimal clinical decisions on the management of UTUC.

A Systematic Review and Meta-Analysis of Prognostic Nomograms After UTUC Surgery

Background

Current guidelines recommend assessing the prognosis in high-risk upper tract urothelial carcinoma patients (UTUC) after surgery. However, no specific method is endorsed. Among the various prognostic models, nomograms represent an easy and accurate tool to predict the individual probability for a specific event. Therefore, identifying the best-suited nomogram for each setting seems of great interest to the patient and provider.

Objectives

To identify, summarize and compare postoperative UTUC nomograms predicting oncologic outcomes. To estimate the overall performance of the nomograms and identify the most reliable predictors. To create a reference tool for postoperative UTUC nomograms, physicians can use in clinical practice.

Design

A systematic review was conducted following the recommendations of Cochrane’s Prognosis Methods Group. Medline and EMBASE databases were searched for studies published before December 2021. Nomograms were grouped according to outcome measurements, the purpose of use, and inclusion and exclusion criteria. Random-effects meta-analyses were performed to estimate nomogram group performance and predictor reliability. Reference tables summarizing the nomograms’ important characteristics were created.

Results

The systematic review identified 26 nomograms. Only four were externally validated. Study heterogeneity was significant, and the overall Risk of Bias (RoB) was high. Nomogram groups predicting overall survival (OS), recurrence-free survival (RFS), and intravesical recurrence (IVR) had moderate discrimination accuracy (c-Index summary estimate with 95% confidence interval [95% CI] and prediction interval [PI] > 0.6). Nomogram groups predicting cancer-specific survival (CSS) had good discrimination accuracy (c-Index summary estimate with 95% CI and PI > 0.7). Advanced pathological tumor stage (≥ pT3) was the most reliable predictor of OS. Pathological tumor stage (≥ pT2), age, and lymphovascular invasion (LVI) were the most reliable predictors of CSS. LVI was the most reliable predictor of RFS.

Conclusions

Despite a moderate to good discrimination accuracy, severe heterogeneity discourages the uninformed use of postoperative prognostic UTUC nomograms. For nomograms to become of value in a generalizable population, future research must invest in external validation and assessment of clinical utility. Meanwhile, this systematic review serves as a reference tool for physicians choosing nomograms based on individual needs.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=282596, identifier PROSPERO [CRD42021282596].