Prediction of the Need for an Extended Lymphadenectomy at the Time of Radical Cystectomy in Patients with Bladder Cancer

Perioperative outcomes using template mapping after radical cystectomy and extended lymph node dissection

BACKGROUND

To evaluate oncologic and perioperative outcomes of extended pelvic lymph node dissection (PLND) during robot-assisted radical cystectomy (RARC) based on the location of lymph node positivity (LN+).

METHODS

We reviewed a tertiary center database of patients with bladder cancer who underwent extended PLND during RARC from 2004 to 2020. Patients were assigned to a standard (sPLN+) or extended (ePLN+) cohort based on LN+ location. ePLN+ patients were LN+ in one or more of the following: common iliac, presacral, aortic bifurcation, or paracaval packets. The Kaplan-Meier method estimated recurrence-free survival (RFS) and overall survival (OS). Perioperative 90-day complications were identified using the Clavien-Dindo system.

RESULTS

Ninety patients were included; 43 (48%) were sPLN+, and 47 (52%) were ePLN+. The median follow-up for sPLN+ and ePLN+ patients was 14.9 and 20.0 months, respectively. ePLN+ patients were older than sPLN+ patients (median age 75 vs. 68 years, p = 0.019). There were more ≤ cT1 LN+ patients in the sPLN+ cohort compared to the ePLN+ cohort (26% vs. 9%, p = 0.037). We recorded no differences in 90-day mortality or in RFS or OS between baseline and 12-year follow-up between groups (all, p > 0.05). Overall, the grade II or higher complication rate was 71%, with similar rates for the sPLN+ and ePLN+ (77% vs. 66%, p = 0.26) cohorts.

CONCLUSION

Location of LN+ does not affect oncologic outcomes in patients who underwent extended PLND. This underscores the lack of a notable therapeutic benefit beyond the standard dissection template.

CLINICAL TRIAL NUMBER

Not applicable.

Use of 18F-fluoro-2-deoxy-d-glucose (18F-FDG) PET/CT for lymph node assessment before radical cystectomy in bladder cancer patients

OBJECTIVE

To assess the diagnostic performance of 18F-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomograpy (PET)/computed tomography (CT) in nodal staging before radical cystectomy (RC) and pelvic lymph node dissection (PLND) for bladder cancer (BCa).

MATERIALS AND METHODS

This analysis was based on a cohort of 199 BCa patients undergoing RC and bilateral PLND between 2015 and 2022. Neoadjuvant chemotherapy (NAC) or immunotherapy (NAI) was administered after oncological evaluation. All patients received preoperative 18F-FDG PET/CT to assess extravesical disease. Point estimates for true negative, false negative, false positive, true positive, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of conventional imaging and PET/CT were calculated. Subgroup analysis in patients receiving neoadjuvant treatment was performed.

RESULTS

At preoperative evaluation, 30 patients (15.1%) had 48 suspicious nodal spots on 18F-FDG PET/CT. At RC and bilateral PLND, a total of 4871 lymph nodes (LNs) were removed with 237 node metastases corresponding to 126 different regions. Pathological node metastases were found in 17/30 (57%) vs 39/169 patients (23%) with suspicious vs negative preoperative 18F-FDG PET/CT, respectively (sensitivity = 0.30, specificity = 0.91, PPV = 0.57, NPV = 0.77, accuracy = 0.74). On per-region analysis including 1367 nodal regions, LN involvement was found in 19/48 (39%) vs 105/1319 (8%) suspicious vs negative regions at PET/CT, respectively (sensitivity = 0.15, specificity = 0.98, PPV = 0.40, NPV = 0.92, ACC = 0.90). Similar results were observed for patients receiving NAC (n = 44, 32.1%) and NAI (n = 93, 67.9% [per-patient: sensitivity = 0.36, specificity = 0.91, PPV = 0.59, NPV = 0.80, accuracy = 0.77; per-region: sensitivity = 0.12, specificity = 0.98, PPV = 0.32, NPV = 0.93, ACC = 0.91]). Study limitations include its retrospective design and limited patient numbers.

CONCLUSIONS

In eight out of 10 patients with negative preoperative 18F-FDG PET/CT, pN0 disease was confirmed at final pathology. No differences were found based on NAC vs NAI treatment. These findings suggest that 18F-FDG PET/CT could play a role in the preoperative evaluation of nodal metastases in BCa patients, although its cost-effectiveness is uncertain.

Preoperative low plasma creatine kinase levels predict worse survival outcomes in bladder cancer after radical cystectomy

BACKGROUND AND AIMS

To evaluate the prognostic significance of preoperative creatine kinase (CK) levels in bladder cancer (BCa) patients who underwent radical cystectomy (RC).

MATERIALS AND METHODS

570 BCa patients with RC were identified between 2010 and 2020. 108.5 U/L of CK levels were defined as the cutoff value. Logistic regression analysis and Cox regression models were performed to evaluate the association between CK levels and oncologic outcomes. Subgroup analyses were performed to address cofounding factors.

RESULTS

Preoperative low CK levels were associated with worse recurrence-free survival (RFS, log-rank P = 0.001) and overall survival (OS, log-rank P = 0.002). Multivariate analysis revealed that preoperative low CK levels were an independent predictor for worse RFS (hazard ratio [HR]: 1.683; P < 0.001) and OS (HR: 1.567; P = 0.002).

CONCLUSIONS

The preoperative low CK level independently predicts worse survival outcomes in BCa after RC. Incorporating it into prediction models might be valuable to assist risk stratification.

Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma

BACKGROUND

Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated with radical cystectomy (RC).

METHODS

We retrospectively collected demographic, pathological, imaging, and laboratory information of BUC patients who underwent RC and bilateral lymphadenectomy in our institution. Patients were randomly categorized into training set and testing set. Five ML algorithms were utilized to establish prediction models. The performance of each model was assessed by the area under the receiver operating characteristic curve (AUC) and accuracy. Finally, we calculated the corresponding variable coefficients based on the optimal model to reveal the contribution of each variable to LNM.

RESULTS

A total of 524 and 131 BUC patients were finally enrolled into training set and testing set, respectively. We identified that the support vector machine (SVM) model had the best prediction ability with an AUC of 0.934 (95% confidence interval [CI]: 0.903-0.964) and accuracy of 0.916 in the training set, and an AUC of 0.855 (95%CI: 0.777-0.933) and accuracy of 0.809 in the testing set. The SVM model contained 14 predictors, and positive lymph node in imaging contributed the most to the prediction of LNM in BUC patients.

CONCLUSIONS

We developed and validated the ML models to preoperatively predict LNM in BUC patients treated with RC, and identified that the SVM model with 14 variables had the best performance and high levels of clinical applicability.

Impact of the extent of lymph node dissection on survival outcomes in clinically lymph node-positive bladder cancer

OBJECTIVE

To determine the oncological impact of extended pelvic lymph node dissection (ePLND) vs standard PLND (sPLND) during radical cystectomy (RC) in clinically lymph node-positive (cN+) bladder cancer (BCa).

PATIENTS AND METHODS

In this retrospective, multicentre study we included 969 patients who underwent RC with sPLND (internal/external iliac and obturator lymph nodes) or ePLND (sPLND plus common iliac and presacral nodes) with or without platin-based peri-operative chemotherapy for cTany N1-3 M0 BCa between 1991 and 2022. We assessed the impact of ePLND on recurrence-free survival (RFS) and the distribution of recurrences (locoregional and distant recurrences). The secondary endpoint was overall survival (OS). We performed propensity-score matching using covariates associated with the extent of PLND in univariable logistic regression analysis. The association of the extent of PLND with RFS and OS was investigated using Cox regression models.

RESULTS

Of 969 cN+ patients, 510 were 1:1 matched on propensity scores. The median (interquartile range [IQR]) time to recurrence was 8 (4-16) months, and median (IQR) follow-up of alive patients was 30 (13-51) months. Disease recurrence was observed in 104 patients in the ePLND and 107 in the sPLND group. Of these, 136 (27%), 47 (9.2%) and 19 patients (3.7%) experienced distant, locoregional, or both distant and locoregional disease recurrence, respectively. When stratified by the extent of PLND, we did not find a difference in recurrence patterns (P > 0.05). ePLND improved neither RFS (hazard ratio [HR] 0.91, 95% confidence interval [CI] 0.70-1.19; P = 0.5) nor OS (HR 0.78, 95% CI 0.60-1.01; P = 0.06) compared to sPLND. Stratification by induction chemotherapy did not change outcomes.

CONCLUSION

Performing an ePLND at the time of RC in cN+ patients improved neither RFS nor OS compared to sPLND, regardless of induction chemotherapy status. Pretreatment risk stratification is paramount to identify ideal candidates for RC with ePLND as part of a multimodal treatment approach.

Pelvic lymphadenectomy: Evaluating nodal stage migration and will rogers effect in bladder cancer

INTRODUCTION

Pelvic lymphadenectomy (PLND) alongside radical cystectomy (RC), provides crucial diagnostic and therapeutic value in patients with bladder cancer. With the advent of neoadjuvant chemotherapy and prospective data supporting standard PLND, controversy remains regarding the optimal PLND extent and patient selection. Nearly 40% of patients may not receive adequate PLND, even though 25% of patients have positive lymph nodes (LN) at time of RC. We hypothesized that PLND still remains an important facet of bladder cancer treatment. To clarify the prognostic importance of nodal yield, we performed a retrospective investigation of a heterogenous population (pTanyNx/0M0) of patients undergoing RC.

METHODS

From the Surveillance, Epidemiology, and End Results (SEER) program, we identified pTanyNx/0M0 bladder cancer patients undergoing RC from 2004 to 2015. Kaplan Meier curves and Cox proportional hazards models assessed cancer-specific survival. Patients were analyzed with PLND performed as the primary covariate. Survival analysis then stratified patients undergoing PLND by LN yield, both as a continuous and categorial variable (≤10, 11-20, 21-30, and >30), and T stage.

RESULTS

The final cohort included pTanyNx/0M0 patients with urothelial bladder cancer (n = 12,096); median follow up was 39 (IQR: 17-77) months. PLND was performed in 81.45% of patients with a median LN yield of 14 (IQR: 7-23). Most commonly, patients had T2 disease (44.68%). After controlling for age and T stage, patients receiving PLND had improved CSS (HR = 0.56, [95% CI: 0.51-0.62]) compared to those that did not receive PLND. When grouping patients by LN yield, survival improved in a "dose dependent" manner (>30 LN: HR = 0.76, [95% CI: 0.66-0.87]). We noted similar results when stratifying patients into non-muscle-invasive (NMIBC) and muscle-invasive bladder cancer (MIBC).

CONCLUSIONS

In a large contemporary series of pTanyNx/0M0 bladder cancer patients, we found a significant oncologic benefit to PLND. Higher LN yield correlated to improved CSS in non-muscle-invasive and muscle-invasive disease. Our data support the possibility of occult micrometastasis even in non-muscle-invasive disease. Additionally, in light of recent advances in adjuvant immunotherapy, our results emphasize the importance of adequate nodal yield for accurate staging and optimal treatment.

Performance of Node-RADS Scoring System for a Standardized Assessment of Regional Lymph Nodes in Bladder Cancer Patients

BACKGROUND

Current cross-sectional imaging modalities exhibit heterogenous diagnostic performances for the detection of a lymph node invasion (LNI) in bladder cancer (BCa) patients. Recently, the Node-RADS score was introduced to provide a standardized comprehensive evaluation of LNI, based on a five-item Likert scale accounting for both size and configuration criteria. In the current study, we hypothesized that the Node-RADS score accurately predicts the LNI and tested its diagnostic performance.

METHODS

We retrospectively reviewed BCa patients treated with radical cystectomy (RC) and bilateral extended pelvic lymph node dissection, from January 2019 to June 2022. Patients receiving preoperative systemic chemotherapy were excluded. A logistic regression analysis tested the correlation between the Node-RADS score and LNI both at patient and lymph-node level. The ROC curves and the AUC depicted the overall diagnostic performance. In addition, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for different cut-off values (>1, >2, >3, >4).

RESULTS

Overall, data from 49 patients were collected. Node-RADS assigned on CT scans images, was found to independently predict the LNI after an adjusted multivariable regression analysis, both at the patient (OR 3.36, 95%CI 1.68-9.40, p = 0.004) and lymph node (OR 5.18, 95%CI 3.39-8.64, p < 0.001) levels. Node-RADS exhibited an AUC of 0.87 and 0.91 at the patient and lymph node levels, respectively. With increasing Node-RADS cut-off values, the specificity and PPV increased from 57.1 to 97.1% and from 48.3 to 83.3%, respectively. Conversely, the sensitivity and NPV decreased from 100 to 35.7% and from 100 to 79.1%, respectively. Similar trends were recorded at the lymph node level. Potentially, Node-RADS > 2 could be considered as the best cut-off value due to balanced values at both the patient (77.1 and 78.6%, respectively) and lymph node levels (82.4 and 93.4%, respectively).

CONCLUSIONS

The current study lays the foundation for the introduction of Node-RADS for the regional lymph-node evaluation in BCa patients. Interestingly, the Node-RADS score exhibited a moderate-to-high overall accuracy for the identification of LNI, with the possibility of setting different cut-off values according to specific clinical scenarios. However, these results need to be validated on larger cohorts before drawing definitive conclusions.

Management of Bladder Cancer Patients with Clinical Evidence of Lymph Node Invasion (cN+)

The purpose of this review is to present the current knowledge about the diagnostic and treatment options for bladder cancer (BCa) patients with clinically positive lymph nodes (cN+). This review shows compaction of CT and MRI performance in preoperative prediction of lymph node invasion (LNI) in BCa patients, along with other diagnostic methods. Most scientific societies do not distinguish cN+ patients in their guidelines; recommendations concern muscle-invasive bladder cancer (MIBC) and differ between associations. The curative treatment that provides the best long-term survival in cN+ patients is a multimodal approach, with a combination of neoadjuvant chemotherapy (NAC) and radical cystectomy (RC) with extended pelvic lymph node dissection (ePLND). The role of adjuvant chemotherapy (AC) remains uncertain; however, emerging evidence indicates comparable outcomes to NAC. Therefore, in cN+ patients who have not received NAC, AC should be implemented. The response to ChT is a crucial prognostic factor for cN+ patients. Recent studies demonstrated the growing importance of immunotherapy, especially in ChT-ineligible patients. Moreover, immunotherapy can be suitable as adjuvant therapy in selected cases. In cN+ patients, the extended template of PLND should be utilized, with the total resected node count being less important than the template. This review is intended to draw special attention to cN+ BCa patients, as the oncological outcomes are significantly worse for this group.

A panel of systemic inflammatory response biomarkers for outcome prediction in patients treated with radical cystectomy for urothelial carcinoma

Objectives

To determine the predictive and prognostic value of a panel of systemic inflammatory response (SIR) biomarkers relative to established clinicopathological variables in order to improve patient selection and facilitate more efficient delivery of peri‐operative systemic therapy.

Materials and Methods

The preoperative serum levels of a panel of SIR biomarkers, including albumin–globulin ratio, neutrophil–lymphocyte ratio, De Ritis ratio, monocyte–lymphocyte ratio and modified Glasgow prognostic score were assessed in 4199 patients treated with radical cystectomy for clinically non‐metastatic urothelial carcinoma of the bladder. Patients were randomly divided into a training and a testing cohort. A machine‐learning‐based variable selection approach (least absolute shrinkage and selection operator regression) was used for the fitting of several multivariable predictive and prognostic models. The outcomes of interest included prediction of upstaging to carcinoma invading bladder muscle (MIBC), lymph node involvement, pT3/4 disease, cancer‐specific survival (CSS) and recurrence‐free survival (RFS). The discriminatory ability of each model was either quantified by area under the receiver‐operating curves or by the C‐index. After validation and calibration of each model, a nomogram was created and decision‐curve analysis was used to evaluate the clinical net benefit.

Results

For all outcome variables, at least one SIR biomarker was selected by the machine‐learning process to be of high discriminative power during the fitting of the models. In the testing cohort, model performance evaluation for preoperative prediction of lymph node metastasis, ≥pT3 disease and upstaging to MIBC showed a 200‐fold bootstrap‐corrected area under the curve of 67.3%, 73% and 65.8%, respectively. For postoperative prognosis of CSS and RFS, a 200‐fold bootstrap corrected C‐index of 73.3% and 72.2%, respectively, was found. However, even the most predictive combinations of SIR biomarkers only marginally increased the discriminative ability of the respective model in comparison to established clinicopathological variables.

Conclusion

While our machine‐learning approach for fitting of the models with the highest discriminative ability incorporated several previously validated SIR biomarkers, these failed to improve the discriminative ability of the models to a clinically meaningful degree. While the prognostic and predictive value of such cheap and readily available biomarkers warrants further evaluation in the age of immunotherapy, additional novel biomarkers are still needed to improve risk stratification.