Predicting the probability of pT3 or higher pathological stage at radical prostatectomy: COVID19-specific considerations.

Background: We tested whether a model identifying prostate cancer (PCa) patients at risk of pT3-4/pN1 can be developed for use during COVID19 pandemic, in order to guarantee appropriate treatment to patients harboring advanced disease patients without compromising sustainability of care delivery. Methods: Within the Surveillance, Epidemiology and End Results database 2010-2016, we identified 27,529 patients with localized PCa and treated with radical prostatectomy. A multivariable logistic regression model predicting presence of pT3-4/pN1 disease was fitted within a development cohort (n=13,977, 50.8%). Subsequently, external validation (n=13,552, 49.2%) and head-to-head comparison with NCCN risk group stratification was performed. Results: In model development, age, PSA, biopsy Gleason Grade Group (GGG) and percentage of positive biopsy cores were independent predictors of pT3-4/pN1 stage. In external validation, prediction of pT3-4/pN1 with novel nomogram was 74% accurate versus 68% for NCCN risk group stratification. Nomogram achieved better calibration and showed net-benefit over NCCN risk group stratification in decision curve analyses. The use of nomogram cut-off of 49% resulted in pT3-4/pN1 rate of 65%, instead of the average 35%. Conclusion: The newly developed, externally validated nomogram predicts presence of pT3-4/pN1 better than NCCN risk group stratification and allows to focus radical prostatectomy treatment on individuals at highest risk of pT3-4/pN1.

Tumor Stage and Substage Predict Cancer-specific Mortality After Nephrectomy for Nonmetastatic Renal Cancer: Histological Subtype-specific Validation.

BACKGROUND: For patients with nonmetastatic renal cell carcinoma (nmRCC) treated with nephrectomy, prediction of cancer-specific mortality (CSM) by T stage and substage has not been validated for the separate histological subtypes. OBJECTIVE: To investigate the ability of pathological T stage and substage to predict CSM for patients with clear-cell, papillary, or chromophobe nmRCC treated with nephrectomy. DESIGN, SETTING, AND PARTICIPANTS: Using the SEER database for 2004-2016, we identified 87 149 patients with T1-4 N0/X M0 nmRCC treated with nephrectomy for the clear-cell (65 715; 75.4%), papillary (14 587; 16.7%), or chromophobe (6847; 7.9%) histological subtype. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Kaplan-Meier plots and Cox regression models were used to estimate CSM. RESULTS AND LIMITATIONS: For all three histological subtypes, patients with T1a-T3a disease exhibited more favorable CSM than patients with T3b-T4 RCC. For clear-cell RCC, there were clinically meaningful and statistically significant differences for virtually all intergroup comparisons among T1a-T3a stages. For papillary T1a-T3a RCC, clinically meaningful differences disappeared, although the statistical significance remained. For chromophobe T1a-T3a RCC, no clinically meaningful or statistically significant differences were observed. For all three histological subtypes, patients with T3b-T4 RCC exhibited virtually uniformly unfavorable CSM, with no clinically meaningful intergroup CSM differences. CONCLUSION: The use of T stage and substage for stratification of patients with nmRCC treated with nephrectomy revealed differences in CSM among T1a-T3a cases, but not T3b-T4. The magnitude of the CSM difference was greatest for clear-cell, intermediate for papillary, and marginal for chromophobe RCC. PATIENT SUMMARY: For patients with kidney cancer, the stage of their disease assessed after surgery on the affected kidney can predict how likely they are to die from their cancer. This prediction varies for different subtypes of kidney cancer.

Improving the stratification of intermediate risk prostate cancer.

BACKGROUND: Intermediate risk prostate cancer (IR PCa) may exhibit a wide array of phenotypes, from favorable to unfavorable. NCCN criteria help distinguishing between favorable versus unfavorable subgroups. We studied and attempted to improve this classification. METHODS: Within the SEER database 2010-2016, we identified 19,193 IR PCa patients treated with radical prostatectomy. A multivariable logistic regression model predicting unfavorable IR PCa was developed and externally validated, in addition to a head-to-head comparison with NCCN IR PCa stratification. RESULTS: Model development (development cohort N.=13,436: 3585 unfavorable versus 9851 favorable) rested on age, PSA, clinical T stage, biopsy Gleason Grade Group (GGG) and percentage of positive cores. All were independent predictors of unfavorable IR PCa. In external validation cohort (N.=5757: 1652 unfavorable versus 4105 favorable), NCCN stratification was 61.8% accurate in discriminating between favorable versus unfavorable, compared to 67.6% for nomogram, which exhibited excellent calibration, less pronounced departures from ideal prediction and greater net-benefit in decision curve analyses (DCA) than NCCN stratification. The optimal nomogram cutoff misclassified 312 of 1976 patients (15.8%) versus 598 of 2877 (20.8%) for NCCN stratification. Of NCCN misclassified patients, 90.0% harbored pT3-4 stages versus 84.6% of nomogram. CONCLUSIONS: The newly developed, externally validated nomogram discriminates better between favorable versus unfavorable IR PCa, according to overall accuracy, calibration, DCA, and actual numbers and stage distribution of misclassified patients.

Higher Cancer Mortality in Rural Upper Urinary Tract Urothelial Carcinoma Patients.

OBJECTIVE: The aim of the study was to investigate differences in the stage at presentation and cancer-specific mortality (CSM) between rural area (RA) and urban area (UA) residence status in nonmetastatic upper urinary tract urothelial carcinoma (UTUC) patients. METHODS: Newly diagnosed T1-3N0M0 UTUC patients with available residence status were abstracted from the Surveillance, Epidemiology, and End Results database (2004-2016). Propensity score (PS) matching (1 RA vs. 3 UA) accounted for age (interval ≤2 years), T stage (exact matching: T1, T2, and T3), and tumor grade (exact matching: high grade, low grade/unknown). Cumulative incidence plots and multivariable competing risk regression models focused on CSM, after adjustment for other-cause mortality. RESULTS: Of 6,012 patients, 125 (2.1%) resided in RAs and 5,887 (97.9%) in UAs. RA patients were younger than UA patients (median age 72 vs. 75 years, p = 0.03). No differences were recorded in tumor location, T stage, tumor grade, or surgical treatment between RA and UA patients. After 1:3 PS matching, 125 RA patients and 375 UA patients were assessable. At 5 years of follow-up, CSM rates were 26.7 versus 15.7% according to RA versus UA, respectively. After additional multivariable adjustment for age, sex, tumor location, and surgical treatment, RA remained an independent predictor of higher CSM (hazard ratio 1.75, p = 0.02). CONCLUSIONS: Despite no differences in cancer characteristics, UTUC patients in RA are at higher risk of CSM than their UA counterparts. This suggests suboptimal care delivery and compliance as possible causes. Complex and/or rare disease should be centralized to expert centers, which are often in UAs.

Predicting the risk of pT3a stage in cT1 clear cell renal cell carcinoma.

We hypothesized that pT3a stage at nephrectomy can be accurately predicted in cT1N0M0 clear cell-renal cell carcinoma (cc-RCC) patients. Of 236 patients, treated with either partial or radical nephrectomy (2005-2019), 25 (10.6%) harbored pT3a stage. Multivariable logistic regression models predicting pT3a were fitted using age, tumor size, tumor location and exophytic rate. The new model was 81% accurate. In calibration plots, minimal departures from ideal prediction were recorded. In decision curve analyses, a net-benefit throughout all threshold probabilities was recorded relative to the treat-all or treat-none strategies. Using a probability cut-off of 21% for presence of pT3a stage, 38 patients (16.1%) were identified, in whom pT3a rate was 36.8%. Conversely, in 198 patients (83.9%) below that cut-off, the rate of pT3a was 5.6%. Alternative user-defined cut-offs may be selected. The new model more accurately identifies a subgroup of cT1N0M0 cc-RCC patients with substantially higher risk of pT3a stage than average.

Rates of other-cause mortality after radical cystectomy are decreasing over time-A population-based analysis over two decades.

BACKGROUND AND OBJECTIVES: To investigate other-cause mortality (OCM) rates over time according to several baseline characteristics in bladder cancer (BCa) patients treated with radical cystectomy (RC). METHODS: Within the Surveillance, Epidemiology, and End Results database (1988-2011), we identified 7702 T1-2 N0 M0 urothelial BCa patients treated with RC. Temporal trends and multivariable Cox regression (MCR) analyses assessed 5-year OCM. Data were stratified according to the year of diagnosis (1988-1995 vs 1996-2000 vs 2001-2004 vs 2005-2008 vs 2009-2011), age group (<60 vs 60-75 vs >75 years), sex, race, marital status, and socioeconomic status. RESULTS: Overall, OCM rates decreased from 13.9% in 1988-1995 to 8.6% in 2009-2011. The greatest decrease was recorded in elderly (>75) patients (32%-16%, slope: -0.55% per year; P = .01), followed by patients aged 60 to 75 (21%-5%, slope: -0.35% per year; P = .01), unmarried patients (16%-10%, slope: -0.26% per year; P < .001), male patients (14%-8.9%, slope: -0.23% per year), and African Americans (16%-11%, slope: -0.27% per year; P < .001). MCR models corroborated these results. CONCLUSIONS: Most important decrease in OCM after RC over the last decades was recorded in the elderly, unmarried, and male patients. Nonetheless, these three patient groups still represent ideal targets for efforts aimed at minimizing the morbidity and mortality after RC, as their risk of OCM is higher than in others.