Introduction: Despite advances in treatment, metastatic urothelial carcinoma of the urinary bladder (mUCUB) is associated with high mortality and treatment risk. We tested for regional differences in mUCUB within a large-scale, population-based database. Methods: Using the Surveillance, Epidemiology and End Results (SEER) database (2010–2018), patient (age, sex, race/ethnicity), tumor (T-stage, N-stage, number of metastatic sites), and treatment (systemic therapy, radical cystectomy) characteristics were tabulated for mUCUB patients according to 11 SEER registries. Multinomial regression models and multivariable Cox regression models tested overall mortality (OM), adjusting for patient, tumor and treatment characteristics. Results: In 4817 mUCUB patients, registry-specific patient counts ranged from 1855 (38.5%) to 105 (2.2%). Important inter-regional differences existed for race/ethnicity (3–36% for others than non-Hispanic Whites), N-stage (28–39% for N1–3, 44–58% in N0, 8–22% for unknown N-stage), systemic therapy (38–54%) and radical cystectomy (3–11%). In multivariable analyses adjusting for these patient, tumor, and treatment characteristics, one registry exhibited significantly lower OM (SEER registry 10: hazard ratio [HR] 0.83) and two other registries exhibited significantly higher OM (SEER registries 9: HR 1.13; SEER registry 8: HR 1.24) relative to the largest reference registry (n=1855). Conclusions: We identified important regional differences that included patient, tumor, and treatment characteristics. Even after adjustment for these characteristics, important OM differences persisted, which may warrant more detailed investigation.
To test for regional differences in clear cell metastatic renal cell carcinoma (ccmRCC) patients across the USA.The Surveillance, Epidemiology, and End Results (SEER) database (2000-2018) was used to tabulate patient (age at diagnosis, sex, race/ethnicity), tumor (N stage, sites of metastasis) and treatment characteristics (proportions of nephrectomy and systemic therapy), according to 12 SEER registries. Multinomial regression models, as well as multivariable Cox regression models, tested the overall mortality (OM) adjusting for those patient, tumor and treatment characteristics.In 9882 ccmRCC patients, registry-specific patient counts ranged from 4025 (41%) to 189 (2%). Differences across registries existed for sex (24-36% female), race/ethnicity (1-75% non-Caucasian), N stage (N1 25-35%, NX 3-13%), proportions of nephrectomy (44-63%) and systemic therapy (41-56%). Significant inter-registry differences remained after adjustment for proportions of nephrectomy (46-63%) and systemic therapy (35-56%). Unadjusted 5-year OM ranged from 73 to 85%. In multivariable analyses, three registries exhibited significantly higher OM (SEER registry 5: hazard ratio (HR) 1.20, p = 0.0001; SEER registry 7:HR 1.15, p = 0.008M SEER registry 10: HR 1.15, p = 0.04), relative to the largest reference registry (n = 4025).Important regional differences including patient, tumor and treatment characteristics exist, when ccmRCC patients included in the SEER database are studied. Even after adjustment for these characteristics, important OM differences persisted, which may require more detailed analyses to further investigate these unexpected differences.
This study aimed to test for temporal trends of in-hospital venous thromboembolism (VTE) and pulmonary embolism (PE) after major urologic cancer surgery (MUCS).In the Nationwide Inpatient Sample (NIS) database (2010-2019), this study identified non-metastatic radical cystectomy (RC), radical prostatectomy (RP), radical nephrectomy (RN), and partial nephrectomy (PN) patients. Temporal trends of VTE and PE and multivariable logistic regression analyses (MLR) addressing VTE or PE, and mortality with VTE or PE were performed.Of 196,915 patients, 1180 (1.0%) exhibited VTE and 583 (0.3%) exhibited PE. The VTE rates increased from 0.6 to 0.7% (estimated annual percentage change [EAPC] + 4.0%; p = 0.01). Conversely, the PE rates decreased from 0.4 to 0.2% (EAPC - 4.5%; p = 0.01). No difference was observed in mortality with VTE (EAPC - 2.1%; p = 0.7) or with PE (EAPC - 1.2%; p = 0.8). In MLR relative to RP, RC (odds ratio [OR] 5.1), RN (OR 4.5), and PN (OR 3.6) were associated with higher VTE risk (all p < 0.001). Similarly in MLR relative to RP, RC (OR 4.6), RN (OR 3.3), and PN (OR 3.9) were associated with higher PE risk (all p < 0.001). In MLR, the risk of mortality was higher when VTE or PE was present in RC (VTE: OR 3.7, PE: OR 4.8; both p < 0.001) and RN (VTE: OR 5.2, PE: OR 8.3; both p < 0.001).RC, RN, and PN predisposes to a higher VTE and PE rates than RP. Moreover, among RC and RN patients with either VTE or PE, mortality is substantially higher than among their VTE or PE-free counterparts.
Within the Surveillance, Epidemiology, and End Results database (2000-2019), we identified 5522 unilateral surgically treated non-metastatic chromophobe kidney cancer (chRCC) patients. This population was randomly divided into development vs. external validation cohorts. In the development cohort, the original Leibovich 2018 and GRANT categories were applied to predict 5- and 10-year cancer-specific survival (CSS). Subsequently, a novel multivariable nomogram was developed. Accuracy, calibration and decision curve analyses (DCA) tested the Cox regression-based nomogram as well as the Leibovich 2018 and GRANT risk categories in the external validation cohort. The accuracy of the Leibovich 2018 and GRANT models was 0.65 and 0.64 at ten years, respectively. The novel prognostic nomogram had an accuracy of 0.78 at ten years. All models exhibited good calibration. In DCA, Leibovich 2018 outperformed the novel nomogram within selected ranges of threshold probabilities at ten years. Conversely, the novel nomogram outperformed Leibovich 2018 for other values of threshold probabilities. In summary, Leibovich 2018 and GRANT risk categories exhibited borderline low accuracy in predicting CSS in North American non-metastatic chRCC patients. Conversely, the novel nomogram exhibited higher accuracy. However, in DCA, all examined models exhibited limitations within specific threshold probability intervals. In consequence, all three examined models provide individual predictions that might be suboptimal and be affected by limitations determined by the natural history of chRCC, where few deaths occur within ten years from surgery. Further investigations regarding established and novel predictors of CSS and relying on large sample sizes with longer follow-up are needed to better stratify CSS in chRCC.
