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Background: To test the effect of urological primary cancers (bladder, kidney, testis, upper tract, penile, urethral) on overall mortality (OM) after secondary prostate cancer (PCa). Methods: Within the Surveillance, Epidemiology and End Results (SEER) database, patients with urological primary cancers and concomitant secondary PCa (diagnosed 2004-2016) were identified and were matched in 1:4 fashion with primary PCa controls. OM was compared between secondary and primary PCa patients and stratified according to primary urological cancer type, as well as to time interval between primary urological cancer versus secondary PCa diagnoses. Results: We identified 5,987 patients with primary urological and secondary PCa (bladder, n = 3,287; kidney, n = 2,127; testis, n = 391; upper tract, n = 125; penile, n = 47; urethral, n = 10) versus 531,732 primary PCa patients. Except for small proportions of Gleason grade group and age at diagnosis, PCa characteristics between secondary and primary PCa were comparable. Conversely, proportions of secondary PCa patients which received radical prostatectomy were smaller (29.0 vs. 33.5%), while no local treatment rates were higher (34.2 vs. 26.3%). After 1:4 matching, secondary PCa patients exhibited worse OM than primary PCa patients, except for primary testis cancer. Here, no OM differences were recorded. Finally, subgroup analyses showed that the survival disadvantage of secondary PCa patients decreased with longer time interval since primary cancer diagnosis. Conclusions: After detailed matching for PCa characteristics, secondary PCa patients exhibit worse survival, except for testis cancer patients. The survival disadvantage is attenuated, when secondary PCa diagnosis is made after longer time interval, since primary urological cancer diagnosis.
Background: To test the effect of urological primary cancers (bladder, kidney, testis, upper tract, penile, urethral) on overall mortality (OM) after secondary prostate cancer (PCa). Methods: Within the Surveillance, Epidemiology and End Results (SEER) database, patients with urological primary cancers and concomitant secondary PCa (diagnosed 2004-2016) were identified and were matched in 1:4 fashion with primary PCa controls. OM was compared between secondary and primary PCa patients and stratified according to primary urological cancer type, as well as to time interval between primary urological cancer versus secondary PCa diagnoses. Results: We identified 5,987 patients with primary urological and secondary PCa (bladder, n = 3,287; kidney, n = 2,127; testis, n = 391; upper tract, n = 125; penile, n = 47; urethral, n = 10) versus 531,732 primary PCa patients. Except for small proportions of Gleason grade group and age at diagnosis, PCa characteristics between secondary and primary PCa were comparable. Conversely, proportions of secondary PCa patients which received radical prostatectomy were smaller (29.0 vs. 33.5%), while no local treatment rates were higher (34.2 vs. 26.3%). After 1:4 matching, secondary PCa patients exhibited worse OM than primary PCa patients, except for primary testis cancer. Here, no OM differences were recorded. Finally, subgroup analyses showed that the survival disadvantage of secondary PCa patients decreased with longer time interval since primary cancer diagnosis. Conclusions: After detailed matching for PCa characteristics, secondary PCa patients exhibit worse survival, except for testis cancer patients. The survival disadvantage is attenuated, when secondary PCa diagnosis is made after longer time interval, since primary urological cancer diagnosis.
Background and Objectives: To test for differences in perioperative outcomes and total hospital costs (THC) in nonmetastatic bladder cancer patients undergoing open (ORC) versus robotic-assisted radical cystectomy (RARC).
Methods: We relied on the National Inpatient Sample database (2016–2019). Statistics consisted of trend analyses, multivariable logistic, Poisson, and linear regression models.
Results: Of 5280 patients, 1876 (36%) versus 3200 (60%) underwent RARC versus ORC. RARC increased from 32% to 41% (estimated annual percentage change [EAPC]: + 8.6%; p = 0.02). Rates of transfusion (8% vs. 16%), intraoperative (2% vs. 3%), wound (6% vs. 10%), and pulmonary (6% vs. 10%) complications were lower in RARC patients (all p < 0.05). Moreover, median length of stay (LOS) was shorter in RARC (6 vs. 7days; p < 0.001). Conversely, median THC (31,486 vs. 27,162$; p < 0.001) were higher in RARC. Multivariable logistic regression-derived odds ratios addressing transfusion (0.49), intraoperative (0.53), wound (0.68), and pulmonary (0.71) complications favored RARC (all p < 0.01). In multivariable Poisson and linear regression models, RARC was associated with shorter LOS (Rate ratio:0.86; p < 0.001), yet higher THC (Coef.:5,859$; p < 0.001). RARC in-hospital mortality was lower (1% vs. 2%; p = 0.04).
Conclusions: RARC complications, LOS, and mortality appear more favorable than ORC, but result in higher THC. The favorable RARC profile contributes to its increasing popularity throughout the United States.
Background: To test for differences in complication rates, in-hospital mortality, length of stay (LOS) and total hospital costs (THCs) in patients treated with neoadjuvant chemotherapy (NAC) prior to radical cystectomy (RC). Methods: Within the National (Nationwide) Inpatient Sample (NIS) database (2016–2019), we identified RC-treated, non-metastatic, lymph-node negative bladder cancer patients, stratified by NAC status. Trend analyses, multivariable logistic, multivariable Poisson and multivariable linear regression models were used. Results: We identified 4347 RC-treated bladder cancer patients. Of those, 805 (19%) received NAC prior to RC. Overall, complications rates did not differ (65 vs. 66%; p = 0.7). However, NAC patients harbored lower rates of surgical site (6 vs. 9%), cardiac (13 vs. 19%) and genitourinary (5.5 vs. 9.7%) complications. In-hospital mortality (<1.7 vs. 1.8%) and LOS (6 vs. 7 days) was lower in NAC patients (all p < 0.05). Moreover, NAC was an independent predictor of shorter LOS in multivariable Poisson regression models (Risk ratio: 0.86; p < 0.001) and an independent predictor for higher THCs in multivariable linear regression models (Odds ratio: 1474$; p = 0.02). Conclusion: NAC was not associated with higher complication rates and in-hospital mortality. Contrary, NAC was associated with shorter LOS, yet moderately higher THCs. The current analysis suggests no detriment from NAC in the context of RC.