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Background: To analyze postoperative, in-hospital, complication rates in patients with organ transplantation before radical prostatectomy (RP). Methods: From National Inpatient Sample (NIS) database (2000–2015) prostate cancer patients treated with RP were abstracted and stratified according to prior organ transplant versus nontransplant. Multivariable logistic regression models predicted in-hospital complications. Results: Of all eligible 202,419 RP patients, 216 (0.1%) underwent RP after prior organ transplantation. Transplant RP patients exhibited higher proportions of Charlson comorbidity index ≥2 (13.0% vs. 3.0%), obesity (9.3% vs. 5.6%, both p < 0.05), versus to nontransplant RP. Of transplant RP patients, 96 underwent kidney (44.4%), 44 heart (20.4%), 40 liver (18.5%), 30 (13.9%) bone marrow, <11 lung (<5%), and <11 pancreatic (<5%) transplantation before RP. Within transplant RP patients, rates of lymph node dissection ranged from 37.5% (kidney transplant) to 60.0% (bone marrow transplant, p < 0.01) versus 51% in nontransplant patients. Regarding in-hospital complications, transplant patients more frequently exhibited, diabetic (31.5% vs. 11.6%, p < 0.001), major (7.9% vs. 2.9%) cardiac complications (3.2% vs. 1.2%, p = 0.01), and acute kidney failure (5.1% vs. 0.9%, p < 0.001), versus nontransplant RP. In multivariable logistic regression models, transplant RP patients were at higher risk of acute kidney failure (odds ratio [OR]: 4.83), diabetic (OR: 2.81), major (OR: 2.39), intraoperative (OR: 2.38), cardiac (OR: 2.16), transfusion (OR: 1.37), and overall complications (1.36, all p < 0.001). No in-hospital mortalities were recorded in transplant patients after RP. Conclusions: Of all transplants before RP, kidney ranks first. RP patients with prior transplantation have an increased risk of in-hospital complications. The highest risk, relative to nontransplant RP patients appears to acute kidney failure.
Background: To test for rates of other cause mortality (OCM) and cancer-specific mortality (CSM) in elderly prostate cancer (PCa) patients treated with the combination of radical prostatectomy (RP) and external beam radiation therapy (EBRT) versus RP alone, since elderly PCa patients may be over-treated. Methods: Within the Surveillance, Epidemiology and End Results database (2004–2016), cumulative incidence plots, after propensity score matching for cT-stage, cN-stage, prostate specific antigen, age and biopsy Gleason score, and multivariable competing risks regression models (socioeconomic status, pathological Gleason score) addressed OCM and CSM in patients (70–79, 70–74, and 75–79 years) treated with RP and EBRT versus RP alone. Results: Of 18,126 eligible patients aged 70–79 years, 2520 (13.9%) underwent RP and EBRT versus 15,606 (86.1%) RP alone. After propensity score matching, 10-year OCM rates were respectively 27.9 versus 20.3% for RP and EBRT versus RP alone (p < .001), which resulted in a multivariable HR of 1.4 (p < .001). Moreover, 10-year CSM rates were respectively 13.4 versus 5.5% for RP and EBRT versus RP alone. In subgroup analyses separately addressing 70–74 year old and 75–79 years old PCa patients, 10-year OCM rates were 22.8 versus 16.2% and 39.5 versus 24.0% for respectively RP and EBRT versus RP alone patients (all p < .001). Conclusion: Elderly patients treated with RP and EBRT exhibited worrisome rates of OCM. These higher than expected OCM rates question the need for combination therapy (RP and EBRT) in elderly PCa patients and indicate the need for better patient selection, when combination therapy is contemplated.
Background: Number of positive prostate biopsy cores represents a key determinant between high versus very high-risk prostate cancer (PCa). We performed a critical appraisal of the association between the number of positive prostate biopsy cores and CSM in high versus very high-risk PCa. Methods: Within Surveillance, Epidemiology, and End Results database (2010–2016), 13,836 high versus 20,359 very high-risk PCa patients were identified. Discrimination according to 11 different positive prostate biopsy core cut-offs (≥2–≥12) were tested in Kaplan–Meier, cumulative incidence, and multivariable Cox and competing risks regression models. Results: Among 11 tested positive prostate biopsy core cut-offs, more than or equal to 8 (high-risk vs. very high-risk: n = 18,986 vs. n = 15,209, median prostate-specific antigen [PSA]: 10.6 vs. 16.8 ng/ml, <.001) yielded optimal discrimination and was closely followed by the established more than or equal to 5 cut-off (high-risk vs. very high-risk: n = 13,836 vs. n = 20,359, median PSA: 16.5 vs. 11.1 ng/ml, p < .001). Stratification according to more than or equal to 8 positive prostate biopsy cores resulted in CSM rates of 4.1 versus 14.2% (delta: 10.1%, multivariable hazard ratio: 2.2, p < .001) and stratification according to more than or equal to 5 positive prostate biopsy cores with CSM rates of 3.7 versus 11.9% (delta: 8.2%, multivariable hazard ratio: 2.0, p < .001) in respectively high versus very high-risk PCa. Conclusions: The more than or equal to 8 positive prostate biopsy cores cutoff yielded optimal results. It was very closely followed by more than or equal to 5 positive prostate biopsy cores. In consequence, virtually the same endorsement may be made for either cutoff. However, more than or equal to 5 positive prostate biopsy cores cutoff, based on its existing wide implementation, might represent the optimal choice.
Background: Recently, an increase in the rates of high-risk prostate cancer (PCa) was reported. We tested whether the rates of and low, intermediate, high and very high-risk PCa changed over time. We also tested whether the number of prostate biopsy cores contributed to changes rates over time. Methods: Within the Surveillance, Epidemiology and End Results (SEER) database (2010–2015), annual rates of low, intermediate, high-risk according to traditional National Comprehensive Cancer Network (NCCN) and high versus very high-risk PCa according to Johns Hopkins classification were tabulated without and with adjustment for the number of prostate biopsy cores. Results: In 119,574 eligible prostate cancer patients, the rates of NCCN low, intermediate, and high-risk PCa were, respectively, 29.7%, 47.8%, and 22.5%. Of high-risk patients, 39.6% and 60.4% fulfilled high and very high-risk criteria. Without adjustment for number of prostate biopsy cores, the estimated annual percentage changes (EAPC) for low, intermediate, high and very high-risk were respectively −5.5% (32.4%–24.9%, p < .01), +0.5% (47.6%–48.4%, p = .09), +4.1% (8.2%–9.9%, p < .01), and +8.9% (11.8%–16.9%, p < .01), between 2010 and 2015. After adjustment for number of prostate biopsy cores, differences in rates over time disappeared and ranged from 29.8%–29.7% for low risk, 47.9%–47.9% for intermediate risk, 8.9%–9.0% for high-risk, and 13.6%–13.6% for very high-risk PCa (all p > .05). Conclusions: The rates of high and very high-risk PCa are strongly associated with the number of prostate biopsy cores, that in turn may be driven by broader use magnetic resonance imaging (MRI).
The effect of race/ethnicity on cancer-specific mortality after salvage radical prostatectomy
(2022)
Background: To test the effect of race/ethnicity on cancer-specific mortality (CSM) after salvage radical prostatectomy (SRP).
Material and methods: We relied on the Surveillance, Epidemiology and End Results database (SEER, 2004–2016) to identify SRP patients of all race/ethnicity background. Univariate and multivariate Cox regression models addressed CSM according to race/ethnicity.
Results: Of 426 assessable SRP patients, Caucasians accounted for 299 (69.9%) vs. 68 (15.9%) African-Americans vs. 39 (9.1%) Hispanics vs. 20 (4.7%) Asians. At diagnosis, African-Americans (64 years) were younger than Caucasians (66 years), but not younger than Hispanics (66 years) and Asians (67 years). PSA at diagnosis was significantly higher in African-Americans (13.2 ng/ml), Hispanics (13.0 ng/ml), and Asians (12.2 ng/ml) than in Caucasians (7.8 ng/ml, p = 0.01). Moreover, the distribution of African-Americans (10.3%–36.6%) and Hispanics (0%–15.8%) varied according to SEER region. The 10-year CSM was 46.5% in African-Americans vs. 22.4% in Caucasians vs. 15.4% in Hispanics vs. 15.0% in Asians. After multivariate adjustment (for age, clinical T stage, lymph node dissection status), African-American race/ethnicity was an independent predictor of higher CSM (HR: 2.2, p < 0.01), but not Hispanic or Asian race/ethnicity. The independent effect of African-American race/ethnicity did not persist after further adjustment for PSA.
Conclusion: African-Americans treated with SRP are at higher risk of CSM than other racial/ethnic groups and also exhibited the highest baseline PSA. The independent effect of African-American race/ethnicity on higher CSM no longer applies after PSA adjustment since higher PSA represents a distinguishing feature in African-American patients.
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: We hypothesized that lymph node dissection (LND) at salvage radical prostatectomy may be associated with lower cancer-specific mortality (CSM) and we tested this hypothesis.
Methods: We relied on surveillance, epidemiology, and end results (2004–2016) to identify all salvage radical prostatectomy patients. Categorical, as well as univariate and multivariate Cox regression models tested the effect of LND (LND performed vs. not), as well as at its extent (log-transformed lymph node count) on CSM.
Results: Of 427 salvage radical prostatectomy patients, 120 (28.1%) underwent LND with a median lymph node count of 6 (interquartile range [IQR], 3–11). According to LND status, no significant or clinically meaningful differences were recorded in PSA at diagnosis, stage and biopsy Gleason score at diagnosis, except for age at prostate cancer diagnosis (LND performed 63 vs. 68 years LND not performed, p < .001). LND status (performed) was an independent predictor of lower CSM (hazard ratio [HR] 0.47; p = .03). Similarly, lymph node count (log transformed) also independently predicted lower CSM (HR: 0.60; p = .01). After the 7th removed lymph node, the effect of CSM became marginal. The effect of N-stage on CSM could not be tested due to insufficient number of observations.
Conclusions: Salvage radical prostatectomy is rarely performed and LND at salvage radical prostatectomy is performed in a minority of patients. However, LND at salvage radical prostatectomy is associated with lower CSM. Moreover, LND extent also exerts a protective effect on CSM. These observations should be considered in salvage radical prostatectomy candidates.
Purpose: To test the value of preoperative and postoperative cystatin C (CysC) as a predictor on kidney function after partial (PN) or radical nephrectomy (RN) in renal cell carcinoma (RCC) patients with normal preoperative renal function.
Methods: From 01/2011 to 12/2014, 195 consecutive RCC patients with a preoperative estimated glomerular filtration rate (eGFR) > 60 ml/min/1.73m2 underwent surgical RCC treatment with either PN or RN. Logistic and linear regression models tested for the effect of CysC as a predictor of new-onset chronic kidney disease in follow-up (eGFR < 60 ml/min/1.73m2). Moreover, postoperative CysC and creatinine values were compared for kidney function estimation.
Results: Of 195 patients, 129 (66.2%) underwent PN. In postoperative and in follow-up setting (median 14 months, IQR 10–20), rates of eGFR < 60 ml/min/1.73m2 were 55.9 and 30.2%. In multivariable logistic regression models, preoperative CysC [odds ratio (OR): 18.3] and RN (OR: 13.5) were independent predictors for a reduced eGFR < 60 ml/min/1.73m2 in follow-up (both p < 0.01), while creatinine was not. In multivariable linear regression models, a difference of the preoperative CysC level of 0.1 mg/dl estimated an eGFR decline in follow-up of about 5.8 ml/min/1.73m2. Finally, we observed a plateau of postoperative creatinine values in the range of 1.2–1.3 mg/dl, when graphically depicted vs. postoperative CysC values (‘creatinine blind area’).
Conclusion: Preoperative CysC predicts renal function impairment following RCC surgery. Furthermore, CysC might be superior to creatinine for renal function monitoring in the early postoperative setting.
Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77–0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77–0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the “first wave” of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78–0.87]; for full follow-up: 0.82 [95% CI: 0.78–0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.