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Background: This study aims to test the effect of the 10 most common nonurological primary cancers (skin, rectal, colon, lymphoma, leukemia, pancreas, stomach, esophagus, liver, lung) on overall mortality (OM) after secondary prostate cancer (PCa). Material and Methods: Within the Surveillance, Epidemiology, and End Results (SEER) database, patients with 10 most common primary cancers and concomitant secondary PCa (diagnosed 2004–2016) were identified and were matched in 1:4 fashion (age, year at diagnosis, race/ethnicity, treatment type, TNM stage) with primary PCa controls. OM was compared between secondary and primary PCa patients and was stratified according to primary cancer type, as well as according to time interval between primary cancer vs. secondary PCa diagnoses. Results: We identified 24,848 secondary PCa patients (skin, n = 3,871; rectal, n = 798; colon, n = 3,665; lymphoma, n = 2,583; leukemia, n = 1,102; pancreatic, n = 118; stomach, n = 361; esophagus, n = 219; liver, n = 160; lung, n = 1,328) vs. 531,732 primary PCa patients. Secondary PCa characteristics were less favorable than those of primary PCa patients (PSA and grade), and smaller proportions of secondary PCa patients received active treatment. After 1:4 matching, all secondary PCa exhibited worse OM than primary PCa patients. Finally, subgroup analyses showed that the survival disadvantage of secondary PCa patients decreased with longer time interval since primary cancer diagnosis and subsequent secondary PCa. Conclusion: Patients with secondary PCa are diagnosed with less favorable PSA and grade. Even after matching for PCa characteristics, secondary PCa patients still exhibit worse survival. However, the survival disadvantage is attenuated, when secondary PCa diagnosis is made after longer time interval, since primary cancer diagnosis.
Background: To test for differences in cancer-specific mortality (CSM) rates between radical prostatectomy (RP) vs external beam radiotherapy (EBRT) in National Comprehensive Cancer Network (NCCN) high-risk African American patients, as well as Johns Hopkins University (JHU) high-risk and very high-risk patients.
Materials and methods: Within the Surveillance, Epidemiology, and End Results database (2010–2016), we identified 4165 NCCN high-risk patients, of whom 1944 (46.7%) and 2221 (53.3%) patients qualified for JHU high-risk or very high-risk definitions. Of all 4165 patients, 1390 (33.5%) were treated with RP versus 2775 (66.6%) with EBRT. Cumulative incidence plots and competing risks regression models addressed CSM before and after 1:1 propensity score matching between RP and EBRT NCCN high-risk patients. Subsequently, analyses were repeated separately in JHU high-risk and very high-risk subgroups. Finally, all analyses were repeated after landmark analyses were applied.
Results: In the NCCN high-risk cohort, 5-year CSM rates for RP versus EBRT were 2.4 versus 5.2%, yielding a multivariable hazard ratio of 0.50 (95% confidence interval [CI] 0.30–0.84, p = 0.009) favoring RP. In JHU very high-risk patients 5-year CSM rates for RP versus EBRT were 3.7 versus 8.4%, respectively, yielding a multivariable hazard ratio of 0.51 (95% CI: 0.28–0.95, p = 0.03) favoring RP. Conversely, in JHU high-risk patients, no significant CSM difference was recorded between RP vs EBRT (5-year CSM rates: 1.3 vs 1.3%; multivariable hazard ratio: 0.55, 95% CI: 0.16–1.90, p = 0.3). Observations were confirmed in propensity score-matched and landmark analyses adjusted cohorts.
Conclusions: In JHU very high-risk African American patients, RP may hold a CSM advantage over EBRT, but not in JHU high-risk African American patients.
Background: The survival benefit of primary external beam radiation therapy (EBRT) has never been formally tested in elderly men who were newly diagnosed with metastatic prostate cancer (mPCa). We hypothesized that elderly patients may not benefit of EBRT to the extent as younger newly diagnosed mPCa patients, due to shorter life expectancy.
Methods: We relied on Surveillance, Epidemiology and End Results (2004–2016) to identify elderly newly diagnosed mPCa patients, aged >75 years. Kaplan–Meier, univariable and multivariable Cox regression models, as well as Competing Risks Regression models tested the effect of EBRT versus no EBRT on overall mortality (OM) and cancer-specific mortality (CSM).
Results: Of 6556 patients, 1105 received EBRT (16.9%). M1b stage was predominant in both EBRT (n = 823; 74.5%) and no EBRT (n = 3908; 71.7%, p = 0.06) groups, followed by M1c (n = 211; 19.1% vs. n = 1042; 19.1%, p = 1) and M1a (n = 29; 2.6% vs. n = 268; 4.9%, p < 0.01). Median overall survival (OS) was 23 months for EBRT and 23 months for no EBRT (hazard ratio [HR]: 0.97, p = 0.6). Similarly, median cancer-specific survival (CSS) was 29 months for EBRT versus 30 months for no EBRT (HR: 1.04, p = 0.4). After additional multivariable adjustment, EBRT was not associated with lower OM or lower CSM in the entire cohort, as well as after stratification for M1b and M1c substages.
Conclusions: In elderly men who were newly diagnosed with mPCa, EBRT does not affect OS or CSS. In consequence, our findings question the added value of local EBRT in elderly newly diagnosed mPCa patients.
Purpose: To test for differences in cancer-specific mortality (CSM) rates in Hispanic/Latino prostate cancer patients according to treatment type, radical prostatectomy (RP) vs external beam radiotherapy (EBRT).
Methods: Within the Surveillance, Epidemiology, and End Results database (2010–2016), we identified 2290 NCCN (National Comprehensive Cancer Network) high-risk (HR) Hispanic/Latino prostate cancer patients. Of those, 893 (39.0%) were treated with RP vs 1397 (61.0%) with EBRT. First, cumulative incidence plots and competing risks regression models tested for CSM differences after adjustment for other cause mortality (OCM). Second, cumulative incidence plots and competing risks regression models were refitted after 1:1 propensity score matching (according to age, PSA, biopsy Gleason score, cT-stage, cN-stage).
Results: In NCCN HR patients, 5-year CSM rates for RP vs EBRT were 2.4 vs 4.7%, yielding a multivariable hazard ratio of 0.37 (95% CI 0.19–0.73, p = 0.004) favoring RP. However, after propensity score matching, the hazard ratio of 0.54 was no longer statistically significant (95% CI 0.21–1.39, p = 0.2).
Conclusion: Without the use of strictest adjustment for population differences, NCCN high-risk Hispanic/Latino prostate cancer patients appear to benefit more of RP than EBRT. However, after strictest adjustment for baseline patient and tumor characteristics between RP and EBRT cohorts, the apparent CSM benefit of RP is no longer statistically significant. In consequence, in Hispanic/Latino NCCN high-risk patients, either treatment modality results in similar CSM outcome.
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).
Background: The most recent overall survival (OS) and adverse event (AE) data have not been compared for the three guideline-recommended high-risk non-metastatic castration-resistant prostate cancer (nmCRPC) treatment alternatives.
Methods: We performed a systematic review and network meta-analysis focusing on OS and AE according to the most recent apalutamide, enzalutamide, and darolutamide reports. We systematically examined and compared apalutamide vs. enzalutamide vs. darolutamide efficacy and toxicity, relative to ADT according to PRISMA. We relied on PubMed search for most recent reports addressing prospective randomized trials with proven predefined OS benefit, relative to ADT: SPARTAN, PROSPER, and ARAMIS. OS represented the primary outcome and AEs represented secondary outcomes.
Results: Overall, data originated from 4117 observations made within the three trials that were analyzed. Regarding OS benefit relative to ADT, darolutamide ranked first, followed by enzalutamide and apalutamide, in that order. In the subgroup of PSA-doubling time (PSA-DT) ≤ 6 months patients, enzalutamide ranked first, followed by darolutamide and apalutamide in that order. Conversely, in the subgroup of PSA-DT 6–10 months patients, darolutamide ranked first, followed by apalutamide and enzalutamide, in that order. Regarding grade 3+ AEs, darolutamide was most favorable, followed by enzalutamide and apalutamide, in that order.
Conclusion: The current network meta-analysis suggests the highest OS efficacy and lowest grade 3+ toxicity for darolutamide. However, in the PSA-DT ≤ 6 months subgroup, the highest efficacy was recorded for enzalutamide. It is noteworthy that study design, study population, and follow-up duration represent some of the potentially critical differences that distinguish between the three studies and remained statistically unaccounted for using the network meta-analysis methodology. Those differences should be strongly considered in the interpretation of the current and any network meta-analyses.
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 compare Cancer-specific mortality (CSM) in patients with Squamous cell carcinoma (SCC) vs. non-SCC penile cancer, since survival outcomes may differ between histological subtypes. Methods: Within the Surveillance, Epidemiology and End Results database (2004–2016), penile cancer patients of all stages were identified. Temporal trend analyses, cumulative incidence and Kaplan–Meier plots, multivariable Cox regression and Fine and Gray competing-risks regression analyses tested for CSM differences between non-SCC vs. SCC penile cancer patients. Results: Of 4,120 eligible penile cancer patients, 123 (3%) harbored non-SCC vs. 4,027 (97%) SCC. Of all non-SCC patients, 51 (41%) harbored melanomas, 42 (34%) basal cell carcinomas, 10 (8%) adenocarcinomas, eight (6.5%) skin appendage malignancies, six (5%) epithelial cell neoplasms, two (1.5%) neuroendocrine tumors, two (1.5%) lymphomas, two (1.5%) sarcomas. Stage at presentation differed between non-SCC vs. SCC. In temporal trend analyses, non-SCC diagnoses neither decreased nor increased over time (p > 0.05). After stratification according to localized, locally advanced, and metastatic stage, no CSM differences were observed between non-SCC vs. SCC, with 5-year survival rates of 11 vs 11% (p = 0.9) for localized, 33 vs. 37% (p = 0.4) for locally advanced, and 1-year survival rates of 37 vs. 53% (p = 0.9) for metastatic penile cancer, respectively. After propensity score matching for patient and tumor characteristics and additional multivariable adjustment, no CSM differences between non-SCC vs. SCC were observed. Conclusion: Non-SCC penile cancer is rare. Although exceptions exist, on average, non-SCC penile cancer has comparable CSM as SCC penile cancer patients, after stratification for localized, locally invasive, and metastatic disease.
Purpose: To compare Cancer-specific mortality (CSM) in patients with Squamous cell carcinoma (SCC) vs. non-SCC penile cancer, since survival outcomes may differ between histological subtypes. Methods: Within the Surveillance, Epidemiology and End Results database (2004–2016), penile cancer patients of all stages were identified. Temporal trend analyses, cumulative incidence and Kaplan–Meier plots, multivariable Cox regression and Fine and Gray competing-risks regression analyses tested for CSM differences between non-SCC vs. SCC penile cancer patients. Results: Of 4,120 eligible penile cancer patients, 123 (3%) harbored non-SCC vs. 4,027 (97%) SCC. Of all non-SCC patients, 51 (41%) harbored melanomas, 42 (34%) basal cell carcinomas, 10 (8%) adenocarcinomas, eight (6.5%) skin appendage malignancies, six (5%) epithelial cell neoplasms, two (1.5%) neuroendocrine tumors, two (1.5%) lymphomas, two (1.5%) sarcomas. Stage at presentation differed between non-SCC vs. SCC. In temporal trend analyses, non-SCC diagnoses neither decreased nor increased over time (p > 0.05). After stratification according to localized, locally advanced, and metastatic stage, no CSM differences were observed between non-SCC vs. SCC, with 5-year survival rates of 11 vs 11% (p = 0.9) for localized, 33 vs. 37% (p = 0.4) for locally advanced, and 1-year survival rates of 37 vs. 53% (p = 0.9) for metastatic penile cancer, respectively. After propensity score matching for patient and tumor characteristics and additional multivariable adjustment, no CSM differences between non-SCC vs. SCC were observed. Conclusion: Non-SCC penile cancer is rare. Although exceptions exist, on average, non-SCC penile cancer has comparable CSM as SCC penile cancer patients, after stratification for localized, locally invasive, and metastatic disease.