Basourakos, Spyridon P.

Prostate cancer lung metastasis represents a clinical conundrum due to its implications for advanced disease progression and the complexities it introduces in treatment planning. As the disease progresses to distant sites such as the lung, the clinical management becomes increasingly intricate, requiring tailored therapeutic strategies to address the unique characteristics of metastatic lesions. This review seeks to synthesize the current state of knowledge surrounding prostate cancer metastasis to the lung, shedding light on the diverse array of clinical presentations encountered, ranging from subtle radiological findings to overt symptomatic manifestations. By examining the diagnostic modalities utilized in identifying this metastasis, including advanced imaging techniques and histopathological analyses, this review aims to provide insights into the diagnostic landscape and the challenges associated with accurately characterizing lung metastatic lesions in prostate cancer patients. Moreover, this review delves into the nuances of therapeutic interventions employed in managing prostate cancer lung metastasis, encompassing systemic treatments such as hormonal therapies and chemotherapy, as well as metastasis-directed therapies including surgery and radiotherapy.

695 Background: Small cell carcinoma of the bladder (SCCB) is a rare variant of bladder cancer with limited data informing prognosis. We present a novel prognostic model for disease specific survival (DSS) for patients with non-metastatic (M0) SCCB, derived from the Surveillance, Epidemiology and End Results (SEER) database. Methods: The SEER database (18 registries/November 2020) was queried with the ICD-10 topography codes C67.0-C67.9 (bladder), and the morphologic code 8041 (SCCB). Eligible patients (adults, histologic confirmation, available follow-up/staging data, M0) were randomly divided into a training (TC) and a validation cohort (VC) (7:3 ratio). Variables significantly associated with DSS were identified with multivariate Cox regression and backwards stepwise conditional approach and inserted in the model. Points were assigned to each variable based on the formula: Probability of an event at time t=S0(t)exp(β1x1, β2x2...), (β = regression coefficients, x = observed covariate values, S0(t) = survival function). Cumulative risk points were assigned to each patient and three distinct risk categories for DSS were constructed. Harrel’s C-statistic with bootstrap resampling was used for internal (TC) and external (VC) validation. Model performance was compared to the AJCC 8th edition (likelihood ratio test -LRT). Results: A total of 1039 patients were included (739 TC, 300 VC). No statistically significant differences in baseline characteristics/survival outcomes were identified between TC and VC. Age (years), T/N stage, radical cystectomy, chemotherapy, and radiation were significant variables inserted in the multivariate model (table). Patients were stratified to three risk groups (low, intermediate, high) based on the total cumulative risk points collected. Median DSS was NR (95%CI; NR, NR), 25 (95% CI; 18-32) and 9 months (95% CI; 7-11) for the low, intermediate, and high-risk category, log-rank p<.001. Harrel's C-statistic for the model was 0.70 (95%CI;0.67-0.73) in the TC and 0.66 (95%CI; 0.61-0.71) in the VC. In comparison, C-statistic for the AJCC 8th edition was 0.56 (95% CI; 0.52-0.59) and 0.53 (95% CI; 0.51 to 0.57), respectively. The LRT demonstrated superior performance of the model compared to AJCC (p<.001). Conclusions: We present a novel prognostic model for DSS in patients with locoregional SCCB composed of variables readily available in daily practice, which may serve as a useful tool for individualized risk assessment of patients with this rare malignancy. Further validation in prospective studies/clinical trials is warranted. [Table: see text]

Abstract Background Despite many available treatments for Peyronie's disease (PD), practice patterns of available therapeutics are not well characterized. Objective We conducted a national survey of urologists to characterize real‐world practice patterns of PD management and to characterize the use of therapies discouraged by the American Urological Association guidelines on PD management. Materials and methods A 34‐item survey was distributed via RedCap to urologists who treat patients with PD in all American Urological Association sections. Questions elicited demographic information as well as practices in the diagnosis and treatment of PD. Comparisons were made with Pearson's chi‐squared test. The primary outcome was reported use of therapies discouraged by the American Urological Association guidelines on PD. Results A total of 145 respondents completed the survey, of whom 19% were fellowship trained in andrology/sexual medicine, 36% practiced in an academic setting, and 50% had at least 20 years in practice. Only 60% of respondents reporting performing in‐office curvature assessment prior to commencing intralesional injection or surgical treatment, with higher prevalence in andrology/sexual medicine fellowship‐trained versus non‐fellowship‐trained urologists (85% vs. 54%, p = 0.003). The most popular treatment modalities were collagenase clostridium histolyticum (61% of respondents), phosphodiesterase‐5 inhibitors (54%), and penile traction (53%). Twenty‐one percent of respondents reported currently using a treatment that is explicitly discouraged by the American Urological Association guidelines (extracorporeal shockwave therapy for curvature, L‐carnitine, omega‐3 fatty acids, or vitamin E). Discussion Patients seeking PD treatment may be offered different therapies, some of which are not evidence‐based, depending on the treating urologist. This study is limited by self‐selection and response bias. Its strength is that it represents a cross‐sectional overview of real‐world practice patterns in PD management, which has not been previously described. Conclusions A significant proportion of urologists reported PD management practices that are not evidence‐based and not guideline‐supported.