Urology Practice最新文献

Introduction: Socioeconomic status and geographical location contribute to disparities in localized prostate cancer (PCa) treatment. We examined the impact of Area of Deprivation Index (ADI) on initial treatment type for localized PCa in a North American cohort.

Methods: We performed a retrospective analysis of patients diagnosed with localized PCa treated within the State of Michigan between 2010 and 2022 with available ADI data. The latter was assigned based on the residential census block group, ranked as a national deprivation percentile. Patients were categorized into 3 treatment groups: radical prostatectomy (RP), radiation therapy (RT), and "Other" treatment. Using multinominal logistic regression, we assessed ADI impact on treatment choice. After excluding patients without cT, International Society of Urological Pathology grade, and/or PSA, we stratified by D'Amico risk classification and repeated the regression analysis in each subgroup.

Results: The cohort consisted of 46,481 patients. Among those, 17.7% were non-Hispanic Black men. Regarding treatment, 21,152 (45.51%) patients underwent RP, 9713 (20.89%) received RT, and the remaining 15,616 (33.59%) underwent "Other" treatments. Median (IQR) national ADI percentile was 58 (38-79), and it was 55 (37-76), 62 (41-83), and 59 (38-82) for the patients treated with RP, RT, and Other, respectively (P < .0001). At multivariable analysis, ADI was significantly associated with the type of received treatment. For each 10-unit increase in ADI, patients were 3% more likely to receive RT and 2% less likely to receive an RP, compared with Other treatment (odds ratio [OR], 1.03, 95% CI, 1.02-1.04; P < .001 and OR, 0.98, 95% CI, 0.97-0.99; P < .001, respectively). When stratified by D'Amico risk classification, among patients with known PSA, grade, and stage (25,571 patients), 6976 (27.28%) were low-risk, 12,329 (48.21%) were intermediate-risk, and 6266 (24.50%) were high-risk. At multivariable analysis, for each 10-unit increase in ADI percentile, low-risk patients were 7% more likely to receive RT compared with other treatments (OR, 1.07, 95% CI, 1.04-1.10; P < .001). Although among intermediate-risk and high-risk patients with PCa, each 10-unit increase in ADI was associated with 4% and 6% decreased likelihood of receiving RP, respectively, compared with other treatments (OR, 0.96, 95% CI, 0.95-0.98; P = .001 and OR, 0.94, 95% CI, 0.91-0.97; P <.001).

Conclusions: Patients living in developed areas were more likely to receive RP, while those living in the most disadvantaged areas received higher rates of RT. Understanding neighborhood influence on initial localized PCa treatment is essential in guiding interventions and reducing disparities.

Introduction: Patients with penile cancer may be particularly vulnerable to depression, anxiety, and social isolation, yet population-level data on mental health outcomes are limited. We investigated the incidence and predictors of mental health disease (MHD) after penile cancer diagnosis and treatment using nationally representative data sets.

Methods: We conducted a retrospective analysis of the deidentified MarketScan Commercial Claims (MCCD) and Medicare supplemental (MSD) databases (2009-2023). Eligible patients were 18 years or older with a confirmed penile cancer. Those with preexisting MHD were excluded. Treatments were categorized as radical (radical penectomy/perineal urethrostomy), partial (partial penectomy), topical (imiquimod/5-fluorouracil), or local excision. The primary outcome was new-onset MHD (major depressive disorder or generalized anxiety disorder) within 36 months. Multivariable Cox models identified predictors.

Results: Among 1633 patients (1044 MCCD; 589 MSD), 151 (14.5%) and 83 (14.1%) developed MHD, respectively. In MCCD, radical penectomy (HR 3.33, 95% CI 1.72-6.47, P < .001), Charlson Comorbidity Index (CCI) 2 (HR 1.74, 95% CI 1.03-2.96, P = .040), and CCI 3+ (HR 2.45, 95% CI 1.54-3.91, P < .001) predicted increased MHD risk compared with local excision and a CCI of 0, respectively, while age in the third quartile was protective (HR 0.47, 95% CI 0.30-0.75, P = .001). These variables did not significantly correlate with MHD in the MSD cohort.

Conclusions: Patients with penile cancer face high rates of MHD, particularly after radical surgery, in the presence of comorbidities. This relationship appeared to differ between MSD and MCCD cohorts. Survivorship models should integrate timely mental health support and address access disparities.

Introduction: Missed outpatient appointments, or no-shows, decrease clinic efficiency and are a major challenge in delivering high-quality, cost-effective care. Given the ubiquity of smartphones, automated text reminders are an attractive tool to promote appointment adherence. Thus, our study aims to describe the prevalence and predictors of pediatric urology clinic appointment no-shows and the effectiveness of an automated text reminder system.

Methods: We surveyed all in-person and telehealth pediatric urology clinic appointments within our institution's health system from January to December 2023. Ethnicity, native language, need for interpreter, clinic site, visit type, appointment time, and insurance type were measured. The primary outcome was appointment no-show rate. Secondary outcomes were appointment cancellation and rescheduling rates. Odds for no-show, cancellation, and rescheduling were compared between the preintervention and postintervention groups. A univariate and multinomial logistic regression model was used with attended visits as the reference for the outcome.

Results: A total of 15,315 outpatient urology clinic appointments were scheduled; 60.0% attended, 24.1% rescheduled, 9.4% cancelled, and 6.5% missed/no-show. Implementation of text reminders was associated with more visit cancellations (odds ratio [OR] 1.20 [1.01-1.42]), but fewer rescheduled visits (OR 0.78 [0.70-0.86]) and no-shows (OR 0.72 [0.60-0.85]). Spanish language, follow-up visits, and nurse visits were less likely to no-show (OR 0.66 [0.54-0.79], 0.80 [0.68-0.93], and 0.15 [0.06-0.37], respectively). Patients with public-payer insurance or appointments before 10:00 am had a higher odds of no-show (OR 3.38 [1.95-5.86] and 1.25 [1.04-1.51], respectively).

Conclusions: An automated text reminder system is effective in reducing no-show rates for pediatric urology clinic appointments in an academic tertiary care setting.

Introduction: Postvasectomy pain syndrome (PVPS) is a poorly understood, chronic condition affecting up to 5% of men post vasectomy. With limited evidence guiding its management, vasectomy reversal (VR) has been referenced as a potential treatment modality. This systematic review evaluates the current literature on the efficacy of VR in relieving PVPS symptoms.

Methods: A systematic search was conducted across PubMed, ScienceDirect, SCOPUS, and Web of Science databases in accordance with preferred peporting items for systematic reviews and meta-analyses 2020 guidelines. Eligible studies included case series and clinical reports from the last 15 years that assessed pain outcomes after VR in men diagnosed with PVPS. Primary outcomes included pain resolution or reduction postoperatively, measured through visual analogue pain scores or patient-reported outcomes.

Results: Five studies involving 123 patients were included, encompassing vasovasostomy, vasoepididymostomy, and robotic-assisted techniques. All studies reported symptomatic improvement after VR, with pain score reductions ranging from 60% to 83%. While 2 studies used validated pain scoring systems before intervention and post intervention, the remaining studies reported other subjective or percentage-based improvements. Across all studies, VR was associated with high rates of patient satisfaction and willingness to undergo the procedure again.

Conclusions: VR seems to offer meaningful pain relief in patients suffering from PVPS. However, further high-quality prospective studies and randomized controlled trials are needed to concretely establish its efficacy, compare it with alternative treatments, and develop standardized treatment algorithms.