The goal of prostate cancer focal therapy is to achieve oncologic control while reducing the rate of adverse events associated with whole-gland treatments. Numerous focal therapy modalities are ...currently available with early data demonstrating highly variable rates of cancer control and preservation of sexual/urinary function.
All English language clinical trial publications evaluating various focal therapies for localized prostate cancer were reviewed. The literature search was limited to studies from the modern era of MRI-guided treatment, as MRI is hypothesized to improve tumor localization and targeting. Primary outcomes were post-treatment cancer-free rates, in-field/out-of-field recurrence rates, and rates of conversion to radical therapy. Secondary outcomes were related to functional status and adverse events.
Numerous focal therapies were identified with clinical data including high-intensity focused ultrasound, transurethral ultrasound ablation, focal laser ablation, focal cryotherapy, irreversible electroporation, and photodynamic therapy. Recurrence rates among all technologies were low to moderate (0-51%) and rates of freedom from radical treatment were highly variable (46-98%). Rates of erectile dysfunction and incontinence generally ranged from 0 to 44% and 0 to 12%, respectively, with variability between focal therapy modalities. Caution should be exercised when comparing studies as outcomes are strongly associated with patient selection. No individual focal therapy is currently recommended by society guidelines. Randomized controlled trials are ongoing in search of a standard of care.
For localized MRI-visible prostate cancer, early clinical trial data demonstrate that focal therapy can provide good to moderate cancer control while having preferable side effect profiles compared to whole-gland treatments. While current studies do not make head-to-head comparisons between technologies, early data suggest a potential for these technologies to provide adequate cancer control in a well-selected patient population. The oncologic outcomes of some focal therapies appear promising; however, longer-term follow-up data are needed to assess the durability of early outcomes.
Objectives
To evaluate whether pathological downstaging (pDS) was more informative in predicting overall survival (OS) than pathological complete response (pCR) in patients treated with neoadjuvant ...chemotherapy (NAC) for upper tract urothelial carcinoma (UTUC).
Patients and Methods
The National Cancer Database was queried for patients with high‐grade cN0M0 disease who had received NAC. pDS was defined as a decrease of at least one stage from cT to pT stage along with pN0, including pCR. A multivariable Cox model predicting OS was generated by fitting alternatively either pDS or pCR, and adjusted for potential confounders. The discrimination of the Cox models for predicting OS was evaluated using Harrell's C‐index. The analyses were repeated in patients diagnosed as having cT2–4N0M0 disease.
Results
Among 264 patients meeting the inclusion criteria, 72 (27%) and 39 (15%) achieved pDS and pCR, respectively. On multivariable analysis, both pDS (hazard ratio HR 0.24, 95% confidence interval CI 0.13, 0.45; P < 0.001) and pCR (HR 0.37, 95% CI 0.18, 0.79; P = 0.01) were associated with OS. The model including pDS achieved better discrimination with respect to the model including pCR: C‐index 76.4 vs 72.7, respectively.
In the 128 patients diagnosed with cT2–4 disease, both pDS (HR 0.19, 95% CI 0.09, 0.40; P < 0.001) and pCR (HR 0.31, 95% CI 0.11, 0.85; P = 0.023) were confirmed as predictors of OS. The model including pDS was confirmed to discriminate better than the model including pCR: C‐index 75 vs 68.9, respectively.
Conclusion
The study showed that pDS after NAC for UTUC was more informative than pCR when predicting OS. These findings, although requiring prospective validation, can aid in the design of clinical trials seeking to refine the use of chemotherapy and other systemic therapies in this setting.
To perform a survey assessing the use of, attitudes towards, and perceived utility of social media (SoMe) in the 2021 urology residency match.
We distributed surveys to urology residency applicants ...and program directors (PDs) via the Urology Match 2021 Google Spreadsheet and email. The survey collected demographic information as well as SoMe activity, perceived pressure to use SoMe, match results, and attitudes regarding the utility of SoMe in the match process.
A total of 108/528 (20%) applicants registered for the 2021 match and 61/142 (43%) PDs completed the survey. More applicants than PDs felt that SoMe helped them gain better insight into residency programs or applicants, respectively. Fewer applicants than PDs felt that SoMe activity provided a benefit to them in the match process. No significant relationship was found between SoMe viewing frequency, posting frequency, or tweetorial use with match outcomes. The majority of PDs believed that SoMe played a more important role in the 2021 match process than previous years while 15% and 12% reported that an applicant's SoMe activity helped or hurt the chances of matching to their program respectively.
SoMe, particularly Twitter, was widely used in the 2021 match by both applicants and PDs. A majority of applicants and PDs believed that SoMe use aided them in some way in the match process, yet there was no relationship between the volume or type of applicant SoMe activity and match outcomes.
The purpose of this study was to determine which characteristics of urology residency programs are most highly valued by medical students and residents, and how these change during training.
We ...distributed a survey to urology residents and medical students interested in urology via program director email and social media. The survey collected demographic data, future career plans, and asked respondents to rank the relative importance of six categories of residency program characteristics and specific characteristics within each category.
Among the six categories of residency characteristics, resident experience was ranked most important by both medical students and residents, followed by geography and clinical experience which were tied. Medical students ranked clinic experience and formal mentorship with greater importance while residents placed higher value on the active role of clinical faculty and help from advanced practice providers. Trainees planning for an academic career ranked research experiences and resident diversity as more important than those entering private practice.
Residents and medical students mostly agreed on the relative importance of residency program characteristics. The differences observed suggest that as trainees gain experience they place greater importance on informal relationships with faculty and value characteristics that enhance surgical training such as support from advanced practice providers and less time in clinic. These findings may guide programs on what information to include on their websites and presentations.
Female sexual health and female sexual dysfunction (FSD) are usually poorly diagnosed and treated because of the numerous barriers providers and patients face. Internet platforms, such as mobile ...applications (apps) are potential tools that help overcome these barriers and improve patient access to education and management options for FSD.
The aim of this review was to identify existing applications on female sexual health and evaluate their educational content and services.
We searched the internet and Apple App Store using multiple keywords. A panel of physicians specialized in the treatment of FSD reviewed the apps for content quality, the scientific basis of provided information, interactivity, usability, and whether they would recommend it as a reference tool for patients.
Of the 204 apps identified, 17 met the inclusion criteria and were reviewed further. The selected apps were organized into groups based on common themes such as educational (n = 6), emotions and communication (n = 2), relaxation and meditation (n = 4), general sexual health (n = 2), and social and fun (n = 3). All apps from the educational category provided scientific information in collaboration with health experts. When assessed for usability, 1 app received good and 5 received excellent scores based on the System Usability Scale. Most apps (n = 5) provided information on pathology and treatments of orgasmic dysfunction, but only 1 app, created by a physician, provided comprehensive information on all the types of FSD.
Digital technology could be an effective way to overcome barriers to accessing information and ultimately care for female sexual health. Our review demonstrated that there is still a need for more accessible educational resources addressing female sexual health and FSD for patients and providers.
Purpose: The purpose of this study was to determine the impact of COVID-19 on the urology residency application cycle on social media engagement and account creation by urology residency programs and ...applicants. Materials and Methods: A list of accredited urology residency programs was taken from the Electronic Residency Application Service, excluding military-sponsored programs. Twitter, Instagram, and Facebook accounts of programs and applicants were then identified through Google and individual platform searches. Results: One hundred and nineteen out of 140 urology programs had Twitter accounts, with 29 created in 2020. Urology program Instagram accounts had the largest growth rate in 2020 of 227.8%. Almost all urology programs that had Instagram or Facebook accounts also had a Twitter account. Urology programs promoted a total of 277 virtual events on Twitter, 83 on Instagram, and 48 on Facebook. Sixteen subinternships were promoted on Twitter, two on Instagram, and two on Facebook. In the 2021 match, 136 of the 237 matched applicants on Twitter made their accounts in the year leading up to the match and 42 of the 162 matched applicants on Twitter created their Twitter accounts during the 2019 cycle. Conclusion: The number of urology programs on Twitter and Instagram increased in 2020 at a faster rate than previous years. Many programs used their accounts to promote virtual events and subinternships. Applicants who matched in 2021 made Twitter accounts during their application year at a higher rate than the previous application cycle. During the COVID-19 pandemic, urology programs and applicants utilized social media, especially Twitter, to engage and learn about each other.
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Background: Artificial Intelligence (AI) in Urology has been used for many conditions including benign prostatic hyperplasia (BPH), urological oncology, and kidney transplant. Many computer ...models use algorithms that may be intricate for urologists to implement, but automated machine learning (AML) can be used to create simple models. Here we expand the use of AI and AML in image detection of kidney tumors, stones, and unremarkable kidney from computed tomography (CT) using Google Vertex AI, a machine learning platform that allows for the building, training, and deployment of models. Methods: Google Vertex AI machine learning system was trained to perform image detection. CT Kidney images were taken from publicly available data from Kaggle, an online database and machine learning platform. Images are from multiple hospitals in Dhaka, Bangladesh. 300 CT Kidney Images were uploaded on Google Vertex AI: 100 tumors, 100 stone, and 100 normal. 240 images were used to train the model, 30 for validation, and a final 30 images for assessing the accuracy of predictions after the training phase. To comprehensively evaluate our model, CT kidney images from the Cedars Sinai Medical Center were employed for further testing. All training images lacked annotations and were solely classified as normal, stone, or tumor. Results: True positivity rate for image detection during model training was 100% for tumors, stones, and normal CTs. We further tested accuracy using Cedars Sinai patient images, using 10 tumors, 10 stones, and 5 normal. The accuracy of the AI prediction was 80%, 70%, and 100%, respectively. Conclusions: Artificial Intelligence can be useful in interpreting urological imaging even in a minimally trained system. A model such as ours may allow for rapid identification and labeling of renal masses, kidney stones, and normal studies with moderate fidelity. Further training of this model may increase accuracy.
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