Salvage treatments after focal therapy for prostate cancer - a comprehensive review.

OBJECTIVE: To review the literature on salvage treatments after focal therapy (FT) for prostate cancer (PCa). MATERIALS AND METHODS: A non-systematic literature review was conducted on PubMed, Scopus, and Web of Science up to March 15, 2024, for studies that assessed salvage treatment outcomes in patients with recurrent PCa after primary FT. Original prospective and retrospective studies with more than 10 patients were included. Reviews, editorial comments, conference abstracts, and studies focusing solely on whole-gland treatments were excluded. RESULTS: Twenty-one studies with a total of 1012 patients were included. The most reported salvage treatments were salvage radical prostatectomy followed by re-do ablation therapy. Only one study evaluated salvage radiation therapy. Except for one prospective study, all studies were retrospective. Oncological outcomes showed acceptable biochemical recurrence rates. Functional outcomes varied, with significant impacts observed on erectile function across modalities, though continence rates were less impacted. Complications were generally low across all treatment options. CONCLUSION: Salvage treatment post-primary FT is feasible, safe, and has reasonable oncologic outcomes. However, significant declines in sexual function are common, while continence is comparatively less affected. The literature primarily consists of retrospective studies; hence, future research should focus on large-scale prospective evaluations to better define treatment protocols and improve patient outcomes.

Transperineal versus Transrectal MRI/TRUS fusion-guided prostate biopsy in a large, ethnically diverse, and multiracial cohort.

PURPOSE: To compare transperineal (TP) vs transrectal (TR) magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) fusion-guided prostate biopsy (PBx) in a large, ethnically diverse and multiracial cohort. MATERIALS AND METHODS: Consecutive patients who underwent multiparametric (mp) MRI followed by TP or TR TRUS-fusion guided PBx, were identified from a prospective database (IRB #HS-13-00663). All patients underwent mpMRI followed by 12-14 core systematic PBx. A minimum of two additional target-biopsy cores were taken per PIRADS≥3 lesion. The endpoint was the detection of clinically significant prostate cancer (CSPCa; Grade Group, GG≥2). Statistical significance was defined as p<0.05. RESULTS: A total of 1491 patients met inclusion criteria, with 480 undergoing TP and 1011 TR PBx. Overall, 11% of patients were Asians, 5% African Americans, 14% Hispanic, 14% Others, and 56% White, similar between TP and TR (p=0.4). For PIRADS 3-5, the TP PBx CSPCa detection was significantly higher (61% vs 54%, p=0.03) than TR PBx, but not for PIRADS 1-2 (13% vs 13%, p=1.0). After adjusting for confounders on multivariable analysis, Black race, but not the PBx approach (TP vs TR), was an independent predictor of CSPCa detection. The median maximum cancer core length (11 vs 8mm; p<0.001) and percent (80% vs 60%; p<0.001) were greater for TP PBx even after adjusting for confounders. CONCLUSIONS: In a large and diverse cohort, Black race, but not the biopsy approach, was an independent predictor for CSPCa detection. TP and TR PBx yielded similar CSPCa detection rates; however the TP PBx was histologically more informative.

Generative AI Platform for Automating Social Media Posts From Urology Journal Articles: A Cross-Sectional Study and Randomized Assessment.

PURPOSE: This cross-sectional study assessed a generative-AI platform to automate the creation of accurate, appropriate, and compelling social-media (SoMe) posts from urological journal articles. MATERIALS AND METHODS: One hundred SoMe-posts from the top 3 journals in urology X (Twitter) profiles were collected from Aug-2022 to Oct-2023 A freeware GPT-tool was developed to auto-generate SoMe posts, which included title-summarization, key findings, pertinent emojis, hashtags, and DOI links to the article. Three physicians independently evaluated GPT-generated posts for achieving tetrafecta of accuracy and appropriateness criteria. Fifteen scenarios were created from 5 randomly selected posts from each journal. Each scenario contained both the original and the GPT-generated post for the same article. Five questions were formulated to investigate the posts' likability, shareability, engagement, understandability, and comprehensiveness. The paired posts were then randomized and presented to blinded academic authors and general public through Amazon Mechanical Turk (AMT) responders for preference evaluation. RESULTS: Median (IQR) time for post auto-generation was 10.2 seconds (8.5-12.5). Of the 150 rated GPT-generated posts, 115 (76.6%) met the correctness tetrafecta: 144 (96%) accurately summarized the title, 147 (98%) accurately presented the articles' main findings, 131 (87.3%) appropriately used emojis and hashtags 138 (92%). A total of 258 academic urologists and 493 AMT responders answered the surveys, wherein the GPT-generated posts consistently outperformed the original journals' posts for both academicians and AMT responders (P < .05). CONCLUSIONS: Generative-AI can automate the creation of SoMe posts from urology journal abstracts that are both accurate and preferable by the academic community and general public.

Stockholm3 in a Multiethnic Cohort for Prostate Cancer Detection (SEPTA): A Prospective Multicentered Trial.

PURPOSE: Asian, Black, and Hispanic men are underrepresented in prostate cancer (PCa) clinical trials. Few novel prostate cancer biomarkers have been validated in diverse cohorts. We aimed to determine if Stockholm3 can improve prostate cancer detection in a diverse cohort. METHODS: An observational prospective multicentered (17 sites) clinical trial (2019-2023), supplemented by prospectively recruited participants (2008-2020) in a urology clinic setting included men with suspicion of PCa and underwent prostate biopsy. Before biopsy, sample was collected for measurement of the Stockholm3 risk score. Parameters include prostate-specific antigen (PSA), free PSA, KLK2, GDF15, PSP94, germline risk (single-nucleotide polymorphisms), age, family history, and previous negative biopsy. The primary endpoint was detection of International Society of Urological Pathology (ISUP) Grade ≥2 cancer (clinically significant PCa, csPC). The two primary aims were to (1) demonstrate noninferior sensitivity (0.8 lower bound 95% CI noninferiority margin) in detecting csPC using Stockholm3 compared with PSA (relative sensitivity) and (2) demonstrate superior specificity by reducing biopsies with benign results or low-grade cancers (relative specificity). RESULTS: A total of 2,129 biopsied participants were included: Asian (16%, 350), Black or African American (Black; 24%, 505), Hispanic or Latino and White (Hispanic; 14%, 305), and non-Hispanic or non-Latino and White (White; 46%, 969). Overall, Stockholm3 showed noninferior sensitivity compared with PSA ≥4 ng/mL (relative sensitivity: 0.95 [95% CI, 0.92 to 0.99]) and nearly three times higher specificity (relative specificity: 2.91 [95% CI, 2.63 to 3.22]). Results were consistent across racial and ethnic subgroups: noninferior sensitivity (0.91-0.98) and superior specificity (2.51-4.70). Compared with PSA, Stockholm3 could reduce benign and ISUP 1 biopsies by 45% overall and between 42% and 52% across racial and ethnic subgroups. CONCLUSION: In a substantially diverse population, Stockholm3 significantly reduces unnecessary prostate biopsies while maintaining a similar sensitivity to PSA in detecting csPC.

Readability Assessment of Patient Education Materials on Uro-oncological Diseases Using Automated Measures.

BACKGROUND AND OBJECTIVE: Readability of patient education materials is of utmost importance to ensure understandability and dissemination of health care information in uro-oncology. We aimed to investigate the readability of the official patient education materials of the European Association of Urology (EAU) and American Urology Association (AUA). METHODS: Patient education materials for prostate, bladder, kidney, testicular, penile, and urethral cancers were retrieved from the respective organizations. Readability was assessed via the WebFX online tool for Flesch Kincaid Reading Ease Score (FRES) and for reading grade levels by Flesch Kincaid Grade Level (FKGL), Gunning Fog Score (GFS), Smog Index (SI), Coleman Liau Index (CLI), and Automated Readability Index (ARI). Layperson readability was defined as a FRES of ≥70 and with the other readability indexes <7 according to European Union recommendations. This study assessed only objective readability and no other metrics such as understandability. KEY FINDINGS AND LIMITATIONS: Most patient education materials failed to meet the recommended threshold for laypersons. The mean readability for EAU patient education material was as follows: FRES 50.9 (standard error [SE]: 3.0), and FKGL, GFS, SI, CLI, and ARI all with scores ≥7. The mean readability for AUA patient material was as follows: FRES 64.0 (SE: 1.4), with all of FKGL, GFS, SI, and ARI scoring ≥7 readability. Only 13 out of 70 (18.6%) patient education materials' paragraphs met the readability requirements. The mean readability for bladder cancer patient education materials was the lowest, with a FRES of 36.7 (SE: 4.1). CONCLUSIONS AND CLINICAL IMPLICATIONS: Patient education materials from leading urological associations reveal readability levels beyond the recommended thresholds for laypersons and may not be understood easily by patients. There is a future need for more patient-friendly reading materials. PATIENT SUMMARY: This study checked whether health information about different cancers was easy to read. Most of it was too hard for patients to understand.

A nomogram to predict the absence of clinically significant prostate cancer in males with negative MRI

ABSTRACT Purpose: To create a nomogram to predict the absence of clinically significant prostate cancer (CSPCa) in males with non-suspicion multiparametric magnetic resonance imaging (mpMRI) undergoing prostate biopsy (PBx). Materials and Methods: We identified consecutive patients who underwent 3T mpMRI followed by PBx for suspicion of PCa or surveillance follow-up. All patients had Prostate Imaging Reporting and Data System score 1-2 (negative mpMRI). CSPCa was defined as Grade Group ≥2. Multivariate logistic regression analysis was performed via backward elimination. Discrimination was evaluated with area under the receiver operating characteristic (AUROC). Internal validation with 1,000x bootstrapping for estimating the optimism corrected AUROC. Results: Total 327 patients met inclusion criteria. The median (IQR) age and PSA density (PSAD) were 64 years (58-70) and 0.10 ng/mL2 (0.07-0.15), respectively. Biopsy history was as follows: 117 (36%) males were PBx-naive, 130 (40%) had previous negative PBx and 80 (24%) had previous positive PBx. The majority were White (65%); 6% of males self-reported Black. Overall, 44 (13%) patients were diagnosed with CSPCa on PBx. Black race, history of previous negative PBx and PSAD ≥0.15ng/mL2 were independent predictors for CSPCa on PBx and were included in the nomogram. The AUROC of the nomogram was 0.78 and the optimism corrected AUROC was 0.75. Conclusions: Our nomogram facilitates evaluating individual probability of CSPCa on PBx in males with PIRADS 1-2 mpMRI and may be used to identify those in whom PBx may be safely avoided. Black males have increased risk of CSPCa on PBx, even in the setting of PIRADS 1-2 mpMRI

PCa-RadHop: A transparent and lightweight feed-forward method for clinically significant prostate cancer segmentation.

Prostate Cancer is one of the most frequently occurring cancers in men, with a low survival rate if not early diagnosed. PI-RADS reading has a high false positive rate, thus increasing the diagnostic incurred costs and patient discomfort. Deep learning (DL) models achieve a high segmentation performance, although require a large model size and complexity. Also, DL models lack of feature interpretability and are perceived as "black-boxes" in the medical field. PCa-RadHop pipeline is proposed in this work, aiming to provide a more transparent feature extraction process using a linear model. It adopts the recently introduced Green Learning (GL) paradigm, which offers a small model size and low complexity. PCa-RadHop consists of two stages: Stage-1 extracts data-driven radiomics features from the bi-parametric Magnetic Resonance Imaging (bp-MRI) input and predicts an initial heatmap. To reduce the false positive rate, a subsequent stage-2 is introduced to refine the predictions by including more contextual information and radiomics features from each already detected Region of Interest (ROI). Experiments on the largest publicly available dataset, PI-CAI, show a competitive performance standing of the proposed method among other deep DL models, achieving an area under the curve (AUC) of 0.807 among a cohort of 1,000 patients. Moreover, PCa-RadHop maintains orders of magnitude smaller model size and complexity.

Accuracy, readability, and understandability of large language models for prostate cancer information to the public.

BACKGROUND: Generative Pretrained Model (GPT) chatbots have gained popularity since the public release of ChatGPT. Studies have evaluated the ability of different GPT models to provide information about medical conditions. To date, no study has assessed the quality of ChatGPT outputs to prostate cancer related questions from both the physician and public perspective while optimizing outputs for patient consumption. METHODS: Nine prostate cancer-related questions, identified through Google Trends (Global), were categorized into diagnosis, treatment, and postoperative follow-up. These questions were processed using ChatGPT 3.5, and the responses were recorded. Subsequently, these responses were re-inputted into ChatGPT to create simplified summaries understandable at a sixth-grade level. Readability of both the original ChatGPT responses and the layperson summaries was evaluated using validated readability tools. A survey was conducted among urology providers (urologists and urologists in training) to rate the original ChatGPT responses for accuracy, completeness, and clarity using a 5-point Likert scale. Furthermore, two independent reviewers evaluated the layperson summaries on correctness trifecta: accuracy, completeness, and decision-making sufficiency. Public assessment of the simplified summaries' clarity and understandability was carried out through Amazon Mechanical Turk (MTurk). Participants rated the clarity and demonstrated their understanding through a multiple-choice question. RESULTS: GPT-generated output was deemed correct by 71.7% to 94.3% of raters (36 urologists, 17 urology residents) across 9 scenarios. GPT-generated simplified layperson summaries of this output was rated as accurate in 8 of 9 (88.9%) scenarios and sufficient for a patient to make a decision in 8 of 9 (88.9%) scenarios. Mean readability of layperson summaries was higher than original GPT outputs ([original ChatGPT v. simplified ChatGPT, mean (SD), p-value] Flesch Reading Ease: 36.5(9.1) v. 70.2(11.2), <0.0001; Gunning Fog: 15.8(1.7) v. 9.5(2.0), p < 0.0001; Flesch Grade Level: 12.8(1.2) v. 7.4(1.7), p < 0.0001; Coleman Liau: 13.7(2.1) v. 8.6(2.4), 0.0002; Smog index: 11.8(1.2) v. 6.7(1.8), <0.0001; Automated Readability Index: 13.1(1.4) v. 7.5(2.1), p < 0.0001). MTurk workers (n = 514) rated the layperson summaries as correct (89.5-95.7%) and correctly understood the content (63.0-87.4%). CONCLUSION: GPT shows promise for correct patient education for prostate cancer-related contents, but the technology is not designed for delivering patients information. Prompting the model to respond with accuracy, completeness, clarity and readability may enhance its utility when used for GPT-powered medical chatbots.

Generative artificial intelligence in surgery.

Generative artificial intelligence is able to collect, extract, digest, and generate information in an understandable way for humans. As the first surgical applications of generative artificial intelligence are applied, this perspective paper aims to provide a comprehensive overview of current applications and future perspectives for the application of generative artificial intelligence in surgery, from preoperative planning to training. Generative artificial intelligence can be used before surgery for planning and decision support by extracting patient information and providing patients with information and simulation regarding the procedure. Intraoperatively, generative artificial intelligence can document data that is normally not captured as intraoperative adverse events or provide information to help decision-making. Postoperatively, GAIs can help with patient discharge and follow-up. The ability to provide real-time feedback and store it for later review is an important capability of GAIs. GAI applications are emerging as highly specialized, task-specific tools for tasks such as data extraction, synthesis, presentation, and communication within the realm of surgery. GAIs have the potential to play a pivotal role in facilitating interaction between surgeons and artificial intelligence.

Study protocol for the Intraoperative Complications Assessment and Reporting with Universal Standards (ICARUS) global cross-specialty surveys and consensus.

Annually, about 300 million surgeries lead to significant intraoperative adverse events (iAEs), impacting patients and surgeons. Their full extent is underestimated due to flawed assessment and reporting methods. Inconsistent adoption of new grading systems and a lack of standardization, along with litigation concerns, contribute to underreporting. Only half of relevant journals provide guidelines on reporting these events, with a lack of standards in surgical literature. To address these issues, the Intraoperative Complications Assessment and Reporting with Universal Standard (ICARUS) Global Surgical Collaboration was established in 2022. The initiative involves conducting global surveys and a Delphi consensus to understand the barriers for poor reporting of iAEs, validate shared criteria for reporting, define iAEs according to surgical procedures, evaluate the existing grading systems' reliability, and identify strategies for enhancing the collection, reporting, and management of iAEs. Invitation to participate are extended to all the surgical specialties, interventional cardiology, interventional radiology, OR Staffs and anesthesiology. This effort represents an essential step towards improved patient safety and the well-being of healthcare professionals in the surgical field.

Publishers' and journals' instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis.

OBJECTIVES: To determine the extent and content of academic publishers' and scientific journals' guidance for authors on the use of generative artificial intelligence (GAI). DESIGN: Cross sectional, bibliometric study. SETTING: Websites of academic publishers and scientific journals, screened on 19-20 May 2023, with the search updated on 8-9 October 2023. PARTICIPANTS: Top 100 largest academic publishers and top 100 highly ranked scientific journals, regardless of subject, language, or country of origin. Publishers were identified by the total number of journals in their portfolio, and journals were identified through the Scimago journal rank using the Hirsch index (H index) as an indicator of journal productivity and impact. MAIN OUTCOME MEASURES: The primary outcomes were the content of GAI guidelines listed on the websites of the top 100 academic publishers and scientific journals, and the consistency of guidance between the publishers and their affiliated journals. RESULTS: Among the top 100 largest publishers, 24% provided guidance on the use of GAI, of which 15 (63%) were among the top 25 publishers. Among the top 100 highly ranked journals, 87% provided guidance on GAI. Of the publishers and journals with guidelines, the inclusion of GAI as an author was prohibited in 96% and 98%, respectively. Only one journal (1%) explicitly prohibited the use of GAI in the generation of a manuscript, and two (8%) publishers and 19 (22%) journals indicated that their guidelines exclusively applied to the writing process. When disclosing the use of GAI, 75% of publishers and 43% of journals included specific disclosure criteria. Where to disclose the use of GAI varied, including in the methods or acknowledgments, in the cover letter, or in a new section. Variability was also found in how to access GAI guidelines shared between journals and publishers. GAI guidelines in 12 journals directly conflicted with those developed by the publishers. The guidelines developed by top medical journals were broadly similar to those of academic journals. CONCLUSIONS: Guidelines by some top publishers and journals on the use of GAI by authors are lacking. Among those that provided guidelines, the allowable uses of GAI and how it should be disclosed varied substantially, with this heterogeneity persisting in some instances among affiliated publishers and journals. Lack of standardization places a burden on authors and could limit the effectiveness of the regulations. As GAI continues to grow in popularity, standardized guidelines to protect the integrity of scientific output are needed.

Fiscal analysis of the pediatric immunization program in Belgium applying a lifetime government perspective framework.

OBJECTIVES: A public economic framework was used to explore lifetime government costs and benefits in relation to the Pediatric Immunization Program (PIP) in Belgium based on cases and deaths averted. METHODS: To estimate changes in net government revenue, we developed a decision-analytic model that quantifies lifetime tax revenues and transfers based on changes in morbidity and mortality arising from Belgium's Pediatric Immunization Program (PIP). The model considered differences in incidence rates with vaccines included in Belgium's PIP: compared with the pre-vaccine era. Changes in deaths and comorbid conditions attributed to PIP on the Belgium 2020 birth cohort were used to estimate gross lifetime earnings changes, tax revenue gains attributed to averted morbidity and mortality avoidance, disability transfer cost savings, and averted special education costs associated with each vaccine. RESULTS: Vaccinating a single birth cohort according to the PIP gives rise to fiscal gains of €56 million in averted tax revenue loss, €8 million disability savings, and €6 million special education cost-savings. Based on the costs of implementing the PIP, we estimate the fiscal benefit-cost ratio (fBCR) of €2.2 investment return for the government from every €1 invested excluding longevity costs. CONCLUSIONS: Reducing vaccine-preventable conditions generates tax revenue for the government, providing fiscal justification for sustained immunization investments.

Awareness and Use of ChatGPT and Large Language Models: A Prospective Cross-sectional Global Survey in Urology.

BACKGROUND: Since its release in November 2022, ChatGPT has captivated society and shown potential for various aspects of health care. OBJECTIVE: To investigate potential use of ChatGPT, a large language model (LLM), in urology by gathering opinions from urologists worldwide. DESIGN, SETTING, AND PARTICIPANTS: An open web-based survey was distributed via social media and e-mail chains to urologists between April 20, 2023 and May 5, 2023. Participants were asked to answer questions related to their knowledge and experience with artificial intelligence, as well as their opinions of potential use of ChatGPT/LLMs in research and clinical practice. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Data are reported as the mean and standard deviation for continuous variables, and the frequency and percentage for categorical variables. Charts and tables are used as appropriate, with descriptions of the chart types and the measures used. The data are reported in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). RESULTS AND LIMITATIONS: A total of 456 individuals completed the survey (64% completion rate). Nearly half (47.7%) reported that they use ChatGPT/LLMs in their academic practice, with fewer using the technology in clinical practice (19.8%). More than half (62.2%) believe there are potential ethical concerns when using ChatGPT for scientific or academic writing, and 53% reported that they have experienced limitations when using ChatGPT in academic practice. CONCLUSIONS: Urologists recognise the potential of ChatGPT/LLMs in research but have concerns regarding ethics and patient acceptance. There is a desire for regulations and guidelines to ensure appropriate use. In addition, measures should be taken to establish rules and guidelines to maximise safety and efficiency when using this novel technology. PATIENT SUMMARY: A survey asked 456 urologists from around the world about using an artificial intelligence tool called ChatGPT in their work. Almost half of them use ChatGPT for research, but not many use it for patients care. The resonders think ChatGPT could be helpful, but they worry about problems like ethics and want rules to make sure it's used safely.

Effectiveness of Cognitive Functional Therapy Versus Core Exercises and Manual Therapy in Patients With Chronic Low Back Pain After Spinal Surgery: Randomized Controlled Trial.

OBJECTIVE: Our aim was to investigate whether cognitive functional therapy (CFT) was more effective than core exercises and manual therapy (CORE-MT) in improving pain and function for patients with chronic low back pain after spinal surgery. METHODS: This study was a randomized controlled superiority trial in a university hospital and a private physical therapist clinic in Santa Catarina, Brazil. Eighty participants who were 18 to 75 years old and had chronic low back pain after spinal surgery received 4 to 12 treatment sessions of CFT or CORE-MT once per week for a maximum period of 12 weeks. Primary outcomes were pain intensity (numeric pain rating scale, scored from 0 to 10) and function (Patient-Specific Functional Scale, scored from 0 to 10) after intervention. RESULTS: We obtained primary outcome data for 75 participants (93.7%). CFT was more effective, with a large effect size, than CORE-MT in reducing pain intensity (mean difference [MD] = 2.42; 95% CI = 1.69-3.14; effect size [d] = 0.85) and improving function (MD = -2.47; 95% CI = -3.08 to -1.87; effect size = 0.95) after intervention (mean = 10.4 weeks [standard deviation = 2.17] after the beginning of treatment). The differences were maintained at 22 weeks for pain intensity (MD = 1.64; 95% CI = 0.98-2.3; effect size = 0.68) and function (MD = -2.01; 95% CI = -2.6 to -1.41; effect size = 0.81). CONCLUSION: CFT was more effective than CORE-MT, with large effect sizes, and may be an option for patients with chronic low back pain after spinal surgery. IMPACT: CFT reduces pain and improves function, with large effect sizes, compared with CORE-MT. The difference between CFT and CORE-MT was sustained at the midterm follow-up. Treatment with CFT may be an option for patients with chronic low back pain after spinal surgery.

A nomogram to predict the absence of clinically significant prostate cancer in males with negative MRI

PURPOSE: To create a nomogram to predict the absence of clinically significant prostate cancer (CSPCa) in males with non-suspicion multiparametric magnetic resonance imaging (mpMRI) undergoing prostate biopsy (PBx). MATERIALS AND METHODS: We identified consecutive patients who underwent 3T mpMRI followed by PBx for suspicion of PCa or surveillance follow-up. All patients had Prostate Imaging Reporting and Data System score 1-2 (negative mpMRI). CSPCa was defined as Grade Group ≥2. Multivariate logistic regression analysis was performed via backward elimination. Discrimination was evaluated with area under the receiver operating characteristic (AUROC). Internal validation with 1,000x bootstrapping for estimating the optimism corrected AUROC. RESULTS: Total 327 patients met inclusion criteria. The median (IQR) age and PSA density (PSAD) were 64 years (58-70) and 0.10 ng/mL2 (0.07-0.15), respectively. Biopsy history was as follows: 117 (36%) males were PBx-naive, 130 (40%) had previous negative PBx and 80 (24%) had previous positive PBx. The majority were White (65%); 6% of males self-reported Black. Overall, 44 (13%) patients were diagnosed with CSPCa on PBx. Black race, history of previous negative PBx and PSAD ≥0.15ng/mL2 were independent predictors for CSPCa on PBx and were included in the nomogram. The AUROC of the nomogram was 0.78 and the optimism corrected AUROC was 0.75. CONCLUSIONS: Our nomogram facilitates evaluating individual probability of CSPCa on PBx in males with PIRADS 1-2 mpMRI and may be used to identify those in whom PBx may be safely avoided. Black males have increased risk of CSPCa on PBx, even in the setting of PIRADS 1-2 mpMRI.

The Impact of Telemedicine in Reducing the Carbon Footprint in Health Care: A Systematic Review and Cumulative Analysis of 68 Million Clinical Consultations.

CONTEXT: Carbon footprint (CF) has emerged as an important factor when assessing health care interventions. OBJECTIVE: To investigate the reduction in CF for patients utilizing telemedicine. EVIDENCE ACQUISITION: The PubMed, Scopus, and Web of Science databases were queried for studies describing telemedicine consultation and reporting on carbon emissions saved and the carbon emissions of telemedicine devices as primary outcomes, and travel distance and time and cost savings and safety as secondary outcomes. Outcomes were tabulated and calculated per consultation. Carbon emissions and travel distances were also calculated for each total study cohort. Risk of bias was assessed using the Newcastle-Ottawa scale, and the Oxford level of evidence was determined. EVIDENCE SYNTHESIS: A total of 48 studies met the inclusion criteria, covering 68 465 481 telemedicine consultations and savings of 691 825 tons of CO2 emissions and 3 318 464 047 km of travel distance. Carbon assessment was mostly reported as the estimated distance saved using a conversion factor. Medical specialties used telemedicine to connect specialists with patients at home (n = 25) or at a local center (n = 6). Surgical specialties used telemedicine for virtual preoperative assessment (n = 9), follow-up (n = 4), and general consultation (n = 4). The savings per consultation were 21.9-632.17 min and $1.85-$325. More studies focused on the COVID-19 time frame (n = 33) than before the pandemic (n = 15). The studies are limited by calculations, mostly for the travel distance for carbon savings, and appropriate follow-up to analyze the real impact on travel and appointments. CONCLUSIONS: Telemedicine reduces the CF of the health care sector. Expanding the use of telemedicine and educating providers and patients could further decrease CO2 emissions and save both money and time. PATIENT SUMMARY: We reviewed 48 studies on the use of telemedicine. We found that people used their cars less and saved time and money, as well as CO2 emissions, if they used teleconsultations. Some studies only looked at how much CO2 from driving was saved, so there might be more to learn about the benefits of teleconsultations. The use of online doctor appointments is not only good for our planet but also helps patients in saving time and money. This review is registered on the PROSPERO database for systematic reviews (CRD42023456839).

Impact of persistent PSA after salvage radical prostatectomy: a multicenter study.

BACKGROUND AND OBJECTIVE: Persistent prostatic specific antigen (PSA) represents a poor prognostic factor for recurrence after radical prostatectomy (RP). However, the impact of persistent PSA on oncologic outcomes in patients undergoing salvage RP is unknown. To investigate the impact of persistent PSA after salvage RP on long-term oncologic outcomes. MATERIAL AND METHODS: Patients who underwent salvage RP for recurrent prostate cancer between 2000 and 2021 were identified from twelve high-volume centers. Only patients with available PSA after salvage RP were included. Kaplan-Meier analyses and multivariable Cox regression models were used to test the effect of persistent PSA on biochemical recurrence (BCR), metastasis and any death after salvage RP. Persistent PSA was defined as a PSA-value ≥ 0.1 ng/ml, at first PSA-measurement after salvage RP. RESULTS: Overall, 580 patients were identified. Of those, 42% (n = 242) harbored persistent PSA. Median follow-up after salvage RP was 38 months, median time to salvage RP was 64 months and median time to first PSA after salvage RP was 2.2 months. At 84 months after salvage RP, BCR-free, metastasis-free, and overall survival was 6.6 vs. 59%, 71 vs. 88% and 77 vs. 94% for patients with persistent vs. undetectable PSA after salvage RP (all p < 0.01). In multivariable Cox models persistent PSA was an independent predictor for BCR (HR: 5.47, p < 0.001) and death (HR: 3.07, p < 0.01). CONCLUSION: Persistent PSA is common after salvage RP and represents an independent predictor for worse oncologic outcomes. Patients undergoing salvage RP should be closely monitored after surgery to identify those with persistent PSA.