Prognostic significance of EGFR, AREG and EREG amplification and gene expression in muscle invasive bladder cancer.

Introduction: Muscle invasive bladder cancer (MIBC) remains a prevalent cancer with limited therapeutic options, obviating the need for innovative therapies. The epidermal growth factor receptor (EGFR) is a linchpin in tumor progression and presents a potential therapeutic target in MIBC. Additionally, the EGFR ligands AREG and EREG have shown associations with response to anti-EGFR therapy and improved progression-free survival in colorectal carcinoma. Materials and methods: We investigated the prognostic significance of EGFR, AREG, and EREG in MIBC. Gene expression and copy number analyses were performed via qRT-PCR on tissue samples from 100 patients with MIBC who underwent radical cystectomy at the University Hospital Mannheim (MA; median age 72, interquartile range [IQR] 64-78 years, 25% female). Results were validated in 361 patients from the 2017 TCGA MIBC cohort (median age 69, IQR 60-77 years, 27% female), in the Chungbuk and MDACC cohort. Gene expressions were correlated with clinicopathologic parameters using the Mann-Whitney test, Kruskal-Wallis- test and Spearman correlation. For overall survival (OS), cancer-specific survival (CSS) and disease-free survival (DFS) gene expression was analyzed with Kaplan-Meier and Cox-proportional hazard models. Results: Significant gene expression differences in EGFR, AREG, and EREG could be detected in all cohorts. In the TCGA cohort, EGFR expression was significantly elevated in patients with EGFR amplification and KRAS wildtype. High AREG expression independently predicted longer OS (HR = 0.35, CI 0.19 - 0.63, p = 0.0004) and CSS (HR = 0.42, CI 0.18 - 0.95, p = 0.0378) in the MA cohort. In the TCGA cohort, high EGFR, AREG, and EREG expression correlated with shorter OS (AREG: HR = 1.57, CI 1.12 - 2.20, p = 0.0090) and DFS (EGFR: HR = 1.91, CI 1.31 - 2.8, p = 0.0008). EGFR amplification was also associated with reduced DFS. Discussion: High EGFR and EREG indicate worse survival in patients with MIBC. The prognostic role of AREG should further be investigated in large, prospective series. Divergent survival outcomes between the four cohorts should be interpreted cautiously, considering differences in analysis methods and demographics. Further in vitro investigations are necessary to elucidate the functional mechanisms underlying the associations observed in this study.

Designing interactive visualizations for analyzing chronic lung diseases in a user-centered approach.

OBJECTIVES: Medical practitioners analyze numerous types of data, often using archaic representations that do not meet their needs. Pneumologists who analyze lung function exams must often consult multiple exam records manually, making comparisons cumbersome. Such shortcomings can be addressed with interactive visualizations, but these must be designed carefully with practitioners' needs in mind. MATERIALS AND METHODS: A workshop with experts was conducted to gather user requirements and common tasks. Based on the workshop results, we iteratively designed a web-based prototype, continuously consulting experts along the way. The resulting application was evaluated in a formative study via expert interviews with 3 medical practitioners. RESULTS: Participants in our study were able to solve all tasks in accordance with experts' expectations and generally viewed our system positively, though there were some usability and utility issues in the initial prototype. An improved version of our system solves these issues and includes additional customization functionalities. DISCUSSION: The study results showed that participants were able to use our system effectively to solve domain-relevant tasks, even though some shortcomings could be observed. Using a different framework with more fine-grained control over interactions and visual elements, we implemented design changes in an improved version of our prototype that needs to be evaluated in future work. CONCLUSION: Employing a user-centered design approach, we developed a visual analytics system for lung function data that allows medical practitioners to more easily analyze the progression of several key parameters over time.

Peritoneal Flap for Lymphocele Prophylaxis Following Robotic-assisted Radical Prostatectomy with Lymph Node Dissection: The Randomised Controlled Phase 3 PELYCAN Trial.

BACKGROUND: Symptomatic lymphoceles (SLCs) after transperitoneal robotic-assisted radical prostatectomy with pelvic lymph node dissection (PLND) are common. Evidence from randomised controlled trials (RCTs) on the impact of peritoneal flaps (PFs) on lymphocele (LC) reduction is inconclusive. OBJECTIVE: To show that addition of PFs leads to a reduction of postoperative SLCs. DESIGN, SETTING, AND PARTICIPANTS: An investigator-initiated, prospective, parallel, double-blinded, adaptive, phase 3 RCT was conducted. Recruitment took place from September 2019 until December 2021; 6-month written survey-based follow-up was recorded. Stratification was carried out according to potential LC risk factors (extended PLND, diabetes mellitus, and anticoagulation) and surgeons; 1:1 block randomisation was used. Surgeons were informed about allocation after completion of the last surgical step. INTERVENTION: To create PFs, the ventral peritoneum was incised bilaterally and fixated to the pelvic floor. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary endpoint was SLCs. Secondary endpoints included asymptomatic lymphoceles (ALCs), perioperative parameters, and postoperative complications. RESULTS AND LIMITATIONS: In total, 860 men were screened and 551 randomised. Significant reductions of SLCs (from 9.1% to 3.7%, p = 0.005) and ALCs (27.2% to 10.3%, p < 0.001) over the follow-up period of 6 mo were observed in the intention-to-treat analysis. Operating time was 11 min longer (p < 0.001) in the intervention group; no significant differences in amount (80 vs 103, p = 0.879) and severity (p = 0.182) of postoperative complications (excluding LCs) were observed. The survey-based follow-up might be a limitation. CONCLUSIONS: This is the largest RCT evaluating PF creation for LC prevention and met its primary endpoint, the reduction of SLCs. The results were consistent among all subgroup analyses including ALCs. Owing to the subsequent reduction of burden for patients and the healthcare system, establishing PFs should become the new standard of care. PATIENT SUMMARY: A new technique-creation of bilateral peritoneal flaps-was added to the standard procedure of robotic-assisted prostatectomy for lymph node removal. It was safe and decreased lymphocele development, a common postoperative complication and morbidity. Hence, it should become a standard procedure.

Randomized Controlled Feasibility Trial of Robot-assisted Versus Conventional Open Partial Nephrectomy: The ROBOCOP II Study.

BACKGROUND: There is no evidence from randomized controlled trials (RCTs) comparing robot-assisted partial nephrectomy (RAPN) and open partial nephrectomy (OPN). OBJECTIVE: To assess the feasibility of trial recruitment and to compare surgical outcomes between RAPN and OPN. DESIGN, SETTING, AND PARTICIPANTS: ROBOCOP II was designed as single-center, open-label, feasibility RCT. Patients with suspected localized renal cell carcinoma referred for PN were randomized at a 1:1 ratio to either RAPN or OPN. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was the feasibility of recruitment, assessed as the accrual rate. Secondary outcomes included perioperative and postoperative data. Data were analyzed descriptively in a modified intention-to-treat population consisting of randomized patients who underwent surgery. RESULTS AND LIMITATIONS: A total of 50 patients underwent RAPN or OPN (accrual rate 65%). In comparison to OPN, RAPN had lower blood loss (OPN 361 ml, standard deviation [SD] 238; RAPN 149 ml, SD 122; difference 212 ml, 95% confidence interval [CI] 105-320; p < 0.001), less need for opioids (OPN 46%; RAPN 16%; difference 30%, 95% CI 5-54; p = 0.024), and fewer complications according to the mean Comprehensive Complication Index (OPN 14, SD 16; RAPN 5, SD 15; difference 9, 95% CI 0-18; p = 0.008). OPN has a shorter operative time (OPN 112 min, SD 29; RAPN 130 min, SD 32; difference -18 min, 95% CI -35 to -1; p = 0.046) and warm ischemia time (OPN 8.7 min, SD 7.1; RAPN 15.4 min, SD 7.0; difference 6.7 min, 95% CI -10.7 to -2.7; p = 0.001). There were no differences between RAPN and OPN regarding postoperative kidney function. CONCLUSIONS: This first RCT comparing OPN and RAPN met the primary outcome of the feasibility of recruitment; however, the window for future RCTs is closing. Each approach has advantages over the other, and both remain safe and effective options. PATIENT SUMMARY: For patients with a kidney tumor, open surgery and robot-assisted keyhole surgery are both feasible and safe approaches for partial removal of the affected kidney. Each approach has known advantages. Long-term follow-up will explore differences in quality of life and cancer control outcomes.

Traceable Research Data Sharing in a German Medical Data Integration Center With FAIR (Findability, Accessibility, Interoperability, and Reusability)-Geared Provenance Implementation: Proof-of-Concept Study.

BACKGROUND: Secondary investigations into digital health records, including electronic patient data from German medical data integration centers (DICs), pave the way for enhanced future patient care. However, only limited information is captured regarding the integrity, traceability, and quality of the (sensitive) data elements. This lack of detail diminishes trust in the validity of the collected data. From a technical standpoint, adhering to the widely accepted FAIR (Findability, Accessibility, Interoperability, and Reusability) principles for data stewardship necessitates enriching data with provenance-related metadata. Provenance offers insights into the readiness for the reuse of a data element and serves as a supplier of data governance. OBJECTIVE: The primary goal of this study is to augment the reusability of clinical routine data within a medical DIC for secondary utilization in clinical research. Our aim is to establish provenance traces that underpin the status of data integrity, reliability, and consequently, trust in electronic health records, thereby enhancing the accountability of the medical DIC. We present the implementation of a proof-of-concept provenance library integrating international standards as an initial step. METHODS: We adhered to a customized road map for a provenance framework, and examined the data integration steps across the ETL (extract, transform, and load) phases. Following a maturity model, we derived requirements for a provenance library. Using this research approach, we formulated a provenance model with associated metadata and implemented a proof-of-concept provenance class. Furthermore, we seamlessly incorporated the internationally recognized Word Wide Web Consortium (W3C) provenance standard, aligned the resultant provenance records with the interoperable health care standard Fast Healthcare Interoperability Resources, and presented them in various representation formats. Ultimately, we conducted a thorough assessment of provenance trace measurements. RESULTS: This study marks the inaugural implementation of integrated provenance traces at the data element level within a German medical DIC. We devised and executed a practical method that synergizes the robustness of quality- and health standard-guided (meta)data management practices. Our measurements indicate commendable pipeline execution times, attaining notable levels of accuracy and reliability in processing clinical routine data, thereby ensuring accountability in the medical DIC. These findings should inspire the development of additional tools aimed at providing evidence-based and reliable electronic health record services for secondary use. CONCLUSIONS: The research method outlined for the proof-of-concept provenance class has been crafted to promote effective and reliable core data management practices. It aims to enhance biomedical data by imbuing it with meaningful provenance, thereby bolstering the benefits for both research and society. Additionally, it facilitates the streamlined reuse of biomedical data. As a result, the system mitigates risks, as data analysis without knowledge of the origin and quality of all data elements is rendered futile. While the approach was initially developed for the medical DIC use case, these principles can be universally applied throughout the scientific domain.

Radical Prostatectomy on YouTube: Education or Disinformation?

Background: YouTube is the second most popular website worldwide. It features numerous videos about radical prostatectomy.The aim of this study was to assess the quality of these videos and screen their benefit for patients and doctors.Methods: All videos on YouTube about radical prostatectomy were analysed using a specially developed software (python 2.7,numpy). According to a predefined selection process most relevant videos were analyzed for quality and reliability using SuitabilityAssessment of Materials (SAM)-Score, Global Quality Score and others.Results: Out of 3520 search results, 179 videos were selected and analysed. Videos were watched a median of 5836 times (interquartilerange (IQR): 11945.5; 18–721546). The median duration was 7.2 minutes (min). 125 of the videos were about roboticprostatectomy. 69 videos each were directly addressed to patients and doctors. Medical content generally was of low quality,while technical quality and total quality were at a high level. Reliability was good.Conclusions: Videos on radical prostatectomy on YouTube allow for patient information. While technical quality and reliabilityare classified as acceptable, medical content was low and warranted preselection. In contrast to Loeb et al. we did notobserve a negative correlation between number of views and scientific quality in different scores. Our findings support the needfor preselection of videos on YouTube as the potential benefit may vary between videos with the significant risk of low medicalquality. (AU)

Triptychon: Usability evaluation and implementation of a web-based application for patients' lab and vital parameters.

Background: A major challenge in healthcare is the interpretation of the constantly increasing amount of clinical data of interest to inpatients for diagnosis and therapy. It is vital to accurately structure and represent data from different sources to help clinicians make informed decisions. Objective: We evaluated the usability of our tool 'Triptychon' - a three-part visualisation dashboard of essential patients' medical data provided by a direct overview of their hospitalisation information, laboratory, and vital parameters over time. Methods: The study followed a cohort of 20 participants using the mixed-methods approach, including interviews and the usability questionnaires, Health Information Technology Usability Evaluation Scale (Health-ITUES), and User Experience Questionnaire (UEQ). The participant's interactions with the dashboard were also observed. A thematic analysis approach was applied to analyse qualitative data and the quantitative data's task completion time and success rates. Results: The usability evaluation of the visualisation dashboard revealed issues relating to the terminology used in the user interface and colour coding in its left and middle panels. The Health-ITUES score was 3.72 (standard deviation (SD) = 1.0), and the UEQ score was 1.6 (SD = 0.74). The study demonstrated improvements in intuitive dashboard use and overall satisfaction with using the dashboard daily. Conclusion: The Triptychon dashboard is a promising new tool for medical data presentation. We identified design and layout issues of the dashboard for improving its usability in routine clinical practice. According to users' feedback, the three panels on the dashboard provided a holistic view of a patient's hospital stay.

The Status of Data Management Practices Across German Medical Data Integration Centers: Mixed Methods Study.

BACKGROUND: In the context of the Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex data flows to transfer routine health care data into research data repositories for secondary use. Data management practices are of importance throughout these processes, and special attention should be given to provenance aspects. Insufficient knowledge can lead to validity risks and reduce the confidence and quality of the processed data. The need to implement maintainable data management practices is undisputed, but there is a great lack of clarity on the status. OBJECTIVE: Our study examines the current data management practices throughout the data life cycle within the Medical Informatics in Research and Care in University Medicine (MIRACUM) consortium. We present a framework for the maturity status of data management practices and present recommendations to enable a trustful dissemination and reuse of routine health care data. METHODS: In this mixed methods study, we conducted semistructured interviews with stakeholders from 10 DICs between July and September 2021. We used a self-designed questionnaire that we tailored to the MIRACUM DICs, to collect qualitative and quantitative data. Our study method is compliant with the Good Reporting of a Mixed Methods Study (GRAMMS) checklist. RESULTS: Our study provides insights into the data management practices at the MIRACUM DICs. We identify several traceability issues that can be partially explained with a lack of contextual information within nonharmonized workflow steps, unclear responsibilities, missing or incomplete data elements, and incomplete information about the computational environment information. Based on the identified shortcomings, we suggest a data management maturity framework to reach more clarity and to help define enhanced data management strategies. CONCLUSIONS: The data management maturity framework supports the production and dissemination of accurate and provenance-enriched data for secondary use. Our work serves as a catalyst for the derivation of an overarching data management strategy, abiding data integrity and provenance characteristics as key factors. We envision that this work will lead to the generation of fairer and maintained health research data of high quality.

German Version of the mHealth App Usability Questionnaire in a Cohort of Patients With Cancer: Translation and Validation Study.

BACKGROUND: Good usability is important for the adoption and continued use of mobile health (mHealth) apps. In particular, high usability can support intuitive use by patients, which improves compliance and increases the app's effectiveness. However, many usability studies do not use adequate tools to measure perceived usability. The mHealth App Usability Questionnaire (MAUQ) was developed specifically for end users in a medical context. MAUQ is a relatively new but increasingly used questionnaire to evaluate mHealth apps, but it is not yet available in German. OBJECTIVE: This study aims to translate MAUQ into German and determine its internal consistency, reliability, and construct validity. METHODS: This validation study was conducted as part of a usability evaluation project for an mHealth app used as a therapy support tool during breast cancer chemotherapy. MAUQ was translated into German through a rigorous forward-backward translation process, ensuring semantic and conceptual equivalence. Patient responses to MAUQ and System Usability Scale (SUS) were analyzed for validation. Descriptive analysis was performed for the MAUQ subscales and SUS standard scores. Significance tests and correlation coefficients assessed the relationship between the SUS and MAUQ results, confirming construct validity. Internal consistency was assessed for item reliability and consistency in measuring the target construct. Free-text questions assessed translation comprehensibility, with responses analyzed descriptively and qualitatively using content analysis. RESULTS: In this study, 133 participants responded to the questionnaire, and the validation analysis showed substantially positive correlations between the overall MAUQ score and its subscales: ease of use (r=0.56), interface and satisfaction (r=0.75), and usefulness (r=0.83). These findings support the construct validity of MAUQ and emphasize the importance of these subscales in assessing the usability of the Enable app. The correlation coefficients ranging from 0.39 to 0.68 for the items further validate the questionnaire by aligning with the overall score and capturing the intended concept. The high internal consistency reliability of MAUQ (Cronbach α=.81) and its subscales further enhances the instrument's robustness in accurately evaluating the usability of mHealth apps. CONCLUSIONS: We successfully validated the German translation of the MAUQ for stand-alone apps using a standardized approach in a cohort of patients with breast cancer. In our validation study, MAUQ exhibited strong internal consistency reliability (Cronbach α=.81) across its subscales, indicating reliable and consistent measurement. Furthermore, a significant positive correlation (P<.001) was found between the subscales and the overall score, supporting their consistent measurement of the intended construct. Therefore, MAUQ can be considered a reliable instrument for assessing the usability of mHealth apps among German-speaking adults. The availability of the German version of MAUQ will help other researchers in conducting usability studies of mHealth apps in German-speaking cohorts and allow for international comparability of their results.

Data Quality- and Utility-Compliant Anonymization of Common Data Model-Harmonized Electronic Health Record Data: Protocol for a Scoping Review.

BACKGROUND: The anonymization of Common Data Model (CDM)-converted EHR data is essential to ensure the data privacy in the use of harmonized health care data. However, applying data anonymization techniques can significantly affect many properties of the resulting data sets and thus biases research results. Few studies have reviewed these applications with a reflection of approaches to manage data utility and quality concerns in the context of CDM-formatted health care data. OBJECTIVE: Our intended scoping review aims to identify and describe (1) how formal anonymization methods are carried out with CDM-converted health care data, (2) how data quality and utility concerns are considered, and (3) how the various CDMs differ in terms of their suitability for recording anonymized data. METHODS: The planned scoping review is based on the framework of Arksey and O'Malley. By using this, only articles published in English will be included. The retrieval of literature items should be based on a literature search string combining keywords related to data anonymization, CDM standards, and data quality assessment. The proposed literature search query should be validated by a librarian, accompanied by manual searches to include further informal sources. Eligible articles will first undergo a deduplication step, followed by the screening of titles. Second, a full-text reading will allow the 2 reviewers involved to reach the final decision about article selection, while a domain expert will support the resolution of citation selection conflicts. Additionally, key information will be extracted, categorized, summarized, and analyzed by using a proposed template into an iterative process. Tabular and graphical analyses should be addressed in alignment with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. We also performed some tentative searches on Web of Science for estimating the feasibility of reaching eligible articles. RESULTS: Tentative searches on Web of Science resulted in 507 nonduplicated matches, suggesting the availability of (potential) relevant articles. Further analysis and selection steps will allow us to derive a final literature set. Furthermore, the completion of this scoping review study is expected by the end of the fourth quarter of 2023. CONCLUSIONS: Outlining the approaches of applying formal anonymization methods on CDM-formatted health care data while taking into account data quality and utility concerns should provide useful insights to understand the existing approaches and future research direction based on identified gaps. This protocol describes a schedule to perform a scoping review, which should support the conduction of follow-up investigations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/46471.

Lightweight Visual Transformers Outperform Convolutional Neural Networks for Gram-Stained Image Classification: An Empirical Study.

We aimed to automate Gram-stain analysis to speed up the detection of bacterial strains in patients suffering from infections. We performed comparative analyses of visual transformers (VT) using various configurations including model size (small vs. large), training epochs (1 vs. 100), and quantization schemes (tensor- or channel-wise) using float32 or int8 on publicly available (DIBaS, n = 660) and locally compiled (n = 8500) datasets. Six VT models (BEiT, DeiT, MobileViT, PoolFormer, Swin and ViT) were evaluated and compared to two convolutional neural networks (CNN), ResNet and ConvNeXT. The overall overview of performances including accuracy, inference time and model size was also visualized. Frames per second (FPS) of small models consistently surpassed their large counterparts by a factor of 1-2×. DeiT small was the fastest VT in int8 configuration (6.0 FPS). In conclusion, VTs consistently outperformed CNNs for Gram-stain classification in most settings even on smaller datasets.

Radical Prostatectomy on YouTube: Education or Disinformation?

BACKGROUND: YouTube is the second most popular website worldwide. It features numerous videos about radical prostatectomy. The aim of this study was to assess the quality of these videos and screen their benefit for patients and doctors. METHODS: All videos on YouTube about radical prostatectomy were analysed using a specially developed software (python 2.7, numpy). According to a predefined selection process most relevant videos were analyzed for quality and reliability using Suitability Assessment of Materials (SAM)-Score, Global Quality Score and others. RESULTS: Out of 3520 search results, 179 videos were selected and analysed. Videos were watched a median of 5836 times (interquartile range (IQR): 11945.5; 18-721546). The median duration was 7.2 minutes (min). 125 of the videos were about robotic prostatectomy. 69 videos each were directly addressed to patients and doctors. Medical content generally was of low quality, while technical quality and total quality were at a high level. Reliability was good. CONCLUSIONS: Videos on radical prostatectomy on YouTube allow for patient information. While technical quality and reliability are classified as acceptable, medical content was low and warranted preselection. In contrast to Loeb et al. we did not observe a negative correlation between number of views and scientific quality in different scores. Our findings support the need for preselection of videos on YouTube as the potential benefit may vary between videos with the significant risk of low medical quality.

Rapid Convolutional Neural Networks for Gram-Stained Image Classification at Inference Time on Mobile Devices: Empirical Study from Transfer Learning to Optimization.

Despite the emergence of mobile health and the success of deep learning (DL), deploying production-ready DL models to resource-limited devices remains challenging. Especially, during inference time, the speed of DL models becomes relevant. We aimed to accelerate inference time for Gram-stained analysis, which is a tedious and manual task involving microorganism detection on whole slide images. Three DL models were optimized in three steps: transfer learning, pruning and quantization and then evaluated on two Android smartphones. Most convolutional layers (≥80%) had to be retrained for adaptation to the Gram-stained classification task. The combination of pruning and quantization demonstrated its utility to reduce the model size and inference time without compromising model quality. Pruning mainly contributed to model size reduction by 15×, while quantization reduced inference time by 3× and decreased model size by 4×. The combination of two reduced the baseline model by an overall factor of 46×. Optimized models were smaller than 6 MB and were able to process one image in <0.6 s on a Galaxy S10. Our findings demonstrate that methods for model compression are highly relevant for the successful deployment of DL solutions to resource-limited devices.

Long-term Reinterventions after Thulium Laser Enucleation of the Prostate: 12-Year Experience with more than 1000 Patients.

BACKGROUND: Thulium laser enucleation of the prostate (ThuLEP) is an established treatment option for benign prostatic enlargement (BPE), but long-term outcomes have not yet been reported. OBJECTIVE: To prove the durability of ThuLEP by investigating its long-term efficacy and morbidity. DESIGN, SETTING, AND PARTICIPANTS: All patients who underwent ThuLEP at a German tertiary referral center between 2009 and 2021 were retrospectively followed up for reinterventions for persistence or regrowth of prostate adenoma (ReIP) or long-term complications (ReIC). INTERVENTION: ThuLEP. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We calculated the cumulative incidence for ReIP and ReIC at 10 yr. Univariate and multivariate Cox regression models were constructed to identify predictors of ReIP and ReIC. RESULTS AND LIMITATIONS: Overall, 1097 patients underwent ThuLEP. The median overall follow-up was 6.0 yr (interquartile range [IQR] 2.4-9.2). For one-third of patients (n = 369), median follow-up of 10 yr (IQR 9.1-11.2) was available. A total of 42 patients (3.8%) underwent ReIP after a median of 2 yr (IQR 0.3-4.9). The rate of long-term ReIC was 2.6% (n = 29) and the median time to ReIC was 0.5 yr (IQR 0.3-1.7). The most frequent ReIC was urethrotomy (n = 16, 1.5%). The cumulative incidence of ReIP and ReIC at 10 yr was estimated at 5.6% and 3.4%, respectively. Enucleation weight ≥60 g was a significant predictor of ReIP (hazard ratio 1.2, p = 0.014). The retrospective study design and the lack of functional outcomes are the main limitations. CONCLUSIONS: ThuLEP is a durably effective and safe procedure with low reintervention rates within 12 yr. PATIENT SUMMARY: This study investigated long-term outcomes of thulium laser enucleation of the prostate for benign enlargement of the prostate (BPE). Low rates of repeat treatment for BPE recurrence or for other complications were observed. Our results show the safety and efficacy of this treatment over a period of 12 years.

Prospective Evaluation of Antibiotic Management in Ureteral Stent and Nephrostomy Interventions.

INTRODUCTION: Screening for and treating asymptomatic bacteriuria (ABU) or administering antibiotic prophylaxis is recommended during ureteral stent and nephrostomy interventions. This study investigates the frequency of postinterventional infectious complications to gain insight into the need for antibiotics. METHODS: Between September 2016 and June 2019, 168 insertions/exchanges of ureteral stents or nephrostomies were recorded in a prospective multicenter study. Patients without a symptomatic UTI did not receive antibiotic treatment/prophylaxis. Asymptomatic patients in whom their urologist already administered an antibiotic treatment served as a comparative group. Follow-up included postinterventional complications within 30 days. Symptoms were assessed by the Acute Cystitis Symptom Score (ACSS) before and after the intervention. Predictors of increasing postinterventional symptoms were analyzed by a multivariable logistic regression model. RESULTS: One hundred forty-five interventions were eligible. One hundred twenty-two (84.1%) interventions were performed without antibiotic treatment. Preinterventional ABU was detected in 54.4% and sterile urine in 22.8% (22.8% without culture). Postinterventional infectious complications did not differ between patients with versus without antibiotics. Transurethral interventions aggravate symptoms (p = 0.034) but do not increase infectious complications compared to percutaneous interventions. Patients without diabetes mellitus are at higher risk for increasing symptoms. CONCLUSION: Results indicate that peri-interventional antibiotic treatment may be omitted in patients without symptomatic UTI. Symptoms must be differentiated between infectious and procedure-associated origins.

Active surveillance inclusion criteria under scrutiny in magnetic resonance imaging-guided prostate biopsy: a multicenter cohort study.

BACKGROUND: Although multiparametric magnetic resonance imaging (mpMRI) is recommended for primary risk stratification and follow-up in Active Surveillance (AS), it is not part of common AS inclusion criteria. The objective was to compare AS eligibility by systematic biopsy (SB) and combined MRI-targeted (MRI-TB) and SB within real-world data using current AS guidelines. METHODS: A retrospective multicenter study was conducted by a German prostate cancer (PCa) working group representing six tertiary referral centers and one outpatient practice. Men with PCa and at least one MRI-visible lesion according to Prostate Imaging Reporting and Data System (PI-RADS) v2 were included. Twenty different AS inclusion criteria of international guidelines were applied to calculate AS eligibility using either a SB or a combined MRI-TB and SB. Reasons for AS exclusion were assessed. RESULTS: Of 1941 patients with PCa, per guideline, 583-1112 patients with PCa in both MRI-TB and SB were available for analysis. Using SB, a median of 22.1% (range 6.4-72.4%) were eligible for AS. Using the combined approach, a median of 15% (range 1.7-68.3%) were eligible for AS. Addition of MRI-TB led to a 32.1% reduction of suitable patients. Besides Gleason Score upgrading, the maximum number of positive cores were the most frequent exclusion criterion. Variability in MRI and biopsy protocols potentially limit the results. CONCLUSIONS: Only a moderate number of patients with PCa can be monitored by AS to defer active treatment using current guidelines for inclusion in a real-world setting. By an additional MRI-TB, this number is markedly reduced. These results underline the need for a contemporary adjustment of AS inclusion criteria.

ROBOCOP II (ROBOtic assisted versus conventional open partial nephrectomy) randomised, controlled feasibility trial: clinical trial protocol.

INTRODUCTION: Randomised controlled trials comparing robotic-assisted partial nephrectomy (RAPN) and open PN (OPN) are lacking. Therefore, we aim to report the study protocol and a trial update for a randomised controlled feasibility trial comparing RAPN versus OPN for renal neoplasms. METHODS AND ANALYSIS: The ROBOtic assisted versus conventional Open Partial nephrectomy II trial is designed as a single-centre, randomised, open-label, feasibility trial. Participation will be offered to patients with renal neoplasms and deemed feasible for both, OPN and RAPN. We aim to enrol 50 patients within 15 months using a 1:1 allocation ratio. The primary endpoint of the trial is feasibility of recruitment and will be successful if one third of eligible patients agree to participate. Secondary endpoints include perioperative results, health-related quality of life, inflammatory response as well as surgical ergonomics of the operating team. If the primary outcome, feasibility of recruitment, is successful, the secondary results of the trial will be used for planning a confirmative phase III trial. ETHICS AND DISSEMINATION: Ethical approval was obtained from the local institutional review board (Ethik-Kommission II at Heidelberg University: 2020-542N). Results will be made publicly available in peer-reviewed scientific journals and presented at appropriate congresses and social media. TRIAL REGISTRATION NUMBER: NCT04534998.

[What can machines do?] / Was können die Maschinen?: Praktischer Nutzen von Big Data und Künstlicher Intelligenz in der Medizin.

With increasing computing and storage capacity, the application of big data and artificial intelligence (AI) is almost inexorably finding its way into medicine. The main areas of application so far have been in radiology and pathology, as well as in other areas such as genome sequencing and psychiatry. By evaluating ever larger amounts of data, patterns are sought that can make physicians' work easier by making a preselection. In addition, efforts are being made to uncover previously unrecognized connections. Large amounts of data are recorded by the patients themselves using so-called wearables. How can this data be used meaningfully? What are the dangers? Efforts are also being made in urology to improve the treatment of urinary tract infections and kidney stones, for example, through the use of networked computer systems. Great progress can be expected in the next few years in the field of big data and AI. An enormous expansion of the areas of application is going to come; as such, we are only at the beginning of the development.

Potential Candidates for Focal Therapy in Prostate Cancer in the Era of Magnetic Resonance Imaging-targeted Biopsy: A Large Multicenter Cohort Study.

BACKGROUND: Focal therapy (FT) with its favorable side-effect profile represents an option between active surveillance and traditional whole-gland treatment in localized prostate cancer (PCa). Consensus statements recommend eligibility criteria based on magnetic resonance imaging (MRI)-targeted and systematic combination biopsy. OBJECTIVE: To estimate the future potential of FT by analyzing the number of men eligible for FT among all men with biopsy-proven PCa and to judge the potential of different energy sources. DESIGN, SETTING, AND PARTICIPANTS: Consensus criteria on FT were analyzed. Patients with biopsy-proven PCa from six tertiary referral hospitals and one outpatient practice in Germany had received a software-based combination biopsy. Men with Prostate Imaging Reporting and Data System (PI-RADS) ≥3 lesions based on PI-RADS v2 were included. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patients were analyzed for potential treatment by FT and hemiablation. MRI lesions were mapped according to prostatic zones. RESULTS AND LIMITATIONS: In total, 2371 patients were analyzed. According to consensus criteria (biopsy-proven unifocal lesion of International Society of Urological Pathology [ISUP] grade group ≤2, prostate-specific antigen [PSA] ≤15ng/mL, and life expectancy >10yr), 303 patients (12.8%; ISUP 1: n=148 [6.2%]; ISUP 2: n=155 [6.5%]) were potential candidates for FT. A maximum PSA level of <10ng/mL would exclude further 60 (2.5%) of these men. The eligibility for hemiablation is slightly higher (16.2%). Unifocal lesions (n=288) were equally distributed within the prostate (anteriorly [31%], apically [29%], and dorsally [36%]). CONCLUSIONS: With adherence to consensus statements, only a minority of PCa patients present as potential candidates for FT. Distribution of tumor localization suggests the need for different energy modalities to warrant an optimal FT treatment. PATIENT SUMMARY: We analyzed how many men who receive a magnetic resonance imaging-targeted and systematic prostate biopsy are candidates for the experimental focal therapy of the prostate. When following expert recommendations, only a small number of men are potential candidates for this alternative treatment.

Comparative analysis of machine learning algorithms for computer-assisted reporting based on fully automated cross-lingual RadLex mappings.

Computer-assisted reporting (CAR) tools were suggested to improve radiology report quality by context-sensitively recommending key imaging biomarkers. However, studies evaluating machine learning (ML) algorithms on cross-lingual ontological (RadLex) mappings for developing embedded CAR algorithms are lacking. Therefore, we compared ML algorithms developed on human expert-annotated features against those developed on fully automated cross-lingual (German to English) RadLex mappings using 206 CT reports of suspected stroke. Target label was whether the Alberta Stroke Programme Early CT Score (ASPECTS) should have been provided (yes/no:154/52). We focused on probabilistic outputs of ML-algorithms including tree-based methods, elastic net, support vector machines (SVMs) and fastText (linear classifier), which were evaluated in the same 5 × fivefold nested cross-validation framework. This allowed for model stacking and classifier rankings. Performance was evaluated using calibration metrics (AUC, brier score, log loss) and -plots. Contextual ML-based assistance recommending ASPECTS was feasible. SVMs showed the highest accuracies both on human-extracted- (87%) and RadLex features (findings:82.5%; impressions:85.4%). FastText achieved the highest accuracy (89.3%) and AUC (92%) on impressions. Boosted trees fitted on findings had the best calibration profile. Our approach provides guidance for choosing ML classifiers for CAR tools in fully automated and language-agnostic fashion using bag-of-RadLex terms on limited expert-labelled training data.