Background: Large language models (LLMs) are increasingly being explored to supporting evidence-based decision-making in urology, but their accuracy in interpreting and applying clinical guidelines remains uncertain.Objectives: We aimed to evaluate the ability of LLMs to interpret and apply clinical guidelines across the full spectrum of major urological cancers.Design: This expert-validated study evaluated six configurations of three top LLMs (Claude, Gemini, and ChatGPT) using 25 structured questions for each of the seven major urological cancers: prostate cancer, upper tract urothelial carcinoma, muscle-invasive and non-muscle-invasive bladder cancer, renal cell carcinoma, penile cancer, and testicular cancer.Methods: Both simple and rephrased prompts were used to assess the impact of prompt engineering on response quality. All figures and tables from the English-language EAU guidelines were systematically converted into plain, structured text and peer reviewed by multidisciplinary experts before evaluating the LLM responses. Each response was independently rated by 9-11 uro-oncology specialists using a five-point Likert scale (1: incorrect/unacceptable, 5: optimal), resulting in 10,500 evaluations.Results: Claude achieved the highest overall accuracy, with 45.9% of responses rated as optimal (Likert 5) and 87% as optimal/acceptable (Likert 4-5). Tumor-specific performance peaked in muscle-invasive bladder (56.7% optimal, 93% optimal/acceptable), penile (49.5%, 95%), and testicular cancer (60.9%, 94%). Gemini and ChatGPT showed lower optimal rates but acceptable performance (68%-70% optimal/acceptable). Rephrased prompts did not consistently outperform simple versions. All models showed acceptable accuracy, but the results should be interpreted cautiously due to recency bias and fast LLM tech evolution.Conclusion: This study demonstrates the value of rigorous plain language adaptation and expert validation in benchmarking LLMs, supporting their potential as decision-support tools in uro-oncology.

In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early prediction of clinically significant cancer (CsPCa). The prostate imaging-reporting and data system (PI-RADS) is combined with clinical variables predominantly based on logistic regression models. This study explores modeling using regularization techniques such as ridge regression, LASSO, elastic net, classification tree, tree ensemble models like random forest or XGBoost, and neural networks to predict CsPCa in a dataset of 4799 patients in Catalonia (Spain). An 80-20% split was employed for training and validation. We used predictor variables such as age, prostate-specific antigen (PSA), prostate volume, PSA density (PSAD), digital rectal exam (DRE) findings, family history of PCa, a previous negative biopsy, and PI-RADS categories. When considering a sensitivity of 0.9, in the validation set, the XGBoost model outperforms others with a specificity of 0.640, followed closely by random forest (0.638), neural network (0.634), and logistic regression (0.620). In terms of clinical utility, for a 10% missclassification of CsPCa, XGBoost can avoid 41.77% of unnecessary biopsies, followed closely by random forest (41.67%) and neural networks (41.46%), while logistic regression has a lower rate of 40.62%. Using SHAP values for model explainability, PI-RADS emerges as the most influential risk factor, particularly for individuals with PI-RADS 4 and 5. Additionally, a positive digital rectal examination (DRE) or family history of prostate cancer proves highly influential for certain individuals, while a previous negative biopsy serves as a protective factor for others.

Antineoplastic therapies for prostate cancer (PCa) have traditionally centered around the androgen receptor (AR) pathway, which has demonstrated a significant role in oncogenesis. Nevertheless, it is becoming progressively apparent that therapeutic strategies must diversify their focus due to the emergence of resistance mechanisms that the tumor employs when subjected to monomolecular treatments. This review illustrates how the dysregulation of the lipid metabolic pathway constitutes a survival strategy adopted by tumors to evade eradication efforts. Integrating this aspect into oncological management could prove valuable in combating PCa.

Background: The sinusoidal pattern in cardiotocographic (CTG) monitoring shows a sinus-shaped signal longer than 30 min without short-term variability. It is commonly linked to fetal morbidity, particularly severe fetal anemia. Pseudosinusoidal patterns resemble sinusoidal patterns but without adverse fetal outcomes. This study aims to characterise sinusoidal and pseudosinusoidal patterns using spectral analysis. Methods: A multicenter study case-control was conducted between January 2012 and February 2023. Maternal characteristics, perinatal data, and CTG parameters through spectral analysis were examined. The spectrum of the electrocardiographic signal was calculated, and the proportion of energy (PE), short- and long-term variability, amplitude, and the differences between sinusoidal, pseudosinusoidal, and control groups were compared. A predictive model for signal type was built using a classification tree. Results: 60 CTG records were collected, including 38 controls. Of the 13 sinusoidal patterns detected, all exhibited a sinusoidal pattern with a PE ratio > 0.3, 9 of them (69 %) had a PE ratio > 0.5, and 4 (31 %) were in the range of 0.3-0.5. Among the 9 cases diagnosed as pseudosinusoidal, all had a sinusoidal pattern with a PE within the range of 0.3-0.5. Every control exhibited a PE < 0.3, except for one case. Short-term variability demonstrated limited discriminatory capability, while long-term variability showed a strong discriminatory capacity. For the classification tree, accuracy diagnosis was 92.3 %, 88.8 %, and 97.3 % for the sinusoidal, pseudosinusoidal, and control groups, respectively. Conclusion: Computerised spectral analysis and the variable PE within the frequency range of 1.8-3.5 are reliable parameters to discriminate sinusoidal patterns.

Early-life onset of high blood pressure is associated with the development of cardiovascular diseases in adulthood. In adolescents, limited evidence exists regarding the association between adherence to the Mediterranean Diet (MedDiet) and normal blood pressure (BP) levels, as well as its potential to modulate genetic predisposition to HTN. This study investigated the interaction between a MedDiet score and a recently developed HTN-genetic risk score (HTN-GRS) on blood pressure levels in a European adolescent cohort. The MedDiet score was derived from two non-consecutive 24-h dietary recalls and ranged from 0 (indicating low adherence) to 9 (indicating high adherence). Multiple linear regression models, adjusted for covariates, were employed to examine the relationship between the MedDiet score and BP z -scores and to assess the interaction effects between the MedDiet score and HTN-GRS on BP z-scores. MedDiet score showed a negative association with z -systolic BP (SBP) ( ß = −0.40, p < 0.001) and z -diastolic BP (DBP) ( ß = −0.29, p = 0.001). Additionally, a significant interaction effect was identified between the MedDiet score and HTN-GRS on z -SBP ( ß = 0.02, p < 0.001) and z -DBP ( ß = 0.02, p < 0.001). The modulatory effect of the MedDiet was more pronounced in females than in males, and HTN-GRS exhibited a stronger influence on DBP than on SBP. Conclusion : The study suggests that higher adherence to the MedDiet is associated with reduced BP levels in adolescents and provides evidence of a genetic-diet interaction influencing BP in adolescents. What is Known: • Adherence to the Mediterranean diet may reduce BP levels. What is New: • It is the first study to assess the connection between adherence to a Mediterranean diet, a hypertension genetic risk score, and how they interact in influencing blood pressure. • It is conducted within a multicenter cohort of European adolescents.

ObjectiveTo identify new parameters predicting fetal acidemia.MethodsA retrospective case-control study in a cohort of deliveries from a tertiary referral hospital-based cohort deliveries in Zaragoza, Spain between 2018 and 2021 was performed. To predict fetal acidemia, the NICHD categorizations and non-NICHD parameters were analyzed in the electronic fetal monitoring (EFM). Those included total reperfusion time, total deceleration area and the slope of the descending limb of the fetal heart rate of the last deceleration curve. The accuracy of the parameters was evaluated using the specificity for (80%, 85%, 90%, 95%) sensitivity and the area under the receiver operating characteristic curve (AUC).ResultsA total of 10 362 deliveries were reviewed, with 224 cases and 278 controls included in the study. The NICHD categorizations showed reasonable discriminatory ability (AUC = 0.727). The non-NICHD parameters measured during the 30-min fetal monitoring, total deceleration area (AUC = 0.807, 95% CI: 0.770, 0.845) and total reperfusion time (AUC = 0.750, 95% CI: 0.707, 0.792), exhibited higher discriminatory ability. The slope of the descending limb of the fetal heart rate of the last deceleration curve had the best AUC value (0.853, 95% CI: 0.816, 0.889). The combination of total deceleration area or total reperfusion time with the slope demonstrated high discriminatory ability (AUC = 0.908, 95% CI: 0.882, 0.933; specificities of 71.6% and 72.7% for a sensitivity of 90%).ConclusionsThe slope of the descending limb of the fetal heart rate of the last deceleration curve is the strongest predictor of fetal acidosis, but its combination with the total reperfusion time shows better clinical utility. Slope combined with total reperfusion time exhibit higher discriminatory ability to detect fetal acidosis in comparison to previous categorizations and better clinical utility to predict fetal acidosis.

Risk-stratified pathways (RSPs) are recommended by the European Association of Uro-logy (EAU) to improve the early detection of clinically significant prostate cancer (csPCa). RSPs can reduce magnetic resonance imaging (MRI) demand, prostate biopsies, and the over-detection of insignificant PCa (iPCa). Our goal is to analyze the efficacy and cost-effectiveness of several RSPs by using sequential stratifications from the serum prostate-specific antigen level and digital rectal examination, the Barcelona risk calculators (BCN-RCs), MRI, and Proclarix™. In a cohort of 567 men with a serum PSA level above 3.0 ng/mL who underwent multiparametric MRI (mpMRI) and targeted and/or systematic biopsies, the risk of csPCa was retrospectively assessed using Proclarix™ and BCN-RCs 1 and 2. Six RSPs were compared with those recommended by the EAU that, stratifying men from MRI, avoided 16.7% of prostate biopsies with a prostate imaging–reporting and data system score of <3, with 2.6% of csPCa cases remaining undetected. The most effective RSP avoided mpMRI exams in men with a serum PSA level of >10 ng/mL and suspicious DRE, following stratifications from BCN-RC 1, mpMRI, and Proclarix™. The demand for mpMRI decreased by 19.9%, prostate biopsies by 19.8%, and over-detection of iPCa by 22.7%, while 2.6% of csPCa remained undetected as in the recommended RSP. Cost-effectiveness remained when the Proclarix™ price was assumed to be below EUR 200.

PURPOSE:To analyze the reduction in multiparametric magnetic resonance imaging (mpMRI) demand and prostate biopsies after the hypothetical implementation of the Barcelona risk-stratified pathway (BCN-RSP) in a population of the clinically significant prostate cancer (csCaP) early detection program in Catalonia.MATERIALS AND METHODS:A retrospective comparation between the hypothetical application of the BCN-RSP and the current pathway, which relied on pre-biopsy mpMRI and targeted and/or systematic biopsies, was conducted. The BCN-RSP stratify men with suspected CaP based on a prostate specific antigen (PSA) level >10 ng/ml and a suspicious rectal examination (DRE), and the Barcelona-risk calculator 1 (BCN-RC1) to avoid mpMRI scans. Subsequently, candidates for prostate biopsy following mpMRI are selected based on the BCN-RC2. This comparison involved 3,557 men with serum PSA levels > 3.0 ng/ml and/or suspicious DRE. The population was recruited prospectively in 10 centers from January 2021 and December 2022. CsCaP was defined when grade group ≥ 2.RESULTS:CsCaP was detected in 1,249 men (35.1%) and insignificant CaP was overdeteced in 498 (14%). The BCN-RSP would have avoid 705 mpMRI scans (19.8%), and 697 prostate biopsies (19.6%), while 61 csCaP (4.9%) would have been undetected. The overdetection of insignificant CaP would have decrease in 130 cases (26.1%), and the performance of prostate biopsy for csCaP detection would have increase to 41.5%.CONCLUSION:The application of the BCN-RSP would reduce the demand for mpMRI scans and prostate biopsies by one fifth while less than 5% of csCaP would remain undetected. The overdetection of insignificant CaP would decrease by more than one quarter and the performance of prostate biopsy for csCaP detection would increase to higher than 40%.

To validate the Barcelona-magnetic resonance imaging predictive model (BCN-MRI PM) for clinically significant prostate cancer (csPCa) in Catalonia, a Spanish region with 7.9 million inhabitants. Additionally, the BCN-MRI PM is validated in men receiving 5-alpha reductase inhibitors (5-ARI). A population of 2,212 men with prostate-specific antigen serum level > 3.0 ng/ml and/or a suspicious digital rectal examination who underwent multiparametric MRI and targeted and/or systematic biopsies in the year 2022, at ten participant centers of the Catalonian csPCa early detection program, were selected. 120 individuals (5.7

Background: Magnetic resonance imaging (MRI)-based risk calculators (MRI-RCs) individualise the likelihood of clinically significant prostate cancer (csPCa) and improve candidate selection for prostate biopsy beyond the Prostate Imaging Reporting and Data System (PI-RADS). Objective: To compare the Barcelona (BCN) and Rotterdam (ROT) MRI-RCs in an entire population and according to the PI-RADS categories. Design, setting, and participants: A prospective comparison of BCN-and ROT-RC in 946 men with suspected prostate cancer in whom systematic biopsy was per-formed, as well as target biopsies of PI-RADS >3 lesions. Outcome measurements and statistical analysis: Saved biopsies and undetected csPCa (grade group >2) were determined. Results and limitations: The csPCa detection was 40.8%. The median risks of csPCa from BCN-and ROT-RC were, respectively, 67.1% and 25% in men with csPCa, whereas 10.5% and 3% in those without csPCa (p < 0.001). The areas under the curve were 0.856 and 0.844, respectively (p = 0.116). BCN-RC showed a higher net benefit and clinical utility over ROT-RC. Using appropriate thresholds, respectively, 75% and 80% of biopsies were needed to identify 50% of csPCa detected in men with PI-RADS <3, whereas 35% and 21% of biopsies were saved, missing 10% of csPCa detected in men with PI-RADS 3. BCN-RC saved 15% of biopsies, missing 2% of csPCa in men with PI-RADS 4, whereas ROT-RC saved 10%, missing 6%. No RC saved biopsies without missing csPCa in men with PI-RADS 5. Conclusions: ROT-RC provided a lower and narrower range of csPCa probabilities than BCN-RC. BCN-RC showed a net benefit over ROT-RC in the entire population. However, BCN-RC was useful in men with PI-RADS 3 and 4, whereas ROT-RC was useful only in those with PI-RADS 3. No RC seemed to be helpful in men with neg-ative MRI and PI-RADS 5. Patient summary: Barcelona risk calculator was more helpful than Rotterdam risk calculator to select candidates for prostate biopsy. & COPY; 2023 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).

Objective: This study aims to build a multistate model and describe a predictive tool for estimating the daily number of intensive care unit (ICU) and hospital beds occupied by patients with coronavirus 2019 disease (COVID-19). Material and methods: The estimation is based on the simulation of patient trajectories using a multistate model where the transition probabilities between states are estimated via competing risks and cure models. The input to the tool includes the dates of COVID-19 diagnosis, admission to hospital, admission to ICU, discharge from ICU and discharge from hospital or death of positive cases from a selected initial date to the current moment. Our tool is validated using 98,496 cases positive for severe acute respiratory coronavirus 2 extracted from the Aragón Healthcare Records Database from July 1, 2020 to February 28, 2021. Results: The tool demonstrates good performance for the 7- and 14-days forecasts using the actual positive cases, and shows good accuracy among three scenarios corresponding to different stages of the pandemic: 1) up-scenario, 2) peak-scenario and 3) down-scenario. Long term predictions (two months) also show good accuracy, while those using Holt-Winters positive case estimates revealed acceptable accuracy to day 14 onwards, with relative errors of 8.8%. Discussion: In the era of the COVID-19 pandemic, hospitals must evolve in a dynamic way. Our prediction tool is designed to predict hospital occupancy to improve healthcare resource management without information about clinical history of patients. Conclusions: Our easy-to-use and freely accessible tool (https://github.com/peterman65) shows good performance and accuracy for forecasting the daily number of hospital and ICU beds required for patients with COVID-19.

Although linearly combining multiple variables can provide adequate diagnostic performance, certain algorithms have the limitation of being computationally demanding when the number of variables is sufficiently high. Liu et al. proposed the min–max approach that linearly combines the minimum and maximum values of biomarkers, which is computationally tractable and has been shown to be optimal in certain scenarios. We developed the Min–Max–Median/IQR algorithm under Youden index optimisation which, although more computationally intensive, is still approachable and includes more information. The aim of this work is to compare the performance of these algorithms with well-known Machine Learning algorithms, namely logistic regression and XGBoost, which have proven to be efficient in various fields of applications, particularly in the health sector. This comparison is performed on a wide range of different scenarios of simulated symmetric or asymmetric data, as well as on real clinical diagnosis data sets. The results provide useful information for binary classification problems of better algorithms in terms of performance depending on the scenario.

Purpose To analyze the variability, associated actors, and the design of nomograms for individualized testosterone recovery after cessation of androgen deprivation therapy (ADT). Materials and Methods A longitudinal study was carried out with 208 patients in the period 2003 to 2019. Castrated and normogonadic testosterone levels were defined as 0.5 and 3.5 ng/mL, respectively. The cumulative incidence curve described the recovery of testosterone. Univariate and multivariate analyzes were performed to predict testosterone recovery with candidate prognostic factors prostate-specific antigen at diagnosis, clinical stage, Gleason score from biopsy, age at cessation of ADT, duration of ADT, primary therapy and use of LHRH (luteinizing hormone-releasing hormone) agonists. Results The median follow-up duration in the study was 80 months (interquartile range, 49–99 mo). Twenty-five percent and 81% of patients did not recover the castrate and normogonadic levels, respectively. Duration of ADT and age at ADT cessation were significant predictors of testosterone recovery. We built two nomograms for testosterone recovery at 12, 24, 36, and 60 months. The castration recovery model had good calibration. The C-index was 0.677, with area under the receiver operating characteristic curve (AUC-ROC) of 0.736, 0.783, 0.782, and 0.780 at 12, 24, 36, and 60 months, respectively. The normogonadic recovery model overestimated the higher values of probability of recovery. The Cindex was 0.683, with AUC values of 0.812, 0.711, 0.708 and 0.693 at 12, 24, 36, and 60 months, respectively. Conclusions Depending on the age of the patient and the length of treatment, clinicians may stop ADT and the castrated testosterone level will be maintained or, if the course of treatment has been short, we can estimate if it will return to normogonadic levels.

IntroductionFrom genome wide association study (GWAS) a large number of single nucleotide polymorphisms (SNPs) have previously been associated with blood pressure (BP) levels. A combination of SNPs, forming a genetic risk score (GRS) could be considered as a useful genetic tool to identify individuals at risk of developing hypertension from early stages in life. Therefore, the aim of our study was to build a GRS being able to predict the genetic predisposition to hypertension (HTN) in European adolescents. MethodsData were extracted from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study. A total of 869 adolescents (53% female), aged 12.5-17.5, with complete genetic and BP information were included. The sample was divided into altered (>= 130 mmHg for systolic and/or >= 80 mmHg for diastolic) or normal BP. Based on the literature, a total of 1.534 SNPs from 57 candidate genes related with BP were selected from the HELENA GWAS database. ResultsFrom 1,534 SNPs available, An initial screening of SNPs univariately associated with HTN (p < 0.10) was established, to finally obtain a number of 16 SNPs significantly associated with HTN (p < 0.05) in the multivariate model. The unweighted GRS (uGRS) and weighted GRS (wGRS) were estimated. To validate the GRSs, the area under the curve (AUC) was explored using ten-fold internal cross-validation for uGRS (0.802) and wGRS (0.777). Further covariates of interest were added to the analyses, obtaining a higher predictive ability (AUC values of uGRS: 0.879; wGRS: 0.881 for BMI z-score). Furthermore, the differences between AUCs obtained with and without the addition of covariates were statistically significant (p < 0.05). ConclusionsBoth GRSs, the uGRS and wGRS, could be useful to evaluate the predisposition to hypertension in European adolescents.

Background Small for gestational age (SGA) perform a postnatal catch-up growth to recover their genetic trajectory. We studied the postnatal catch-up growth pattern of fetuses born with an appropriate-for-gestational-age (AGA) weight but with fetal growth deceleration (FGD) to explore whether they catch up. Methods Nine hundred and sixty-six newborns at Villalba University General Hospital (HUGV), were followed from 34 to 37 weeks to birth. Z -scores, adjusted for sex and age, of weight, length, and BMI at 3, 6, 9, and 12 months were calculated. We define catch-up as an increase in z -score greater than 0.67 SD in the growth curves. Results AGA FGD had lower mean weight and length than AGA non-FGD at all time points; BMI was lower until 3 months. AGA FGD had a lower weight, length, and BMI z -score (until 9, 6 months, and at birth, respectively) than AGA non-FGD. AGA FGD newborns had a significantly increased likelihood of weight catch-up at 3 months (OR 1.79; 95% CI: 1.16, 2.78; p = 0.009) and BMI in all investigated periods (OR 1.90; 95% CI 1.30, 2.78; p < 0.001 at 3 months), compared to AGA non-FGD newborns. Conclusions AGA FGD newborns perform catch-up growth, especially in weight and BMI, in the first year of life, compared to AGA non-FGD. Impact Appropriate-for-gestational-age (AGA) newborns with fetal growth deceleration (FGD), between the third trimester of pregnancy and delivery, present a lower weight and height, during the first year of life, compared to AGA non-FGD. Appropriate-for-gestational-age (AGA) newborns with fetal growth deceleration (FGD), between the third trimester of pregnancy and delivery, present a higher likelihood of weight catch-up in the first 3 months of life and of BMI in the first year compared to AGA non-FGD. AGA FGD experienced early weight and BMI catch-up, especially in the first 3 months of life, like SGA. This finding should be considered in the future follow-up.

BJUI CompassEarly View RESEARCH LETTEROpen Access A risk-organised model for clinically significant prostate cancer early detection Juan Morote, Corresponding Author Juan Morote [email protected] orcid.org/0000-0002-2168-323X Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, Spain Department of Urology, Hospital Miguel Servet, IIS-Aragon, Zaragoza, Spain Correspondence Juan Morote, Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain. Email: [email protected]Search for more papers by this authorÁngel Borque-Fernando, Ángel Borque-Fernando orcid.org/0000-0003-0178-4567 Department of Urology, Hospital Miguel Servet, IIS-Aragon, Zaragoza, SpainSearch for more papers by this authorMarina Triquell, Marina Triquell Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, SpainSearch for more papers by this authorJosé M. Abascal, José M. Abascal Department of Urology, Parc de Salut Mar, Barcelona, Spain Department of Surgery, Universitat Pompeu Fabra, Barcelona, SpainSearch for more papers by this authorPol Servian, Pol Servian Department of Urology, Hospital Germans Trias i Pujol, Badalona, SpainSearch for more papers by this authorJacques Planas, Jacques Planas Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, SpainSearch for more papers by this authorOlga Mendez, Olga Mendez Urology Biomedical Research Unit, Vall d'Hebron Research Institute, Barcelona, SpainSearch for more papers by this authorLuis M. Esteban, Luis M. Esteban Department of Applied Mathematics, Escuela Universitaria Politécnica La Almunia, Universidad de Zaragoza, Zaragoza, SpainSearch for more papers by this authorEnrique Tilla, Enrique Tilla orcid.org/0000-0001-9401-0872 Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, SpainSearch for more papers by this author Juan Morote, Corresponding Author Juan Morote [email protected] orcid.org/0000-0002-2168-323X Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, Spain Department of Urology, Hospital Miguel Servet, IIS-Aragon, Zaragoza, Spain Correspondence Juan Morote, Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain. Email: [email protected]Search for more papers by this authorÁngel Borque-Fernando, Ángel Borque-Fernando orcid.org/0000-0003-0178-4567 Department of Urology, Hospital Miguel Servet, IIS-Aragon, Zaragoza, SpainSearch for more papers by this authorMarina Triquell, Marina Triquell Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, SpainSearch for more papers by this authorJosé M. Abascal, José M. Abascal Department of Urology, Parc de Salut Mar, Barcelona, Spain Department of Surgery, Universitat Pompeu Fabra, Barcelona, SpainSearch for more papers by this authorPol Servian, Pol Servian Department of Urology, Hospital Germans Trias i Pujol, Badalona, SpainSearch for more papers by this authorJacques Planas, Jacques Planas Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, SpainSearch for more papers by this authorOlga Mendez, Olga Mendez Urology Biomedical Research Unit, Vall d'Hebron Research Institute, Barcelona, SpainSearch for more papers by this authorLuis M. Esteban, Luis M. Esteban Department of Applied Mathematics, Escuela Universitaria Politécnica La Almunia, Universidad de Zaragoza, Zaragoza, SpainSearch for more papers by this authorEnrique Tilla, Enrique Tilla orcid.org/0000-0001-9401-0872 Department of Urology, Vall d'Hebron Hospital, Barcelona, Spain Department of Surgery, Universitat Autònoma de Barcelona, Barcelona, SpainSearch for more papers by this author First published: 07 March 2023 https://doi.org/10.1002/bco2.230 Juan Morote and Ángel Borque-Fernando have equal contribution as first author. Luis M. Esteban and Enrique Tilla have equal contribution as last author. AboutSectionsPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Evidence that specific mortality of PCa decrease when clinically significant PCa (csPCa) is early detected has moved the focus of PCa screening towards csPCa.1 This paradigm shift has occurred since the spread of multiparametric magnetic resonance imaging (mpMRI), which allows to avoid unnecessary prostate biopsies and overdetection of insignificant PCa (iPCa) in a cost-effective way.2, 3 However, because suspicion of PCa remains based on elevated serum prostate-specific antigen (PSA) and/or abnormal digital rectal examination (DRE), there has been an increased demand for mpMRI that cannot always be performed. In experienced centres, biparametric MR has replaced mpMRI, reducing scan time by a quarter and maintaining the reproducibility and accuracy of the Prostate Imaging Reporting and Data System (PI-RADS).1 The recommendation of prostate biopsy is currently made according to the PI-RADS category. Experienced radiologists, reporting with an updated version of PI-RADS, obtain a negative predictive value of mpMRI that reaches up to 95%, which makes it possible to avoid prostate biopsies in men with suspected PCa with a PI-RADS <3. MRI-targeted biopsies of suspicious lesions (PI-RADS ≥3) improve the sensitivity of systematic biopsies for csPCa. However, uncertain scenarios after mpMRI, having high rates of unnecessary biopsies and/or overdetection of iPCa, remain, and then PSA density (PSAD), new markers and predictive models are recommended to improve the selection of candidates for prostate biopsy.4 The European Association of Urology currently recommends the design of csPCa risk-organised models (ROMs) by sequencing available tools to reduce the demand of mpMRI exams, and unnecessary prostate biopsies ones mpMRI is performed.1 Because prostate volume is a powerful predictor of csPCa and usually transrectal ultrasound is not performed to assess prostate volume before mpMRI, its assessment through DRE-prostate volume category is now recommended.5 There is also evidence that men with serum PSA higher than 10 ng/mL and abnormal DRE do not benefit from MRI-targeted biopsies, since systematic biopsies can detect all existing csPCa.6 The Barcelona-risk calculator 1 (BCN RC-1) has been developed and externally validated to individualise the risk of csPCa to avoid the demand of mpMRI exams,7 as well as the BCN-RC 2 to predict the risk of csPCa after mpMRI and avoid unnecessary biopsies.7 Both risk calculators are available at https://mripcaprediction.shinyapps.io/MRIPCaPrediction/. The present study aims to compare the current standard approach for early detection of csPCa, based on MRI-targeted biopsies when PI-RADS lesions ≥3 and systematic biopsy,1 with a ROM designed to avoiding mpMRI exams in men with serum PSA over than 10.0 ng/mL and abnormal DRE, in addition to rule out mpMRI exams when the risk of csPCa from the BCN-RC 1 is lower than 12%.6, 7 Once mpMRI is performed, prostate biopsy will be scheduled in men having a risk of csPCa from the BCN-RC 2 higher than 4%.8 The selection of proposed thresholds was made to avoid missing no more than 10% of csPCa detected. The 95% csPCa sensitivity thresholds of BCN RC-1 and BCN RC-2, in those men in whom they were applied, were selected. A probability analysis of avoiding mpMRI exams and prostate biopsies as well as missed csPCa has been performed. A series of 946 men with serum PSA > 3.0 ng/mL and/or abnormal DRE was recruited prospectively in two academic centres of cities from the Barcelona metropolitan area (PSM and GTiP), between January 1 of 2018 and December 31 of 2021. This series was independent from those for the development of BCN-RC 1 and BCN-RC 2 recruited at VHH, between January 1 of 2016 and December 31 of 2019.7, 8 All men were scheduled to 3-T mpMRI and two- to four-core transrectal ultrasound (TRUS) cognitive MRI-targeted biopsies to PI-RADSv.2 ≥ 3 lesions and 12-core TRUS systematic biopsy; 12-core TRUS systematic biopsy was performed when PI-RADSv.2 < 3. This project was approved by the institutional ethics committee of VHH (PRAG-317/2017), and the analysis was performed on anonymised databases. CsPCa, defined as the International Society of Uro-pathology grade group 2 or higher, was detected in 386 men (40.8%). The median age of participants was 67 years with an interquartile range (IQR) between 61 and 75. The median serum PSA was 7.2 ng/mL (IQR: 5.5–10.9), 32.5% of participants had abnormal DRE, and 31% had previous negative prostate biopsy. CsPCa was detected in 17.9% of the 235 men with PI-RADS <3 (24.8%); in 20.4% of the 301 men with PI-RADS 3 (21.2%); in 51.9% of the men with PI-RADS 4 (12.6%); and 84% of those with PI-RADS 5 (12.6%). In the subset of 124 men with serum PSA > 10.0 ng/mL and abnormal DRE, csPCa was detected in 106 (85.6%). The probability analyses of the standard approach and the proposed ROM are presented in Figure 1. The standard approach required mpMRI in all participants, 235 (24.8%) of prostate biopsies were avoided in those men with PI-RADS <3, and 42 (10.9%) of overall csPCa detected were missed. Among the 711 participants biopsied (75.2%) csPCa was detected in 344 (48.4%). The proposed ROM initially ruled out mpMRI in 124 men with serum PSA > 10.0 ng/mL and abnormal DRE (13.1% of all participants), in whom systematic biopsies identified all 106 csPCa detected, which represented 27.5% of all csPCa detected. The BCN-RC 1 ruled out mpMRI exams in 167 men (17.7%), missing 13 csPCa (3.4%). After mpMRI, performed in 655 men (69.2%), the BCN RC-2 ruled out prostate biopsy in 100 men, in whom 13 detected csPCa were missed (3.4%). Among the 555 men finally biopsied (63.3%), csPCa was detected in 254 (45.8%). The ROM would rule out 30.8% of mpMRI exams, and 28.2% of prostate biopsies, whereas 6.7% of overall csPCa would be undetected. FIGURE 1Open in figure viewerPowerPoint Flow chart description of standard approach of csPCa, and the proposed risk-organised model, with intermediate and overall results according to rule out mpMRI exams, avoided prostate biopsies and missed csPCa detection. Data are expressed in number and (%) of all MRI exams and prostate biopsies performed and csPCa detected. Abbreviations: BCN, Barcelona; csPCa, clinically significant PCa; DRE, digital rectal examination; mpMRI, multiparametric magnetic resonance imaging; PB, prostate biopsies; PCa, prostate cancer; PI-RADS, Prostate Imaging Report and Data System; PSA, prostate-specific antigen; RC, risk calculator. aProposed thresholds. The proposed ROM was able to rule out almost one-third of mpMRI exams and the percentage of saved biopsies increased from the 24.8% observed with the standard approach to the 28.2%, whereas the percentage of undetected csPCa decreased from 10.9 to 6.7 respectively. Remmers et al. have recently reported the results with an ROM based on sequencing the Rotterdam RC-3 and the Rotterdam MRI-RC in the MRI arm of the PRECISION trial, which was carried out in biopsy-naïve men. After recalibration and adjustment of csPCa thresholds in both predictive models, this ROM was able to rule out 13% of mpMRI exams, decreasing the number of prostate biopsies in 9% and missing 8.5% of csPCa detected in the 134 men with PI-RADS ≥3 in whom MRI-targeted biopsies of suspicious lesions and systematic biopsy were performed.9 The present study confirms the effectiveness of the proposed ROM to improve the early detection of csPCa by reducing the demand of mpMRI exams and unnecessary prostate biopsies. The missing rate of csPCa of the standard approach that avoids systematic biopsy in men with negative mpMRI also decreased. The main limitation for the use of the proposed ROM is the need of validation in the populations where it will be implemented. Now, following the recommendation of EAU, this ROM is ready to be used in the metropolitan area of Barcelona, and validation in Catalonia (Spain), a country with seven and half million inhabitants, is ongoing. Ideally, a randomised trial would be necessary to generate high evidence level. AUTHOR CONTRIBUTIONS Juan Morote, Ángel Borque-Fernando and Luis M. Esteban conceptualised the idea. Marina Triquell, José M. Abascal, Pol Servian, Jacques Planas, Olga Mendez and Enrique Tilla developed the concept. Juan Morote wrote the first draft of the manuscript. All authors were involved in editing, critical review and final approval of the manuscript. ACKNOWLEDGEMENTS The Instituto de Salut Carlos III (SP) and European Union financed this project, ref. PI20/01666. CONFLICT OF INTEREST STATEMENT The authors have no conflict of interest to declare. REFERENCES 1Van Poppel H, Hogenhout R, Albers P, van den Bergh RCN, Barentsz JO, Roobol MJ. A European model for an organised risk-stratified early detection Programme for prostate cancer. Eur Urol Oncol. 2021; 4(5): 731– 9. https://doi.org/10.1016/j.euo.2021.06.006 2Schoots IG, Padhani AR, Rouvière O, Barentsz JO, Richenberg J. Analysis of magnetic resonance imaging-directed biopsy strategies for changing the paradigm of prostate cancer diagnosis. Eur Urol Oncol. 2020; 3(1): 32– 41. https://doi.org/10.1016/j.euo.2019.10.001 3Donato P, Morton A, Yaxley J, Teloken PE, Coughlin G, Esler R, et al. Improved detection and reduced biopsies: The effect of a multiparametric magnetic resonance imaging-based triage prostate cancer pathway in a public teaching hospital. World J Urol. 2020; 38(2): 371– 9. https://doi.org/10.1007/s00345-019-02774-y 4Osses DF, Roobol MJ, Schoots IG. Prediction medicine: Biomarkers, risk calculators and magnetic resonance imaging as risk stratification tools in prostate cancer diagnosis. Int J Mol Sci. 2019; 20(7):1637. https://doi.org/10.3390/ijms20071637 5Roobol MJ, van Vugt HA, Loeb S, Zhu X, Bul M, Bangma CH, et al. Prediction of prostate cancer risk: The role of prostate volume and digital rectal examination in the ERSPC risk calculators. Eur Urol. 2012; 61(3): 577– 83. https://doi.org/10.1016/j.eururo.2011.11.012 6Morote J, Celma A, Roche S, de Torres IM, Mast R, Semedey ME, et al. Who benefits from multiparametric magnetic resonance imaging after suspicion of prostate cancer. Eur Urol Oncol. 2019; 2(6): 664– 9. https://doi.org/10.1016/j.euo.2018.11.009 7Morote J, Borque-Fernando Á, Triquell M, Campistol M, Celma A, Regis L, et al. A clinically significant prostate cancer predictive model using digital rectal examination prostate volume category to stratify initial prostate cancer suspicion and reduce magnetic resonance imaging demand. Cancers (Basel). 2022; 14(20):5100. https://doi.org/10.3390/cancers14205100 8Morote J, Borque-Fernando A, Triquell M, Celma A, Regis L, Escobar M, et al. The Barcelona predictive model of clinically significant prostate cancer. Cancers (Basel). 2022; 14(6):1589. https://doi.org/10.3390/cancers14061589 9Remmers S, Kasivisvanathan V, Verbeek JFM, Moore CM, Roobol MJ, ERSPC RSGPRECISIONIG. Reducing biopsies and magnetic resonance imaging scans during the diagnostic pathway of prostate cancer: Applying the Rotterdam prostate cancer risk calculator to the PRECISION trial data. Eur Urol Open Sci. 2022; 36: 1– 8. https://doi.org/10.1016/j.euros.2021.11.002 Early ViewOnline Version of Record before inclusion in an issue FiguresReferencesRelatedInformation

BACKGROUND:Hepatic disorders are often complex and multifactorial, modulated by genetic and environmental determinants. During the last years, the hepatic disease has been progressively established from early stages in life. The use of genetic risk scores (GRS) to predict the genetic susceptibility to a particular phenotype among youth has gained interest in recent years. Moreover, the alanine aminotransferase (ALT) blood biomarker is often considered as hepatic screening tool, in combination with imaging techniques. The aim of the present study was to develop an ALT-specific GRS to help in the evaluation of hepatic damage risk in European adolescents. METHODS:A total of 972 adolescents (51.3% females), aged 12.5-17.5 years, from the Healthy Lifestyle in Europe by Nutrition in Adolescence study were included in the analyses. The sample incorporated adolescents in all body mass index (BMI) categories and was divided considering healthy/unhealthy ALT levels, using sex-specific cut-off points. From 1212 a priori ALT-related single nucleotide polymorphisms (SNPs) extracted from candidate gene selection, a first screening of 234 SNPs univariately associated was established, selecting seven significant SNPs (p < .05) in the multivariate model. An unweighted GRS (uGRS) was developed by summing the number of reference alleles, and a weighted GRS (wGRS), by multiplying each allele to its estimated coefficient. RESULTS:The uGRS and wGRS were significantly associated with ALT (p < .001). The area under curve was obtained integrating BMI as clinical factor, improving the predictive ability for uGRS (.7039) and wGRS (.7035), using 10-fold internal cross-validation. CONCLUSIONS:Considering BMI status, both GRSs could contribute as complementary tools to help in the early diagnosis of hepatic damage risk in European adolescents.

Electronic fetal monitoring (EFM) is widely used in intrapartum care as the standard method for monitoring fetal well-being. Our objective was to employ machine learning algorithms to predict acidemia by analyzing specific features extracted from the fetal heart signal within a 30 min window, with a focus on the last deceleration occurring closest to delivery. To achieve this, we conducted a case–control study involving 502 infants born at Miguel Servet University Hospital in Spain, maintaining a 1:1 ratio between cases and controls. Neonatal acidemia was defined as a pH level below 7.10 in the umbilical arterial blood. We constructed logistic regression, classification trees, random forest, and neural network models by combining EFM features to predict acidemia. Model validation included assessments of discrimination, calibration, and clinical utility. Our findings revealed that the random forest model achieved the highest area under the receiver characteristic curve (AUC) of 0.971, but logistic regression had the best specificity, 0.879, for a sensitivity of 0.95. In terms of clinical utility, implementing a cutoff point of 31% in the logistic regression model would prevent unnecessary cesarean sections in 51% of cases while missing only 5% of acidotic cases. By combining the extracted variables from EFM recordings, we provide a practical tool to assist in avoiding unnecessary cesarean sections.