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      Long-term functional outcomes and surgical retreatment after thulium laser enucleation of the prostate: A 10-year follow-up study

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          ABSTRACT

          Background:

          To evaluate the 10-year functional outcomes (primary) and frequency and predictors of BPH surgical retreatment (secondary) after ThuLEP.

          Materials and Methods:

          A single-center retrospective analysis of consecutive patients undergoing ThuLEP between 2010 and 2013 was performed. Inclusion criteria were: age ≥ 40 years, prostate volume (PV) ≥ 80 mL, International Prostate Symptom Score (IPSS)-Total score ≥ 8 points. IPSS-Total score was the primary outcome, and BPH surgical retreatment rate was the secondary outcome. Paired t-test, McNemar test, and Wilcoxon signed-rank test were used to compare variables. Logistic regression analysis was performed to evaluate predictors of surgical retreatment.

          Results:

          A total of 410 patients with a mean ±SD age of 63.9 ± 9.7 years and a PV of 115.6 ± 28.6 mL were included. Mean ±SD follow-up was 108.2 ± 29.6 months. IPSS-Total score was significantly improved at 1 year compared to baseline (23.3 ± 4.7 vs. 10.3 ± 3.8; p<0.001). It was similar after 5 years (10.5 ± 3.6 vs. 10.7 ± 5.0; p=0.161), with a significant worsening at 10 years (10.3 ±4.8 vs. 13.8 ±4.5; p=0.042) but remaining statistically and clinically better than baseline (13.8 ±4.5 vs. 22.1 ±4.3; p<0.001). After 10 years, 21 (5.9%) patients had undergone BPH reoperation. Baseline PV (adjusted OR 1.27, 95% CI 1.09-1.41; p<0.001) and time from BPH surgery (adjusted OR 1.32, 95% CI 1.15-1.43; p<0.001) were predictors of BPH surgical retreatment.

          Conclusions:

          ThuLEP is associated with optimal functional outcomes and a low frequency of BPH surgical retreatment in the long-term. Baseline PV and time from surgery were predictors of BPH reoperation.

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          Understanding survival analysis: Kaplan-Meier estimate

          Kaplan-Meier estimate is one of the best options to be used to measure the fraction of subjects living for a certain amount of time after treatment. In clinical trials or community trials, the effect of an intervention is assessed by measuring the number of subjects survived or saved after that intervention over a period of time. The time starting from a defined point to the occurrence of a given event, for example death is called as survival time and the analysis of group data as survival analysis. This can be affected by subjects under study that are uncooperative and refused to be remained in the study or when some of the subjects may not experience the event or death before the end of the study, although they would have experienced or died if observation continued, or we lose touch with them midway in the study. We label these situations as censored observations. The Kaplan-Meier estimate is the simplest way of computing the survival over time in spite of all these difficulties associated with subjects or situations. The survival curve can be created assuming various situations. It involves computing of probabilities of occurrence of event at a certain point of time and multiplying these successive probabilities by any earlier computed probabilities to get the final estimate. This can be calculated for two groups of subjects and also their statistical difference in the survivals. This can be used in Ayurveda research when they are comparing two drugs and looking for survival of subjects.
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            Logistic regression: a brief primer.

            Regression techniques are versatile in their application to medical research because they can measure associations, predict outcomes, and control for confounding variable effects. As one such technique, logistic regression is an efficient and powerful way to analyze the effect of a group of independent variables on a binary outcome by quantifying each independent variable's unique contribution. Using components of linear regression reflected in the logit scale, logistic regression iteratively identifies the strongest linear combination of variables with the greatest probability of detecting the observed outcome. Important considerations when conducting logistic regression include selecting independent variables, ensuring that relevant assumptions are met, and choosing an appropriate model building strategy. For independent variable selection, one should be guided by such factors as accepted theory, previous empirical investigations, clinical considerations, and univariate statistical analyses, with acknowledgement of potential confounding variables that should be accounted for. Basic assumptions that must be met for logistic regression include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers. Additionally, there should be an adequate number of events per independent variable to avoid an overfit model, with commonly recommended minimum "rules of thumb" ranging from 10 to 20 events per covariate. Regarding model building strategies, the three general types are direct/standard, sequential/hierarchical, and stepwise/statistical, with each having a different emphasis and purpose. Before reaching definitive conclusions from the results of any of these methods, one should formally quantify the model's internal validity (i.e., replicability within the same data set) and external validity (i.e., generalizability beyond the current sample). The resulting logistic regression model's overall fit to the sample data is assessed using various goodness-of-fit measures, with better fit characterized by a smaller difference between observed and model-predicted values. Use of diagnostic statistics is also recommended to further assess the adequacy of the model. Finally, results for independent variables are typically reported as odds ratios (ORs) with 95% confidence intervals (CIs). © 2011 by the Society for Academic Emergency Medicine.
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              Management of Lower Urinary Tract Symptoms Attributed to Benign Prostatic Hyperplasia: AUA GUIDELINE PART I—Initial Work-up and Medical Management

              Benign prostatic hyperplasia (BPH) is a histologic diagnosis describing proliferation of smooth muscle and epithelial cells within the prostatic transition zone. The prevalence and severity of lower urinary tract symptoms (LUTS) in aging men are progressive and impact the health and welfare of society. This revised Guideline provides a useful reference on effective evidence-based management of male LUTS/BPH. See the accompanying algorithm for a summary of the procedures detailed in the Guideline (figures 1 and 2[Figure: see text][Figure: see text]).
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                Author and article information

                Journal
                Int Braz J Urol
                Int Braz J Urol
                ibju
                International Brazilian Journal of Urology : Official Journal of the Brazilian Society of Urology
                Sociedade Brasileira de Urologia
                1677-5538
                1677-6119
                10 March 2024
                May-Jun 2024
                : 50
                : 3
                : 309-318
                Affiliations
                [1 ] orgnameUniversity of Campania "Luigi Vanvitelli" orgdiv1Unit of Urology, Child and General and Specialized Surgery orgdiv2Department of Woman Naples Italy originalDepartment of Woman - Unit of Urology, Child and General and Specialized Surgery, University of Campania "Luigi Vanvitelli", Naples, Italy;
                [2 ] orgnameUniversity of Naples "Federico II" orgdiv1Urology Unit orgdiv2Department of Neurosciences, Reproductive Sciences and Odontostomatology Naples Italy originalDepartment of Neurosciences, Reproductive Sciences and Odontostomatology, Urology Unit, University of Naples "Federico II", Naples, Italy;
                [3 ] orgnameUniversity of Verona orgdiv1Department of Urology Verona Italy originalDepartment of Urology, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy;
                [4 ] orgnameRush University Medical Center orgdiv1Department of Urology Chicago IL USA originalDepartment of Urology, Rush University Medical Center, Chicago, IL, USA;
                [5 ] orgnameUrology Complex Unit-ASL Napoli 2 Nord "Santa Maria delle Grazie" Hospital Pozzuoli Italy originalUrology Complex Unit-ASL Napoli 2 Nord "Santa Maria delle Grazie" Hospital, Pozzuoli, Italy
                Author notes
                Correspondence address: Francesco Ditonno, MD Department of Urology, University of Verona, Azienda Ospedaliera Universitaria Integrata Verona Piazzale Aristide Stefani, 1, 37126 Verona, Italy Telephone: + 39 340 634-5849 E-mail: francesco.ditonno@ 123456icloud.com

                CONFLICT OF INTEREST

                None declared.

                Author information
                https://orcid.org/0009-0005-0126-4731
                Article
                S1677-5538.IBJU.2024.0039
                10.1590/S1677-5538.IBJU.2024.0039
                11152334
                38446905
                dc18d32f-0de6-4779-beb6-1d4147ca62ee

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 January 2024
                : 05 February 2024
                Page count
                Figures: 2, Tables: 3, Equations: 0, References: 22, Pages: 10
                Categories
                Original Article

                prostatic hyperplasia,surgical procedures, operative,thulium

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