1,721,219 research outputs found
The search for better prognostic factors for men treated for localized prostate cancer continues
No full textImpact of medical treatments for male lower urinary tract symptoms due to benign prostatic hyperplasia on ejaculatory function: a systematic review and meta-analysis.
No full textIntroduction: Several drugs, currently used to treat lower urinary tract symptoms (LUTS) due to benign prostatic hyperplasia (BPH), can be associated with bothersome sexual side effects, including ejaculatory dysfunction (EjD). Aim: To provide a systematic review and meta-analysis of the available randomized clinical trials (RCTs) reporting the impact of medical treatments for LUTS due to BPH on ejaculatory function. Main Outcome Measure: EjD related to medical treatments for LUTS. Methods: A systematic literature search was performed using PubMed, Scopus and Cochrane databases. EjD was identified using both free text ("ejaculat*," "retrograde ejaculation," "anejaculation," "ejaculatory dysfunction") and Mesh ("Ejaculation") searches. Results: Of 101 retrieved articles, 23 were included in the present meta-analysis. EjD was significantly more common with alpha-blockers (ABs) than with placebo (OR:5.88; P<0.0001), in particular, considering Tamsulosin (OR:8.58; P=0.006) or Silodosin (OR:32.5; P<0.0001), with Tamsulosin associated with significantly lower risk of EjD than Silodosin (OR:0.09; P<0.00001). Conversely, Doxazosin and Terazosin were associated with a risk similar to placebo. Meta-regression showed that EjD was associated with IPSS and with Qmax both before and after treatment with ABs, while multivariate analysis demonstrated that EjD was independently associated with the improvement of IPSS (adj.r:0.2012; P<0.0001) and Qmax (adj.r:0.522; P<0.0001). EjD was significantly more common with 5ARIs as compared with placebo (OR:2.73; P<0.0001). Both Finasteride (OR 2.70; P<0.0001) and Dutasteride (OR 2.81; P=0.0002) were associated with significantly higher risk of EjD than placebo. EjD was significantly more common with combination therapy as compared with ABs alone (OR:3.75; P<0.0001),or with 5ARIs alone (OR:2.76; P=0.02). Conclusions: ABs and 5ARI were both associated with significantly higher risk of EjD than placebo. More the AB is effective over time, greater is the incidence of EjD. Finasteride has the same risk of Dutasteride to cause EjD. Combination therapy with ABs and 5ARIs resulted in a 3-fold increased risk of EjD as compared with ABs or 5ARIs alone. These data can be relevant both for drug selection and patients counseling. Gacci M, Ficarra V, Sebastianelli A, Corona G, Serni S, Shariat SF, Maggi M, Zattoni F, Carini M, and Novara G. Impact of medical treatments for male lower urinary tract symptoms due to benign prostatic hyperplasia on ejaculatory function: A systematic review and meta-analysis. J Sex Med 2014;11:1554-1566. © 2014 International Society for Sexual Medicine
Comparison of nomograms with other methods for predicting outcomes in prostate cancer: A critical analysis of the literature
No full textPurpose: Accurate estimates of risk are essential for physicians if they are to recommend a specific management to patients with prostate cancer, Accurate risk estimates are also required for clinical trial design, to ensure homogeneous patient groups. Because there is more than one model available for prediction of most outcomes, model comparisons are necessary for selection of the best model. We describe the criteria based on which to judge predictive tools, describe the limitations of current predictive tools, and compare the different predictive methodologies that have been used in the prostate cancer literature. Experimental Design: Using MEDLINE, a literature search was done on prostate cancer decision aids from January 1966 to July 2007. Results: The decision aids consist of nomograms, risk groupings, artificial neural networks, probability tables, and classification and regression tree analyses. The following considerations need to be applied when the qualities of predictive models are assessed: predictive accuracy (internal or ideally external validation), calibration (i.e., performance according to risk level or in specific patient subgroups), generalizability (reproducibility and transportability), and level of complexity relative to established models, to assess whether the new model offers advantages relative to available alternatives. Studies comparing decision aids have shown that nomograms outperform the other methodologies. Conclusions: Nomograms provide superior individualized disease-related risk estimations that facilitate management-related decisions. Of currently available prediction tools, the nomograms have the highest accuracy and the best discriminating characteristics for predicting outcomes in prostate cancer patients
Prediction of delayed graft function after renal transplantation
No full textIntroduction: Delayed graft function (DGF), defined as the need for dialysis during the first week after renal transplantation, is an important adverse clinical outcome. A previous model relied on 16 variables to quantify the risk of DGF, thereby undermining its clinical usefulness. We explored the possibility of developing a simpler, equally accurate and more user-friendly paradigm for renal transplant recipients from deceased donors. Methods: Logistic regression analyses addressed the occurrence of DGF in 532 renal transplant recipients from deceased donors. Predictors consisted of recipient age, gender, race, weight, number of HLA-A, HLA-B and HLA-DR mismatches, maximum and last titre of panel reactive antibodies, donor age and cold ischemia time. Accuracy was quantified with the area under the curve. Two hundred bootstrap resamples were used for internal validation. Results: Delayed graft function occurred in 103 patients (19.4%). Recipient weight (p < 0.001), panel of reactive antibodies (p < 0.001), donor age (p < 0.001), cold ischemia time (p = 0.005) and HLA-DR mismatches (p = 0.05) represented independent predictors. The multivariable nomogram relying on 6 predictors was 74.3% accurate in predicting the probability of DGF. Conclusion: Our simple and user-friendly model requires 6 variables and is at least equally accurate (74%) to the previous nomogram (71 %). We demonstrate that DGF can be accurately predicted in different populations with this new model
Predictive and Prognostic Models in Radical Prostatectomy Candidates: A Critical Analysis of the Literature
No full textContext: Numerous predictive and prognostic tools have recently been developed for risk stratification of prostate cancer (PCa) patients who are candidates for or have been treated with radical prostatectomy (RP). Objective: To critically review the currently available predictive and prognostic tools for RP patients and to describe the criteria that should be applied in selecting the most accurate and appropriate tool for a given clinical scenario. Evidence acquisition: A review of the literature was performed using the Medline, Scopus, and Web of Science databases. Relevant reports published between 1996 and January 2010 identified using the keywords prostate cancer, radical prostatectomy, predictive tools, predictive models, and nomograms were critically reviewed and summarised. Evidence synthesis: We identified 16 predictive and 22 prognostic validated tools that address a variety of end points related to RP. The majority of tools are prediction models, while a few consist of risk-stratification schemes. Regardless of their format, the tools can be distinguished as preoperative or postoperative. Preoperative tools focus on either predicting pathologic tumour characteristics or assessing the probability of biochemical recurrence (BCR) after RP. Postoperative tools focus on cancer control outcomes (BCR, metastatic progression, PCa-specific mortality [PCSM], overall mortality). Finally, a novel category of tools focuses on functional outcomes. Prediction tools have shown better performance in outcome prediction than the opinions of expert clinicians. The use of these tools in clinical decision-making provides more accurate and highly reproducible estimates of the outcome of interest. Efforts are still needed to improve the available tools' accuracy and to provide more evidence to further justify their routine use in clinical practice. In addition, prediction tools should be externally validated in independent cohorts before they are applied to different patient populations. Conclusions: Predictive and prognostic tools represent valuable aids that are meant to consistently and accurately provide most evidence-based estimates of the end points of interest. More accurate, flexible, and easily accessible tools are needed to simplify the practical task of prediction. (C) 2010 European Association of Urology. Published by Elsevier B.V. All rights reserved
External validation of a biomarker-based preoperative nomogram predicts biochemical recurrence after radical prostatectomy
No full textPurpose Biomarker signatures currently are used in several malignancies to guide clinical decision making. Recently, preoperative plasma levels of transforming growth factor-beta 1 (TGF-beta 1) and interleukin-6 soluble receptor (IL6-SR) have improved the accuracy of a clinical nomogram that predicted biochemical recurrence after radical prostatectomy. However, this model was never externally validated. We tested the accuracy of this nomogram in an independent, external cohort. Patients and Methods Preoperative plasma levels of TGF-beta 1 and IL6-SR were measured in 423 consecutive men who underwent radical prostatectomy and bilateral lymphadenectomy and were used, along with preoperative prostate-specific antigen levels, biopsy Gleason sum, and clinical stage to determine nomogram-derived probabilities of biochemical recurrence-free survival at 5 years after radical prostatectomy. The accuracy of predictions was quantified with the area under the curve (AUC) and calibration plots that graphically displayed the nomogram's performance characteristics. The statistical significance of the difference between the biomarker nomogram and a model designed on the basis of clinical variables alone was tested by using the Mantel-Haenszel statistic. Results Biochemical recurrence-free survival at 5 years was 77.0% (95% CI, 72.0% to 82.0%). The biomarker-based nomogram was 87.9% accurate versus 71.1% for the nomogram designed on the basis of clinical variables alone (16.8% difference; P < .001). The performance characteristics of the biomarker-based nomogram were superior to those of the clinical nomogram. Conclusion We confirm that plasma levels of TGF-beta 1 and IL6-SR considerably enhance the accuracy of the standard preoperative nomogram for the prediction of biochemical recurrence after radical prostatectomy. This model further refines our ability to identify patients at a high risk of biochemical recurrence after radical prostatectomy
The effect of comorbidities and socioeconomic status on sexual and urinary function in men undergoing prostate cancer screening
No full textIntroduction. Comorbidities and socioeconomic status (SES) represent known confounders of baseline health-related quality of life. Aim. To assess the effect of comorbidities and of SES variables on urinary function (UF) and sexual function (SF) and on associated bother items. Methods. A cohort of 1,162 men without an established diagnosis of prostate cancer (PCa) completed questionnaires addressing SES characteristics, the lifetime prevalence of 12 comorbid conditions, SF and UF as well as their associated bother. Main Outcome Measures. Crude and adjusted logistic regression models tested the association between the predictors, SES and comorbidity, and four separate outcomes, namely SF and UF and their associated bother. Results. Of all men, aged 40-79 years, 172 (14.8%) reported poor or very poor ability to have an erection, and for 165 (14.2%), erectile function (EF) was a big or moderate problem. Daily or weekly urinary incontinence was reported by 98 (8.4%) men, and for 94 (8.1%) men, UF was a big or moderate problem. One or more comorbidities were present in 437 (37.6%) men. In age- and SES-adjusted analyses, major depression and diabetes had the most detrimental effect on EF (5.8 [P < 0.001] and 4.8 [P < 0.001], respectively) and on sexual bother (4.3 [P < 0.001] and 7.2 [P < 0.001], respectively). Stroke (4.7 [P = 0.004]) and drug problems (4.8 [P = 0.002]) had the most detrimental effect on urinary incontinence. Alcoholism and alcohol-related problems (3.1 [P = 0.004]) had the most detrimental effect on the urinary bother scale. Finally, SES only affected urinary incontinence, which was poorer in men who lived with a spouse or partner (2.1 [P = 0.03]). Conclusion. Select comorbidities have very strong effects on UF and EF. Conversely, for most SES variables, the effect was weak and insignificant. In consequence, when patients are assessed for definitive PCa therapy, comorbidities require an adjustment, whereas SES assessment may potentially be omitted, especially if questionnaire brevity is a consideration
Multifocal carcinoma in situ of the upper tract is associated with high risk of bladder cancer recurrence.
No full textPre-Treatment Biomarker Levels Improve the Accuracy of Post-Prostatectomy Nomogram for Prediction of Biochemical Recurrence
No full textPURPOSE. We tested the ability of several pre-operative blood-based biomarkers to enhance the accuracy of standard post-operative features for the prediction of biochemical recurrence (BCR) after radical prostatectomy (RP). METHODS. Pre-operative plasma levels of Endoglin, interleukin-6 (IL-6), interleukin-6 soluble receptor (IL-6sR), transforming growth factor-beta 1 (TGF-beta 1), urokinase plasminogen activator (uPA), urokinase plasminogen inhibitor-1 (PAI-1), urokinase plasminogen receptor (uPAR), vascular cell adhesion molecule-1 (VCAM1), and vascular endothelial growth factor (VEGF) were measured using commercially available enzyme immunoassays in 423 consecutive patients treated with RP for clinically localized prostate cancer. Standard postoperative features consisted of surgical margin status, extracapsular extension, seminal vesicle invasion, lymph node involvement, and pathologic Gleason sum. Multivariable modeling was used to explore the gain in the predictive accuracy. The accuracy was quantified by the c-index statistic and was internally validated with 200 bootstrap resamples. RESULTS. Plasma IL-6 (P = 0.03), IL-6sR (P < 0.001), TGF-beta 1 (P = 0.005), and V-CAM1 (P = 0.01) achieved independent predictor status after adjusting for the effects of standard post-operative features. After stepwise backward variable elimination, a model relying on RP Gleason sum, IL-6sR, TGF-beta 1, VCAM1, and uPA improved the predictive accuracy of the standard post-operative model by 4% (86.1% vs. 82.1%, P < 0.001). CONCLUSIONS. Pre-operative plasma biomarkers improved the accuracy of established post-operative prognostic factors of BCR by a significant margin. Incorporation of these biomarkers into standard predictive models may allow more accurate identification of patients who are likely to fail RP thereby allowing more efficient delivery of adjuvant therapy. Prostate 69: 886-894, 2009. (c) 2009 Wiley-Liss, Inc
The effect of surgical volume, age and comorbidities on 30-day mortality after radical prostatectomy: a population-based analysis of 9208 consecutive cases
No full textOBJECTIVE To examine the effect of surgical volume (SV) on 30-day mortality after radical prostatectomy (RP; reportedly 0.1-0.6% and influenced by age and comorbidities) and to explore the most informative SV, age and comorbidity thresholds to distinguish between high- and low-risk men. PATIENTS AND METHODS Between 1989 and 2000, 9208 consecutive patients were treated with RP. The effects on 30-day mortality of (either continuously coded or categorized) patient age, comorbidities (Charlson Comorbidity Index, CCI) and SV were tested in multivariable logistic regression models. The models were corrected for overfit bias using 200 bootstrap re-samples and were displayed graphically as nomograms. RESULTS The overall 30-day mortality was 0.52%; being younger ( 27 RPs, 0.07 vs 0.6% otherwise, P = 0.049) had a protective effect and represented independent predictors of 30-day mortality. After correction for overfit bias, their combined input was 72.3% accurate in predicting 30-day mortality, vs 67.1% (P 27 RPs) can accurately identify patients at negligible risk of 30-day mortality
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