486 research outputs found

    Variation in annual volume at a university hospital does not predict mortality for pancreatic resections.

    Get PDF
    Annual volume of pancreatic resections has been shown to affect mortality rates, prompting recommendations to regionalize these procedures to high-volume hospitals. Implementation has been difficult, given the paucity of high-volume centers and the logistical hardships facing patients. Some studies have shown that low-volume hospitals achieve good outcomes as well, suggesting that other factors are involved. We sought to determine whether variations in annual volume affected patient outcomes in 511 patients who underwent pancreatic resections at the University of California, San Francisco between 1990 and 2005. We compared postoperative mortality and complication rates between low, medium, or high volume years, designated by the number of resections performed, adjusting for patient characteristics. Postoperative mortality rates did not differ between high volume years and medium/low volume years. As annual hospital volume of pancreatic resections may not predict outcome, identification of actual predictive factors may allow low-volume centers to achieve excellent outcomes

    Predicting 6-Year Mortality Risk in Patients With Type 2 Diabetes

    Get PDF
    OBJECTIVE—The objective of this study was to create a tool that predicts the risk of mortality in patients with type 2 diabetes

    Long-term outcome among men with conservatively treated localised prostate cancer

    Get PDF
    Optimal management of clinically localised prostate cancer presents unique challenges, because of its highly variable and often indolent natural history. There is an urgent need to predict more accurately its natural history, in order to avoid unnecessary treatment. Medical records of men diagnosed with clinically localised prostate cancer, in the UK, between 1990 and 1996 were reviewed to identify those who were conservatively treated, under age 76 years at the time of pathological diagnosis and had a baseline prostate-specific antigen (PSA) measurement. Diagnostic biopsy specimens were centrally reviewed to assign primary and secondary Gleason grades. The primary end point was death from prostate cancer and multivariate models were constructed to determine its best predictors. A total of 2333 eligible patients were identified. The most important prognostic factors were Gleason score and baseline PSA level. These factors were largely independent and together, contributed substantially more predictive power than either one alone. Clinical stage and extent of disease determined, either from needle biopsy or transurethral resection of the prostate (TURP) chips, provided some additional prognostic information. In conclusion, a model using Gleason score and PSA level identified three subgroups comprising 17, 50, and 33% of the cohort with a 10-year prostate cancer specific mortality of <10, 10–30, and >30%, respectively. This classification is a substantial improvement on previous ones using only Gleason score, but better markers are needed to predict survival more accurately in the intermediate group of patients

    Carbamazepine induces a bioenergetics disruption to microvascular endothelial cells from the blood-brain barrier

    Get PDF
    Carbamazepine (CBZ) is a widely employed anti-seizure medication that crosses the blood-brain barrier (BBB) to exert its anti-convulsant action. The effects of CBZ on components of the BBB have yet to be completely delineated. Hence the current study evaluated the effects of CBZ upon mitochondrial functionality of BBB-derived microvascular endothelial cells isolated from Albino rats. The influence of CBZ on cell viability and barrier functions were evaluated by 3-(4,5 dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT), lactate dehydrogenase, and electrophysiological assays over a drug concentration range of 0.1-1000 µM. Bioenergetics effects were measured via ATP production, mitochondrial complexes I an

    Ki-67 and outcome in clinically localised prostate cancer: analysis of conservatively treated prostate cancer patients from the Trans-Atlantic Prostate Group study

    Get PDF
    Treatment decisions after diagnosis of clinically localised prostate cancer are difficult due to variability in tumour behaviour. We therefore examined one of the most promising biomarkers in prostate cancer, Ki-67, in a cohort of 808 patients diagnosed with prostate cancer between 1990 and 1996 and treated conservatively. Ki-67 expression was assessed immunohistochemically, in two laboratories, by two different scoring methods and the results compared with cancer-specific and overall survival. The power of the biomarker was compared with Gleason score and initial serum prostate-specific antigen (PSA). Both methods showed that Ki-67 provided additional prognostic information beyond that available from Gleason score and PSA: for the semi-quantitative method, Δχ2 (1 d.f.)=24.6 (P<0.0001), overall survival χ2=20.5 (P<0.0001), and for the quantitative method, Δχ2 (1 d.f.)=15.1 (P=0.0001), overall survival χ2=10.85 (P=0.001). Ki-67 is a powerful biomarker in localised prostate cancer and adds to a model predicting the need for radical or conservative therapy. As it is already in widespread use in routine pathology, it is confirmed as the most promising biomarker to be applied into routine practice

    Prostate Cancer Postoperative Nomogram Scores and Obesity

    Get PDF
    Nomograms are tools used in clinical practice to predict cancer outcomes and to help make decisions regarding management of disease. Since its conception, utility of the prostate cancer nomogram has more than tripled. Limited information is available on the relation between the nomograms' predicted probabilities and obesity. The purpose of this study was to examine whether the predictions from a validated postoperative prostate cancer nomogram were associated with obesity.We carried out a cross-sectional analysis of 1220 patients who underwent radical prostatectomy (RP) in southern California from 2000 to 2008. Progression-free probabilities (PFPs) were ascertained from the 10-year Kattan postoperative nomogram. Multivariable logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs).In the present study, aggressive prostate cancer (Gleason ≥7), but not advanced stage, was associated with obesity (p = 0.01). After adjusting for age, black race, family history of prostate cancer and current smoking, an inverse association was observed for 10-year progression-free predictions (OR = 0.50; 95% CI = 0.28–0.90) and positive associations were observed for preoperative PSA levels (OR = 1.23; 95% CI = 1.01–1.50) and Gleason >7 (OR = 1.45; 95% CI = 1.11–1.90).Obese RP patients were more likely to have lower PFP values than non-obese patients, suggesting a higher risk of experiencing prostate cancer progression. Identifying men with potentially higher risks due to obesity may improve disease prognosis and treatment decision-making

    Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

    Full text link
    Objective: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user. Study Design and Setting: Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate cancer, defined as Gleason grade group greater or equal 2 on standard TRUS prostate biopsy. One large European PBCG cohort was withheld for external validation, where calibration-in-the-large (CIL), calibration curves, and area-underneath-the-receiver-operating characteristic curve (AUC) were evaluated. Ten-fold leave-one-cohort-internal validation further validated the optimal missing data approach. Results: Among 12,703 biopsies from 10 training cohorts, 3,597 (28%) had clinically significant prostate cancer, compared to 1,757 of 5,540 (32%) in the external validation cohort. In external validation, the available cases method that pooled individual patient data containing all risk factors input by an end-user had best CIL, under-predicting risks as percentages by 2.9% on average, and obtained an AUC of 75.7%. Imputation had the worst CIL (-13.3%). The available cases method was further validated as optimal in internal cross-validation and thus used for development of an online risk tool. For end-users of the risk tool, two risk factors were mandatory: serum prostate-specific antigen (PSA) and age, and ten were optional: digital rectal exam, prostate volume, prior negative biopsy, 5-alpha-reductase-inhibitor use, prior PSA screen, African ancestry, Hispanic ethnicity, first-degree prostate-, breast-, and second-degree prostate-cancer family history
    corecore