Simvastatin protects against cholestasis-induced liver injury

Background:

Bile duct obstruction is associated with hepatic accumulation of leukocytes and liver injury. The aim of this study was to evaluate the effect of simvastatin on cholestasis-induced liver inflammation and tissue damage.

Experimental approach:

C57BL/6 mice were treated with simvastatin (0.02 and 0.2 mg·kg⁻¹) and vehicle before and after undergoing bile duct ligation (BDL) for 12 h. Leukocyte recruitment and microvascular perfusion in the liver were analysed using intravital fluorescence microscopy. CXC chemokines in the liver were determined by enzyme-linked immunosorbent assay. Liver damage was monitored by measuring serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Hepatic levels of myeloperoxidase (MPO) were also determined.

Key results:

Administration of 0.2 mg·kg⁻¹ simvastatin decreased ALT and AST by 87% and 83%, respectively, in BDL mice. This dose of simvastatin reduced hepatic formation of CXC chemokines by 37–82% and restored sinusoidal perfusion in cholestatic animals. Moreover, BDL-induced leukocyte adhesion in sinusoids and postsinusoidal venules, as well as MPO levels in the liver, was significantly reduced by simvastatin. Notably, administration of 0.2 mg·kg⁻¹ simvastatin 2 h after BDL induction also decreased cholestatic liver injury and inflammation.

Conclusions and implications:

These findings show that simvastatin protects against BDL-induced liver injury. The hepatoprotective effect of simvastatin is mediated, at least in part, by reduced formation of CXC chemokines and leukocyte recruitment. Thus, our novel data suggest that the use of statins may be an effective strategy to protect against the hepatic injury associated with obstructive jaundice.     

Inventory of prostate cancer predictive tools

PURPOSE OF REVIEW: We created an inventory of current predictive tools available for prostate cancer. This review may serve as an initial step toward a comprehensive reference guide for physicians to locate published nomograms that apply to the clinical decision in question. Using MEDLINE a literature search was performed on prostate cancer predictive tools from January 1966 to November 2007. We describe the patient populations to which they apply and the outcomes predicted, and record their individual characteristics. RECENT FINDINGS: The literature search generated 111 published prediction tools that may be applied to patients in various clinical stages of disease. Of the 111 prediction tools, only 69 had undergone validation. We present an inventory of models with input variables, prediction form, number of patients used to develop the prediction tools, the outcome being predicted, prediction tool-specific features, predictive accuracy, and whether validation was performed. SUMMARY: Decision rules, such as nomograms, provide evidence-based and at the same time individualized predictions of the outcome of interest. Such predictions have been repeatedly shown to be more accurate than those of clinicians, regardless of their level of expertise. Accurate risk estimates are also required for clinical trial design, to ensure homogeneous high-risk patient groups for whom new cancer therapeutics will be investigated.     

The prediction philosophy in statistics

Estimation and hypothesis testing have been popular in applied statistical analysis. More recently, emphasis has been placed on prediction. Traditional questions of estimation and hypothesis testing are being reframed as problems of prediction, and as such, the methods and approaches have shifted. The reporting of P values is de-emphasized from the prediction philosophy perspective, and incremental predictive accuracy has become the metric of choice. Ties to individual patient decision making and outcomes research are presented.     

A preoperative prognostic nomogram for solid enhancing renal tumors 7 cm or less amenable to partial nephrectomy

PURPOSE: Small renal masses are increasing in incidence. Most tumors 7 cm or less are treated with radical or partial nephrectomy but clinicians are increasingly relying on ablative therapies and observation for some small renal masses. We present novel nomograms that predict the likelihood of benign, likely indolent or potentially aggressive pathological findings based only on readily identifiable preoperative factors. MATERIALS AND METHODS: Information on all partial nephrectomies performed at a single institution was collected in an institutional review board approved registry. Using retrospectively collected data on all 862 patients who underwent partial nephrectomy for a single, solid, enhancing, clinical T1 (7 cm or less) tumor between 1999 and 2005 tumors were classified as benign or malignant. Grade 3 clear cell renal cell carcinoma, grade 4 renal cell carcinoma of any type and any renal cell carcinoma with vascular, fat or collecting system invasion were considered potentially aggressive. The likelihood of benign, likely indolent or potentially aggressive pathological findings was modeled using multivariable logistic regression models based on age, gender, radiographic tumor size, symptoms at presentation and smoking history. RESULTS: Of 862 small renal masses 20% were benign and 80% were malignant but only 30% of cancers (24% of small renal masses) were potentially aggressive. All 11 patients with systemic symptoms had cancer. The remaining 851 patients underwent further analysis. Factors that were most strongly associated with the likelihood of benign pathology were age, gender, tumor size and smoking history. A nomogram constructed to predict benign histology proved to be relatively accurate and discriminating (bootstrap corrected concordance index 0.644) and calibrated. Small renal masses in older men and younger women were more likely to be benign. With regard to differentiating indolent from potentially aggressive cancers, only advanced age was independently significant on multivariate analysis (p <0.005). The nomogram for this outcome performed with limited ability (concordance index 0.557). CONCLUSIONS: Clinical factors provide substantial predictive ability to predict benign vs malignant pathology for small renal masses amenable to partial nephrectomy. Although most of these small renal masses are benign or indolent, our ability to predict potentially aggressive cancer in this population remains limited.     

Meta-analysis: Its strengths and limitations

Nowadays, doctors face an overwhelming amount of information, even in narrow areas of interest. In response, reviews designed to summarize the large volumes of information are frequently published. When a review is done systematically, following certain criteria, and the results are pooled and analyzed quantitatively, it is called a meta-analysis. A well-designed meta-analysis can provide valuable information for researchers, policymakers, and clinicians. However, there are many critical caveats in performing and interpreting them, and thus many ways in which meta-analyses can yield misleading information.     

The comparability of models for predicting the risk of a positive prostate biopsy with prostate-specific antigen alone: a systematic review

CONTEXT: The sensitivity and specificity profile of measuring levels of prostate-specific antigen (PSA) to select men for prostate biopsy is not optimal. This has prompted the construction of nomograms and artificial neural networks (ANNs) to increase the performance of PSA measurements. OBJECTIVE: A systematic review of nomograms and ANNs designed to predict the risk of a positive prostate biopsy for cancer was conducted in order to determine their value versus measuring PSA levels alone. EVIDENCE ACQUISITION: Medical Literature Analysis and Retrieval System Online (U.S. National Library of Medicine's life science database; MEDLINE) was searched using the terms "nomogram" "artificial neural network" and "prostate cancer" for dates up to and including July 2007 and was supplemented by manual searches of reference lists. Included studies used an assessment tool to examine the risk of a positive prostate biopsy in a man without a known cancer diagnosis. Intramodel comparisons with evaluation of PSA levels alone, and intermodel comparisons of area under the curve (AUC) from receiver operating characteristic (ROC) curves were conducted. Individual case examples were also used for comparisons. EVIDENCE SYNTHESIS: Twenty-three studies examining 36 models were included. With the exception of two studies, all the models had AUC values of 0.70 or greater, with eight reporting an AUC of >/=0.80 and four (all ANNs) reporting an AUC >/=0.85, with variable validation status. Fourteen studies compared the AUC with PSA levels alone: all showed a benefit from using AUCs which varied from 0.02 to 0.26. Of the 16 external validation comparisons, in 13 the AUC was lower in the external population than in the model population. CONCLUSIONS: Nomograms and ANNs produce improvements in AUC over measurement of PSA levels alone, but many lack external validation. Where this is available, the benefits are often diminished, although most remain significantly better than with evaluation of PSA levels alone. In men without additional risk factors, PSA cutoff values alone provide a relatively precise risk estimate, but if additional risk factors are known, PSA values alone are less accurate.