Development and evaluation of the Clinician Suicide Risk Assessment Checklist

This paper describes the development and evaluation of a new instrument - the Clinician Suicide Risk Assessment Checklist (CSRAC). The instrument assesses the clinician's competency in three areas: clinical interviewing, assessment of specific suicide risk factors, and formulating a management plan. A draft checklist was constructed by integrating information from 1) literature review 2) expert clinician focus group and 3) consultation with experts. It was utilised in a simulated clinical scenario with clinician trainees and a trained actor in order to test for inter-rater agreement. Agreement was calculated and the checklist was re-drafted with the aim of maximising agreement. A second phase of simulated clinical scenarios was then conducted and inter-rater agreement was calculated for the revised checklist. In the first phase of the study, 18 of 35 items had inadequate inter-rater agreement (60%>), while in the second phase, using the revised version, only 3 of 39 items failed to achieve adequate inter-rater agreement. Further evidence of reliability and validity are required. Continued development of the CSRAC will be necessary before it can be utilised to assess the effectiveness of risk assessment training programs.

A comparative analysis of risk stratification tools for emergency department patients with chest pain

Background: Appropriate disposition of emergency department (ED) patients with chest pain is dependent on clinical evaluation of risk. A number of chest pain risk stratification tools have been proposed. The aim of this study was to compare the predictive performance for major adverse cardiac events (MACE) using risk assessment tools from the National Heart Foundation of Australia (HFA), the Goldman risk score and the Thrombolysis in Myocardial Infarction risk score (TIMI RS). Methods: This prospective observational study evaluated ED patients aged ≥30 years with non-traumatic chest pain for which no definitive non-ischemic cause was found. Data collected included demographic and clinical information, investigation findings and occurrence of MACE by 30 days. The outcome of interest was the comparative predictive performance of the risk tools for MACE at 30 days, as analyzed by receiver operator curves (ROC). Results: Two hundred eighty-one patients were studied; the rate of MACE was 14.1%. Area under the curve (AUC) of the HFA, TIMI RS and Goldman tools for the endpoint of MACE was 0.54, 0.71 and 0.67, respectively, with the difference between the tools in predictive ability for MACE being highly significant [chi2 (3) = 67.21, N = 276, p < 0.0001]. Conclusion: The TIMI RS and Goldman tools performed better than the HFA in this undifferentiated ED chest pain population, but selection of cutoffs balancing sensitivity and specificity was problematic. There is an urgent need for validated risk stratification tools specific for the ED chest pain population.

Correlation of macrophage location and plaque stress distribution using USPIO-enhanced MRI in a patient with symptomatic severe carotid stenosis: A new insight into risk stratification

High resolution, USPIO-enhanced MR imaging can be used to identify inflamed atherosclerotic plaque. We report a case of a 79-year-old man with a symptomatic carotid stenosis of 82%. The plaque was retrieved for histology and finite element analysis (FEA) based on the preoperative MR imaging was used to predict maximal Von Mises stress on the plaque. Macrophage location correlated with maximal predicted stresses on the plaque. This supports the hypothesis that macrophages thin the fibrous cap at points of highest stress, leading to an increased risk of plaque rupture and subsequent stroke.

Cancer gene signatures in risk stratification: use in personalized medicine

Cancer is a complex disease which arises due to a series of genetic changes related to cell division and growth control. Cancer remains the second leading cause of death in humans next to heart diseases. As a testimony to our progress in understanding the biology of cancer and developments in cancer diagnosis and treatment methods, the overall median survival time of all cancers has increased six fold one year to six years during the last four decades. However, while the median survival time has increased dramatically for some cancers like breast and colon, there has been only little change for other cancers like pancreas and brain. Further, not all patients having a single type of tumour respond to the standard treatment. The differential response is due to genetic heterogeneity which exists not only between tumours, which is called intertumour heterogeneity, but also within individual tumours, which is called intratumoural heterogeneity. Thus it becomes essential to personalize the cancer treatment based on a specific genetic change in a given tumour. It is also possible to stratify cancer patients into low- and high-risk groups based on expression changes or alterations in a group of genes gene signatures and choose a more suitable mode of therapy. It is now possible that each tumour can be analysed using various high-throughput methods like gene expression profiling and next-generation sequencing to identify its unique fingerprint based on which a personalized or tailor-made therapy can be developed. Here, we review the important progress made in the recent years towards personalizing cancer treatment with the use of gene signatures.

Risk stratification of latent tuberculosis defined by combined interferon gamma release assays.

Most individuals infected with Mycobacterium tuberculosis develop latent tuberculosis infection (LTBI). Some may progress to active disease and would benefit from preventive treatment yet no means currently exists to predict who will reactivate. Here, we provide an approach to stratify LTBI based on IFN-γ responses to two antigens, the recombinant Early-Secreted Antigen Target-6 (rESAT-6) and the latency antigen Heparin-Binding Haemagglutinin (HBHA).

Population-based study reveals new risk-stratification biomarker panel for Barrett's esophagus

BACKGROUND & AIMS: The risk of progression of Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) is low and difficult to calculate. Accurate tools to determine risk are needed to optimize surveillance and intervention. We assessed the ability of candidate biomarkers to predict which cases of BE will progress to EAC or high-grade dysplasia and identified those that can be measured in formalin-fixed tissues. METHODS: We analyzed data from a nested case-control study performed using the population-based Northern Ireland BE Register (1993-2005). Cases who progressed to EAC (n = 89) or high-grade dysplasia =6 months after diagnosis with BE were matched to controls (nonprogressors, n = 291), for age, sex, and year of BE diagnosis. Established biomarkers (abnormal DNA content, p53, and cyclin A expression) and new biomarkers (levels of sialyl Lewis(a), Lewis(x), and Aspergillus oryzae lectin [AOL] and binding of wheat germ agglutinin) were assessed in paraffin-embedded tissue samples from patients with a first diagnosis of BE. Conditional logistic regression analysis was applied to assess odds of progression for patients with dysplastic and nondysplastic BE, based on biomarker status. RESULTS: Low-grade dysplasia and all biomarkers tested, other than Lewis(x), were associated with risk of EAC or high-grade dysplasia. In backward selection, a panel comprising low-grade dysplasia, abnormal DNA ploidy, and AOL most accurately identified progressors and nonprogressors. The adjusted odds ratio for progression of patients with BE with low-grade dysplasia was 3.74 (95% confidence interval, 2.43-5.79) for each additional biomarker and the risk increased by 2.99 for each additional factor (95% confidence interval, 1.72-5.20) in patients without dysplasia. CONCLUSIONS: Low-grade dysplasia, abnormal DNA ploidy, and AOL can be used to identify patients with BE most likely to develop EAC or high-grade dysplasia.

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.

Ventricular arrhythmia in coronary artery disease: limits of a risk stratification strategy based on the ejection fraction alone and impact of infarct localization.

AIMS: Estimates of the left ventricular ejection fraction (LVEF) in patients with life-threatening ventricular arrhythmias related to coronary artery disease (CAD) have rarely been reported despite it has become the basis for determining patient's eligibility for prophylactic defibrillator. We aimed to determine the extent and distribution of reduced LVEF in patients with sustained ventricular tachycardia or ventricular fibrillation. METHODS AND RESULTS: 252 patients admitted for ventricular arrhythmia related to CAD were included: 149 had acute myocardial infarction (MI) (Group I, 59%), 54 had significant chronic obstructive CAD suggestive of an ischaemic arrhythmic trigger (Group II, 21%) and 49 patients had an old MI without residual ischaemia (Group III, 19%). 34% of the patients with scar-related arrhythmias had an LVEF > or =40%. Based on pre-event LVEF evaluation, it can be estimated that less than one quarter of the whole study population had a known chronic MI with severely reduced LVEF. In Group III, the proportion of inferior MI was significantly higher than anterior MI (81 vs. 19%; absolute difference, -62; 95% confidence interval, -45 to -79; P < or = 0.0001), though median LVEF was higher in inferior MI (0.37 +/- 10 vs. 0.29 +/- 10; P = 0.0499). CONCLUSION: Patients included in defibrillator trials represent only a minority of the patients at risk of sudden cardiac death. By applying the current risk stratification strategy based on LVEF, more than one third of the patients with old MI would not have qualified for a prophylactic defibrillator. Our study also suggests that inferior scars may be more prone to ventricular arrhythmia compared to anterior scars.

Cardiac risk stratification in cardiac rehabilitation programs: a review of protocols

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)