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Acute and transient psychotic disorders (ATPDs) include short-lived psychotic episodes with a high probability of developing psychotic recurrences. Clinical care for ATPD is currently limited by the inability to predict outcomes. Real-world electronic health record (EHR)-based retrospective cohort study STROBE/RECORD compliant included all individuals accessing the South London and Maudsley NHS Trust between 2006 and 2017 and receiving a first diagnosis of ATPD (F23, ICD-10). After imputing missing data, stepwise and LASSO Cox regression methods employing a priori predictors (n = 23) were compared to develop and internally validate an individualized risk prediction model to forecast the risk of psychotic recurrences following TRIPOD guidelines. The primary outcome was prognostic accuracy (area under the curve [AUC]). 3018 ATPD individuals were included (average age = 33.75 years, 52.7% females). Over follow-up (average 1042 ± 1011 days, up to 8 years) there were 1160 psychotic recurrences (events). Stepwise (n = 12 predictors) and LASSO (n = 17 predictors) regression methods yielded comparable prognostic accuracy, with an events per variable ratio >100 for both models. Both models showed an internally validated adequate prognostic accuracy from 4 years follow-up (AUC 0.70 for both models) and good calibration. A refined model was adapted in view of the new ICD-11 criteria on 307 subjects with polymorphic ATPD, showing fair prognostic accuracy at 4 years (AUC: stepwise 0.68; LASSO 0.70). This study presents the first clinically based prediction model internally validated to adequately predict long-term psychotic recurrence in individuals with ATPD. The model can be automatable in EHRs, supporting further external validations and refinements to improve its prognostic accuracy.

Genome-wide association studies have identified hundreds of single nucleotide polymorphisms (SNPs) that are associated with BMI and diabetes. However, lack of adequate data has for long time prevented investigations on the pathogenesis of diabetes where BMI was a mediator of the genetic causal effects on this disease. Of our particular interest is the underlying causal mechanisms of diabetes. We leveraged the summary statistics reported in two studies: UK Biobank (N = 336,473) and Genetic Investigation of ANthropometric Traits (GIANT, N = 339,224) to investigate BMI-mediated genetic causal pathways to diabetes. We first estimated the causal effect of BMI on diabetes by using four Mendelian randomization methods, where a total of 76 independent BMI-associated SNPs (R2 ≤ 0.001, P −8) were used as instrumental variables. It was consistently shown that higher level of BMI (kg/m2) led to increased risk of diabetes. We then applied two Bayesian colocalization methods and identified shared causal SNPs of BMI and diabetes in genes TFAP2B, TCF7L2, FTO and ZC3H4. This study utilized integrative analysis of Mendelian randomization and colocalization to uncover causal relationships between genetic variants, BMI and diabetes. It highlighted putative causal pathways to diabetes mediated by BMI for four genes.

The thoughts and feelings people have about pain (referred to as "Pain expectations") are known to alter the perception of pain. However we know very little about the cognitive processes that underpin pain expectations, or what drives the differing effect that pain expectations have between individuals. This paper details the testing of a model of pain perception which formalises the response to pain in terms of a Bayesian prior-to-posterior updating process. Using data acquired from a short and deception-free predictive cue task, it was found that this Bayesian model predicted ratings of pain better than other, simpler models. At the group level, the results confirmed two core predictions of Hierarchical Predictive Processing; that expectation alters perception and that increased uncertainty in the expectation reduces its impact on perception. The addition to the model of parameters relating to trait differences in pain expectation, improved its fit, suggesting that such traits (which have been relatively neglected in experimental work on pain perception) play a significant role in perception beyond those expectations triggered by the pain cue. When model parameters were allowed to vary by participant, the fit improved further. This final model produced a characterisation of the sensitivity of each individual to pain expectations. These findings are relevant for the understanding of the cognitive basis of pain expectations, and potentially useful for guiding patient stratification and clinical experimentation.

Background Recent advances in data analysis methods based on principles of Mendelian Randomisation, such as Egger regression and the weighted median estimator, add to the researcher’s ability to infer cause-effect links from observational data. Now is the time to gauge the potential of these methods within specific areas of biomedical research. In this paper, we choose a study in metabolomics as an illustrative testbed. We apply Mendelian Randomisation methods in the analysis of data from the DILGOM (Dietary, Lifestyle and Genetic determinants of Obesity and Metabolic syndrome) study, in the context of an effort to identify molecular pathways of cardiovascular disease. In particular, our illustrative analysis addresses the question whether body mass, as measured by body mass index (BMI), exerts a causal effect on the concentrations of a collection of 137 cardiometabolic markers with different degrees of atherogenic power, such as the (highly atherogenic) lipoprotein metabolites with very low density (VLDLs) and the (protective) high density lipoprotein metabolites. Results We found strongest evidence of a positive BMI effect (that is, evidence that an increase in BMI causes an increase in the metabolite concentration) on those metabolites known to represent strong risk factors for coronary artery disease, such as the VLDLs, and evidence of a negative effect on protective biomarkers. Conclusions The methods discussed represent a useful scientific tool, although they assume the validity of conditions that are (at best) only partially verifiable. This paper provides a rigorous account of such conditions. The results of our analysis provide a proof-of-concept illustration of the potential usefulness of Mendelian Randomisation in genomic biobank studies aiming to dissect the molecular causes of disease, and to identify candidate pharmacological targets. Electronic supplementary material The online version of this article (10.1186/s12859-018-2178-2) contains supplementary material, which is available to authorized users.

Early-onset myocardial infarction (MI) can be a major cause of physical and psychological morbidity. The known chronic and degenerative nature of the coronary atherosclerosis underlying an acute event can lead to justified concerns regarding the future risk of recurrent ischemic events or even

Acute myocardial infarction is primarily due to coronary atherosclerotic plaque rupture and subsequent thrombus formation. Platelets play a key role in the genesis and progression of both atherosclerosis and thrombosis. Since platelets are anuclear cells that inherit their mRNA from megakaryocyte precursors and maintain it unchanged during their life span, gene expression profiling at the time of an acute myocardial infarction provides information concerning the platelet gene expression preceding the coronary event. In ST-segment elevation myocardial infarction (STEMI), a gene-by-gene analysis of the platelet gene expression identified five differentially expressed genes: FKBP5, S100P, SAMSN1, CLEC4E and S100A12. The logistic regression model used to combine the gene expression in a STEMI vs healthy donors score showed an AUC of 0.95. The same five differentially expressed genes were externally validated using platelet gene expression data from patients with coronary atherosclerosis but without thrombosis. Platelet gene expression profile highlights five genes able to identify STEMI patients and to discriminate them in the background of atherosclerosis. Consequently, early signals of an imminent acute myocardial infarction are likely to be found by platelet gene expression profiling before the infarction occurs.

ObjectivesBeing able to predict which patients with COVID-19 are going to deteriorate is important to help identify patients for clinical and research practice. Clinical prediction models play a critical role in this process, but current models are of limited value because they are typically restricted to baseline predictors and do not always use contemporary statistical methods. We sought to explore the benefits of incorporating dynamic changes in routinely measured biomarkers, non-linear effects and applying ‘state-of-the-art’ statistical methods in the development of a prognostic model to predict death in hospitalised patients with COVID-19.DesignThe data were analysed from admissions with COVID-19 to three hospital sites. Exploratory data analysis included a graphical approach to partial correlations. Dynamic biomarkers were considered up to 5 days following admission rather than depending solely on baseline or single time-point data. Marked departures from linear effects of covariates were identified by employing smoothing splines within a generalised additive modelling framework.Setting3 secondary and tertiary level centres in Greater Manchester, the UK.Participants392 hospitalised patients with a diagnosis of COVID-19.Results392 patients with a COVID-19 diagnosis were identified. Area under the receiver operating characteristic curve increased from 0.73 using admission data alone to 0.75 when also considering results of baseline blood samples and to 0.83 when considering dynamic values of routinely collected markers. There was clear non-linearity in the association of age with patient outcome.ConclusionsThis study shows that clinical prediction models to predict death in hospitalised patients with COVID-19 can be improved by taking into account both non-linear effects in covariates such as age and dynamic changes in values of biomarkers.

ObjectiveThe aim of the study was to perform a preliminary comparison of quality of life (QoL) and patient satisfaction in individualized nurse-led follow-up versus conventional medical follow-up in ovarian cancer.MethodsOne hundred twelve women who received a diagnosis of ovarian, fallopian tube, or peritoneal cancer, completed primary treatment by surgery alone or with chemotherapy, irrespective of outcome with regard to remission, and expected survival of more than 3 months. Fifty-seven participants were randomized to individualized follow-up and 55 patients to conventional follow-up. Well-being was measured at baseline and at 3, 6, 12, and 24 months after randomization for QoL (QLQ-C30 [European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire], QLQ-Ov28), the Hospital Anxiety and Depression Scale (HADS), and a Patient Satisfaction Questionnaire (PSQ-III). The primary endpoints were the effects of follow-up on each of the scores (via hierarchical mixed-effects model) and on relapse-free time (via Cox model). The total cost of follow-up was compared between each group.ResultsThere was evidence for a QoL and patient satisfaction benefit for individualized versus standard follow-up (QLQ-C30, P = 0.013; 95% confidence interval, −0.03 to −0.001; PSQ-III P = 0.002; 95% confidence interval, −0.003 to −0.015; QLQ-Ov28, P = 0.14). Hospital Anxiety and Depression Scale data provided no evidence in favor of either treatment (P = 0.42). Delivered to protocol individualized follow-up resulted in a delay in the presentation of symptomatic relapse (P = 0.04), although the effect on survival in this study is unknown. Cost was £700 lower on average for the individualized follow-up group, but the difference was not statistically significant at the 5% level (P = 0.07).ConclusionsIndividualized follow-up was superior to conventional follow-up in 3 of the 4 QoL and patient satisfaction surveys in this preliminary study. Further prospective studies are needed in a larger population.Trial registration number is ISRCTN59149551.

The effect of estrogen on Alzheimer's Disease (AD) risk has received substantial research and media attention, especially in terms of hormone replacement therapy. But reproductive history is also an important modifier of estrogenic exposure, and deserves further investigation. Importantly, there is wide variation in reproductive patterns that modifies estrogen exposure during the reproductive span, which previous AD studies have not incorporated into their calculations. We measured degree of Alzheimer's-type dementia in a cohort of elderly British women, and collected detailed reproductive and medical history information, which we used to estimate number of months with estrogen exposure and number of months with menstrual cycles. Using Cox proportional-hazards models, we find that longer duration of estrogen exposure may have a protective effect against AD risk, such that for every additional month with estrogen, women experienced on average a 0.5% decrease in AD risk (N=89, p=0.02). More menstrual cycles may also have a protective effect against AD risk, although this result was of borderline statistical significance (p0.10). These results build upon previous methodologies by taking into account a variety of parameters including oral contraceptive use, breastfeeding, post-partum anovulation, abortions, and miscarriages. Additionally, Cox models revealed that longer reproductive span, age21 at first birth, and more months in lifetime spent pregnant had protective effects against AD risk.

The effect of early and midlife factors on later-life cognitive function has attracted scientific and public interest in recent years, especially with respect to hormonal risk factors for dementia. There is substantial evidence for reproductive history affecting Alzheimer's disease (AD) etiology. Here, we demonstrate how breastfeeding history affects women's risk of AD. Reproductive history data was collected, and AD diagnostic interviews were performed, for a cohort of elderly British women. Using Cox proportional-hazard models, we find that longer breastfeeding duration corresponded to reduced risk of AD (p < 0.01, n = 81). Women who breastfed had lower AD risk than women who did not breastfeed (p = 0.017, n = 81). Breastfeeding practices are an important modifier of cumulative endogenous hormone exposure for mothers. Ovarian hormone deprivation and/or insulin sensitivity benefits of breastfeeding may be responsible for the observed reduction in AD risk. Future studies concerning hormone effects on AD risk should consider how reproductive history leads to variation in endogenous hormone exposure and how this may influence the relationship between hormones and AD.

Background & Aims Genome-wide association studies (GWAS) have identified 140 Crohn's disease (CD) susceptibility loci. For most loci, the variants that cause disease are not known and the genes affected by these variants have not been identified. We aimed to identify variants that cause CD through detailed sequencing, genetic association, expression, and functional studies. Methods We sequenced whole exomes of 42 unrelated subjects with CD and 5 healthy subjects (controls) and then filtered single nucleotide variants by incorporating association results from meta-analyses of CD GWAS and in silico mutation effect prediction algorithms. We then genotyped 9348 subjects with CD, 2868 subjects with ulcerative colitis, and 14,567 control subjects and associated variants analyzed in functional studies using materials from subjects and controls and in vitro model systems. Results We identified rare missense mutations in PR domain-containing 1 ( PRDM1 ) and associated these with CD. These mutations increased proliferation of T cells and secretion of cytokines on activation and increased expression of the adhesion molecule L-selectin. A common CD risk allele, identified in GWAS, correlated with reduced expression of PRDM1 in ileal biopsy specimens and peripheral blood mononuclear cells (combined P = 1.6 × 10 −8 ). We identified an association between CD and a common missense variant, Val248Ala, in nuclear domain 10 protein 52 ( NDP52 ) ( P = 4.83 × 10 −9 ). We found that this variant impairs the regulatory functions of NDP52 to inhibit nuclear factor κB activation of genes that regulate inflammation and affect the stability of proteins in Toll-like receptor pathways. Conclusions We have extended the results of GWAS and provide evidence that variants in PRDM1 and NDP52 determine susceptibility to CD. PRDM1 maps adjacent to a CD interval identified in GWAS and encodes a transcription factor expressed by T and B cells. NDP52 is an adaptor protein that functions in selective autophagy of intracellular bacteria and signaling molecules, supporting the role of autophagy in the pathogenesis of CD.

background: There is a critical need for predictive/resistance biomarkers for VEGF inhibitors to optimise their use. methods: Blood samples were collected during and following treatment and, where appropriate, upon progression from ovarian cancer patients in ICON7, a randomised phase III trial of carboplatin and paclitaxel with or without bevacizumab. Plasma concentrations of 15 circulating angio-biomarkers were measured using a validated multiplex ELISA, analysed through a novel network analysis and their relevance to the PFS then determined. results: Samples (n=650) were analysed from 92 patients. Bevacizumab induced correlative relationships between Ang1 and Tie2 plasma concentrations, which reduced after initiation of treatment and remained decreased until progressive disease occurred. A 50% increase from the nadir in the concentration of circulating Tie2 (or the product of circulating Ang1 and Tie2) predicted tumour progression. Combining Tie2 with GCIG-defined Ca125 data yielded a significant improvement in the prediction of progressive disease in patients receiving bevacizumab in comparison with Ca125 alone (74.1% vs 47.3%, P

BACKGROUND: Evidence suggests the wide variation in platelet response within the population is genetically controlled. Unraveling the complex relationship between sequence variation and platelet phenotype requires accurate and reproducible measurement of platelet response. OBJECTIVE: To develop a methodology suitable for measuring signaling pathway-specific platelet phenotype, to use this to measure platelet response in a large cohort, and to demonstrate the effect size of sequence variation in a relevant model gene. METHODS: Three established platelet assays were evaluated: mobilization of [Ca(2+)](i), aggregometry and flow cytometry, each in response to adenosine 5'-diphosphate (ADP) or the glycoprotein (GP) VI-specific crosslinked collagen-related peptide (CRP). Flow cytometric measurement of fibrinogen binding and P-selectin expression in response to a single, intermediate dose of each agonist gave the best combination of reproducibility and inter-individual variability and was used to measure the platelet response in 506 healthy volunteers. Pathway specificity was ensured by blocking the main subsidiary signaling pathways. RESULTS: Individuals were identified who were hypo- or hyper-responders for both pathways, or who had differential responses to the two agonists, or between outcomes. 89 individuals, retested three months later using the same methodology, showed high concordance between the two visits in all four assays (r(2) = 0.872, 0.868, 0.766 and 0.549); all subjects retaining their phenotype at recall. The effect of sequence variation at the GP6 locus accounted for approximately 35% of the variation in the CRP-XL response. CONCLUSION: Genotyping-phenotype association studies in a well-characterized, large cohort provides a powerful strategy to measure the effect of sequence variation in genes regulating the platelet response.

Purpose: Randomized ovarian cancer trials, including ICON7, have reported improved progression-free survival (PFS) when bevacizumab was added to conventional cytotoxic therapy. The improvement was modest prompting the search for predictive biomarkers for bevacizumab. Experimental Design: Pretreatment training (n = 91) and validation (n = 114) blood samples were provided by ICON7 patients. Plasma concentrations of 15 angio-associated factors were determined using validated multiplex ELISAs. Our statistical approach adopted PFS as the primary outcome measure and involved (i) searching for biomarkers with prognostic relevance or which related to between-individual variation in bevacizumab effect; (ii) unbiased determination of cutoffs for putative biomarker values; (iii) investigation of biologically meaningfully predictive combinations of putative biomarkers; and (iv) replicating the analysis on candidate biomarkers in the validation dataset. Results: The combined values of circulating Ang1 (angiopoietin 1) and Tie2 (Tunica internal endothelial cell kinase 2) concentrations predicted improved PFS in bevacizumab-treated patients in the training set. Using median concentrations as cutoffs, high Ang1/low Tie2 values were associated with significantly improved PFS for bevacizumab-treated patients in both datasets (median, 23.0 months vs. 16.2; P = 0.003) for the interaction of Ang1–Tie2 treatment in Cox regression analysis. The prognostic indices derived from the training set also distinguished high and low probability for progression in the validation set (P = 0.008), generating similar values for HR (0.21 vs. 0.27) between treatment and control arms for patients with high Ang1 and low Tie2 values. Conclusions: The combined values of Ang1 and Tie2 are predictive biomarkers for improved PFS in bevacizumab-treated patients with ovarian cancer. These findings need to be validated in larger trials due to the limitation of sample size in this study. Clin Cancer Res; 20(17); 4549–58. ©2014 AACR.

Aim: We propose a simple tool for early prediction of unfavorable long-term evolution of multiple sclerosis (MS). Methods: A Bayesian model allowed us to calculate, within the first year of disease and for each patient, the Bayesian Risk Estimate for MS (BREMS) score that represents the risk of reaching secondary progression (SP). Results: The median BREMS were higher in 158 patients who reached SP within 10 years in comparison with 1087 progression-free patients (0.69 vs. 0.30, p

The 9139 follow-up records of 438 myasthenia gravis (MG) patients were reviewed. Excluding those patients who were diagnosed 5 or more years after symptom onset (n = 37) and those who experienced only oculomotor symptoms throughout follow-up (n = 21), there were 380 patients. A survival analysis approach was used to assess the influence of prognostic factors on the following endpoints: (a) stable complete remission, (b) complete remission of at least 6 months and (c) pharmacological remission of at least 6 months. Early diagnosis was associated with a better prognosis with respect to all endpoints. Thymectomy also improved the prognosis but only for those patients without thymoma. Later MG onset was associated with a higher tendency to achieve pharmacological remission.

Background Although recent meta-analysis trials have shown that exercise training may improve survival after myocardial infarction, the mechanism of this beneficial effect is still unknown. The purpose of this study was to detect possible interactions between exercise training and predictors of prognosis after a first myocardial infarction. Methods and Results Patients with uneventful clinical courses after a first myocardial infarction were randomly assigned to a 4-week training period (125 patients, group 1) or to a control group (131 patients, group 2). Before randomization, all patients underwent a symptom-limited exercise test (28±2 days after myocardial infarction), 24-hour Holter monitoring, and coronary arteriography (31±3 days after the acute episode). After a mean follow-up period of 34.5 months, 18 patients had cardiac deaths (5 in group 1 and 13 in group 2). Multivariate analysis by Cox regression model showed that ejection fraction was the only independent prognostic indicator ( P =.03). Evidence existed of an interaction between ejection fraction and exercise training, showing an effect of physical training on survival that depended on the patient's ejection fraction. Among patients with ejection fractions P =.04), whereas for ejection fractions >40%, the estimated risks for trained and untrained patients were similar. Conclusions These data show that exercise training may prolong survival in post-myocardial infarction patients with depressed left ventricular function. A randomized trial in such patients seems warranted.

We propose a Bayesian approach to the analysis of survival data on multiple time scales. Non-parametric modelling of variation of rates with more than one time scale is achieved using priors which specify smooth variation. Computations are conveniently carried out using Gibbs sampling. We discuss the extension of the method to Bayesian forecasting of rates. Numerical experience of two examples is described.

BACKGROUND: NLRP3 (formerly known as CIAS1 or NALP3) encodes a key component of the inflammasome and is a strong candidate gene for Crohn's disease (CD) susceptibility. A recent study reported significant and internally replicated association between CD and six single nucleotide polymorphisms (SNPs) in a regulatory region 5.3 kb downstream of NLRP3. Independent replication is required to verify these findings. METHODS: In all, 1298 CD cases and 1244 healthy controls were genotyped for the six SNPs using Taqman. Single locus, haplotype, and subphenotype analyses were conducted using logistic regression-based methods and PLINK, respectively. RESULTS: No significant associations were found, either on single locus, subphenotype, or haplotype analysis. CONCLUSIONS: Given our high (>90%) power to replicate findings from the index study, our data suggest either a much smaller effect size for the association between NLRP3 and CD susceptibility than previously reported or the possibility of a false-positive result in the index study. Further studies in other populations are required to determine what role, if any, NLRP3 variants play in CD susceptibility.

We conducted a genome-wide association study testing single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for association with early-onset myocardial infarction in 2,967 cases and 3,075 controls. We carried out replication in an independent sample with an effective sample size of up to 19,492. SNPs at nine loci reached genome-wide significance: three are newly identified (21q22 near MRPS6-SLC5A3-KCNE2, 6p24 in PHACTR1 and 2q33 in WDR12) and six replicated prior observations1, 2, 3, 4 (9p21, 1p13 near CELSR2-PSRC1-SORT1, 10q11 near CXCL12, 1q41 in MIA3, 19p13 near LDLR and 1p32 near PCSK9). We tested 554 common copy number polymorphisms (>1% allele frequency) and none met the pre-specified threshold for replication (P < 10-3). We identified 8,065 rare CNVs but did not detect a greater CNV burden in cases compared to controls, in genes compared to the genome as a whole, or at any individual locus. SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with myocardial infarction risk.

Identification of Crohn's disease (CD)-associated genetic variants is key to understanding pathogenic pathways underlying disease susceptibility. Recent reports of an association between TNFSF15 variants and CD have been modestly replicated in European populations, suggesting heterogeneity at this locus with stronger CD association in Japanese than European populations.We investigated the association between variants in TNFSF15 and CD in 756 CD patients and 636 controls. Disease subphenotype associations were also investigated.TNFSF15 single nucleotide polymorphism (SNP) variants were associated with CD in our panel with peak odds ratio (OR) 1.2 (95% confidence interval [CI] 1.01-1.41) P = 0.033. The presence of a risk haplotype was replicated for the first time in a European population (frequency 67% in cases and 61% in controls) OR = 1.44 (95% CI 1.23-1.68) P = 0.00012. This result mirrors the UK panel in the index study (Yamazaki et al [2005] Hum Mol Genet 14:3499-3506) but is less significant than that reported in Japanese populations. There was no evidence of association with any individual CD subphenotype.Variants in TNFSF15 contribute to overall CD susceptibility in European populations, although to a lesser extent than that seen in the Japanese. Further studies to define the precise disease-causing variants as well as targeted functional studies are now required in human CD as TNFSF15 is a potential target for biological therapies.

Background & Aims: Identification of inflammatory bowel disease (IBD) susceptibility genes is key to understanding pathogenic mechanisms. Recently, the North American IBD Genetics Consortium provided compelling evidence for an association between ileal Crohn’s disease (CD) and the IL23R gene using genome-wide association scanning. External replication is a priority, both to confirm this finding in other populations and to validate this new technique. We tested for association between IL23R and IBD in a large independent UK panel to determine the size of the effect and explore subphenotype correlation and interaction with CARD15. Methods: Eight single nucleotide polymorphism markers in IL23R tested in the North American study were genotyped in 1902 cases of Crohn’s disease (CD), 975 cases of ulcerative colitis (UC), and 1345 controls using MassARRAY. Data were analyzed using χ2 statistics, and subgroup association was sought. Results: A highly significant association with CD was observed, with the strongest signal at coding variant Arg381Gln (allele frequency, 2.5% in CD vs 6.2% in controls [P = 1.1 × 10−12]; odds ratio, 0.38; 95% confidence interval, 0.29–0.50). A weaker effect was seen in UC (allele frequency, 4.6%; odds ratio, 0.73; 95% confidence interval, 0.55–0.96). Analysis accounting for Arg381Gln suggested that other loci within IL23R also influence IBD susceptibility. Within CD, there were no subphenotype associations or evidence of interaction with CARD15. Conclusions: This study shows an association between IL23R and all subphenotypes of CD with a smaller effect on UC. This extends the findings of the North American study, providing clear evidence that genome-wide association scanning can successfully identify true complex disease genes.

Prognostic stratification is relevant in clinical decision making in heart failure (HF). Predictors identified during hospitalization or in clinical trials may be unrepresentative of HF in the community. The aim of this study was to derive and validate, in different clinical settings, a risk stratification model for the prediction of stable HF outcomes. The study included 807 patients, 350 enrolled at discharge from the hospital (44%), 309 in the outpatient clinic (38%), and 148 in the home-care setting (18%). There were 292 patients in the derivation cohort and 515 in the validation cohort. A multivariate logistic analysis was performed to obtain the Cardiovascular Medicine Heart Failure (CVM-HF) index. One-year mortality was 20.8% in the derivation cohort and 20.7% in the validation cohort. The CVM-HF index included cardiac conditions and co-morbidities and stratified the 1-year mortality risk as low (death rate 4%), average (32%), high (63%), and very high (96%). The area under the curve of the receiver-operating characteristic curve was 0.844 (95% confidence interval [CI] 0.779 to 0.89) for the derivation cohort and 0.812 (95% CI 0.76 to 0.86) for the validation cohort. Model performance was equally good in the 3 different HF settings. In a subgroup of 409 patients; the CVM-HF index (area under the curve 0.821, 95% CI 0.79 to 0.89) outperformed the most-used prognostic models (the Charlson index and the Heart Failure Risk Scoring System). In conclusion, the CVM-HF index, a novel prognostic model that is easy to derive and applicable to unselected patients, may represent a valuable tool for the prognostication of stable HF outcomes. (c) 2006 Elsevier Inc. All rights reserved.

Background— We investigated the association between 9 polymorphisms of genes encoding hemostasis factors and myocardial infarction in a large sample of young patients chosen because they have less coronary atherosclerosis than older patients, and thus their disease is more likely to be related to a genetic predisposition to a prothrombotic state. Methods and Results— This nationwide case-control study involved 1210 patients who had survived a first myocardial infarction at an age of Conclusions— This study provides no evidence supporting an association between 9 polymorphisms of genes encoding proteins involved in hemostasis and the occurrence of premature myocardial infarction or protection against it.

With the aid of a Bayesian statistical model of the natural course of relapsing remitting Multiple Sclerosis (MS), we identify short-term clinical predictors of long-term evolution of the disease, with particular focus on predicting onset of secondary progressive course (failure event) on the basis of patient information available at an early stage of disease. The model specifies the full joint probability distribution for a set of variables including early indicator variables (observed during the early stage of disease), intermediate indicator variables (observed throughout the course of disease, prefailure) and the time to failure. Our model treats the intermediate indicators as a surrogate response event, so that in right-censored patients, these indicators provide supplementary information pointing towards the unobserved failure times. Moreover, the full probability modelling approach allows the considerable uncertainty which affects certain early indicators, such as the early relapse rates, to be incorporated in the analysis. With such a model, the ability of early indicators to predict failure can be assessed more accurately and reliably, and explained in terms of the relationship between early and intermediate indicators. Moreover, a model with the aforementioned features allows us to characterize the pattern of disease course in high-risk patients, and to identify short-term manifestations which are strongly related to long-term evolution of disease, as potential surrogate responses in clinical trials. Our analysis is based on longitudinal data from 186 MS patients with a relapsing–remitting initial course. The following important early predictors of the time to progression emerged: age; number of neurological functional systems (FSs) involved; sphincter, or motor, or motor-sensory symptoms; presence of sequelae after onset. During the first 3 years of follow up, to reach EDSS≥4 outside relapse, to have sphincter or motor relapses and to reach moderate pyramidal involvement were also found to be unfavourable prognostic factors.

"Objectives The purpose of this study was to test whether the 9p21.3 variant rs1333040 influences the occurrence of new cardiovascular events and coronary atherosclerosis progression after early-onset myocardial infarction. Background 9p21.3 genetic variants are associated with ischemic heart disease, but it is not known whether they influence prognosis after an acute coronary event. Methods Within the Italian Genetic Study of Early-onset Myocardial Infarction, we genotyped rs1333040 in 1,508 patients hospitalized for a first myocardial infarction before the age of 45 years who underwent coronary angiography without index event coronary revascularization. They were followed up for major cardiovascular events and angiographic coronary atherosclerosis progression. Results Over 16,599 person-years, there were 683 cardiovascular events and 492 primary endpoints: 77 cardiovascular deaths, 223 reoccurrences of myocardial infarction, and 383 coronary artery revascularizations. The rs1333040 genotype had a significant influence (p = 0.01) on the primary endpoint, with an adjusted hazard ratio of 1.19 (95% confidence interval [CI]: 1.08 to 1.37) for heterozygous carriers and 1.41 (95% CI: 1.06 to 1.87) for homozygous carriers. Analysis of the individual components of the primary endpoints provided no significant evidence that the rs1333040 genotype influenced the hazard of cardiovascular death (p = 0.24) or the reoccurrence of myocardial infarction (p = 0.57), but did provide significant evidence that it influenced on the hazard of coronary revascularization, with adjusted heterozygous and homozygous ratios of 1.38 (95% CI: 1.17 to 1.63) and 1.90 (95% CI: 1.36 to 2.65) (p = 0.00015), respectively. It also significantly influenced the angiographic endpoint of coronary atherosclerosis progression (p = 0.002). Conclusions In early-onset myocardial infarction, the 9p21.3 variant rs1333040 affects the progression of coronary atherosclerosis and the probability of coronary artery revascularization during long-term follow-up. (J Am Coll Cardiol 2011;58:426-34) (C) 2011 by the American College of Cardiology Foundation"

Quantitative information on abnormalities of erythropoiesis and mechanisms of anaemia has been obtained in 136 anaemic patients by means of ferrokinetic studies. To derive a functional classification of anaemia based on ferrokinetic parameters, agglomerative hierarchical cluster analysis and principal coordinate analysis were utilized as techniques for unsupervised classification. Two main clusters were found and named anaemia with low potential erythropoiesis and with high potential erythropoiesis, since the most discriminant parameter between them was total erythroid iron turnover, a measure of total erythropoietic activity. A value of total erythropoiesis equal to 4 times the normal was found to discriminate these two types of anaemia in 94% of cases. Within the group with low potential erythropoiesis, three clusters showing different qualitative disturbances of erythropoiesis were singled out. Among patients with high potential erythropoiesis, two clusters were found. A value of effective erythropoiesis equal to 2.5 times the normal was shown to have a high discriminant power between these clusters. This threshold level distinguished between patients having ineffective erythropoiesis or peripheral haemolysis as the major mechanism of anaemia. The present functional classification of anaemia provides a complete picture of the different pathogenetic mechanisms and may represent the basis for a more rational diagnostic approach to erythroid disorders.

In order to determine those factors which influence long-term prognosis in patients with angina at rest associated with transient ST-segment changes, 217 patients undergoing medical treatment were followed for a mean of 39 months. All patients underwent coronary arteriography. Univariate analysis identified 12 variables significantly related to prognosis. These were disease of the left main coronary artery; the number of diseased vessels; left ventricular end-diastolic pressure; ejection fraction; baseline electrocardiogram; presence of prior myocardial infarction; ST-segment depression and ventricular arrhythmias during pain; disease of the proximal anterior descending coronary artery; crescendo angina; hypertension; and age. Use of the Cox regression model for survival analysis revealed only 3 variables which were independent predictors of prognosis. They were disease of the left main coronary artery; the number of diseased vessels and left ventricular end-diastolic pressure. The model allowed stratification of patients into 3 groups. Survival at 3 years was 98% in the low risk group; 82% in the intermediate risk group; and 58% in the high risk group. These data indicate that disease of the left main coronary artery, the number of diseased vessels and left ventricular end-diastolic pressure are the independent predictors of prognosis in angina at rest. These variables may allow stratification of patients into groups having different long-term survivals.

A quantitative evaluation of erythropoiesis was carried out in 12 patients with hairy cell leukaemia (HCL). The results were compared with those obtained in eight patients with aplastic anaemia (AA) in order to define the characteristics of erythroid failure in HCL. Discriminant analysis was applied to both haematological and erythrokinetic parameters of the two disease groups. Plasma iron concentration and MCV were significantly higher in AA, and allowed a perfect separation of the patients. As regards erythrokinetics, values of ineffective erythropoiesis and peripheral haemolysis were able to separate completely the two disease groups, being significantly lower in HCL than in AA. A true erythroid failure was the peculiar erythrokinetic pattern of HCL. This conclusion allows one to speculate on the nature of the stem cell damage in this disease.

The effect of surgical versus medical treatment on long-term prognosis in angina at rest was assessed using the Cox regression model for survival analysis in 400 patients complaining of recurrent episodes of resting chest pain associated with transient repolarization changes. The surgical group included 185 patients, and the medical group 215. Surgically treated patients more frequently had two- and three-vessel disease, while single-vessel disease prevailed in medically treated patients (P less than 0.01). No difference between the two groups was found in mean values of left ventricular end diastolic pressure and ejection fraction. Three variables were identified as independent predictors of prognosis in all patients: left ventricular end-diastolic pressure (P less than 0.001), age greater than 45 years (P less than 0.05), and number of diseased vessels (P less than 0.05). Treatment modality did not result in different long-term survival in the entire population. However, patients with three-vessel disease had a better outcome with surgical than with medical therapy (P less than 0.05). Although our conclusions must be tempered by consideration of the limitations of non-randomized studies, these results show that surgical treatment may improve survival in patients with angina at rest and three-vessel disease.

Previous studies of possible prognostic indicators for multiple sclerosis have been based on "classic" Cox's proportional hazards regression model, as well as on equivalent or simpler approaches, restricting their attention to variables measured either at disease onset or at a few points during follow-up. The aim of our study was to analyse the risk of reaching secondary progression in MS patients with a relapsing-remitting initial course, using two different statistical approaches: a Cox's proportional-hazards model and a Bayesian latent-variable model with Markov chain Monte Carlo methods of computation. In comparison with a standard statistical approach, our model is advantageous because, exploiting all the information gleaned from the patient as it is gradually made available, it is capable to detect even small prognostic effects.

Patients enrolled in a clinical heart transplantation program were evaluated to identify the predictors of prognosis in patients with advanced heart disease and to optimize timing of heart transplantation. Three hundred eighty-eight subjects were consecutively evaluated from 1985 through 1989. One hundred eighty-four patients (47.5%) had dilated cardiomyopathy; 164 patients (42.2%) had ischemic heart disease; 34 patients (8.8%) had valvular heart disease, and six patients (1.5%) had miscellaneous disorders. In each patient, 45 different parameters were considered. During follow-up (mean, 8.4 months) 166 patients underwent heart transplantation; 99 patients died (heart failure, 66 patients; sudden death, 26 patients; thromboembolism, two patients; noncardiac causes, five patients). The actuarial survival was 83% at 3 months, 77% at 6 months, 73% at 9 months, 70% at 1 year, and 59% at 2 years. The median survival time was 28 months. Analysis by Cox proportional hazard regression model revealed seven independent and significant prognostic factors: etiology (p0.05), NYHA class (p0.05), third heart sound (p0.05), diastolic pulmonary artery pressure (p0.05), pulmonary wedge pressure (p0.01), mean systemic blood pressure (p0.05), and cardiac output (p0.05). Cox's analysis allows the computation of patient-specific curves for predictions of residual survival time at any moment during follow-up. Moreover it can be used to calculate a simple prognostic index, which enables stratification of the patient population into three risk classes: patients at high (n = 105), intermediate (n = 160) and low (n = 123) risk of early death. Pairwise comparisons of survival between the classes were significant at 1% level.

The prognosis of chronic heart failure has been studied extensively, but factors predicting short-term outcome in patients with severe chronic heart failure are still poorly defined, and the current indications for heart transplantation as a treatment for end-stage heart failure need on objective analysis.Purpose of the study was to identify the determinants of short-term prognosis in a group of 142 consecutive ambulatory patients (mean age 49.8 +/- 11 years). Referred for heart transplantation because of severe chronic heart failure, the patients were admitted with left ventricular ejection fraction markedly depressed and had had symptoms in spite of an optimal standardized medical therapy for at least 1 month. Baseline clinical and instrumental evaluation included right-sided heart catheterization with a flow-directed multilumen thermodilution catheter, which enables determination of pressures, cardiac output, right ventricular volumes, and ejection fraction.Most patients were in New York Heart Association class III (61%) and IV (24%), and the hemodynamic profile was characterized by mean left ventricular ejection fraction of 20.2% +/- 6%, cardiac index of 2.13 +/- 0.6 l/min/m2, pulmonary capillary wedge pressure of 23.1 +/- 11 mm Hg, right atrial pressure of 7.9 +/- 6 mm Hg, right ventricular ejection fraction of 23.2% +/- 12.4%. During a mean follow-up of 11.1 +/- 9.4 months, 33 patients underwent transplantation (23.4%), 41 died (28.8%), and 68 were still alive (47.8%). There was a substantial overlap in left ventricular ejection fraction between patients divided on the basis of outcome, whereas right ventricular ejection fraction was significantly lower in patients who died or underwent transplantation. Cox multivariate analysis showed three independent prognostic variables: cause (p = 0.03), heart failure score (p = 0.001), and right ventricular ejection fraction (p = 0.000). Short-term survival (10 months) was significantly (p = 0.000) different in patients withor = 24% or24% right ventricular ejection fraction. Statistical analysis identified right ventricular ejection fraction as the single variable to be highly correlated with an increased risk of early death.This study suggests that right ventricular function is a crucial determinant of short-term prognosis in severe chronic heart failure. Statistical analysis identified right ventricular ejection fraction, determined by thermodilution during right-sided heart catheterization, as the single most important predictor of short-term prognosis in a large cohort of patients who had symptoms in spite of a standardized, optimized, multipharmacologic treatment. The variable allows a useful risk stratification in patients with severe chronic heart failure and uniformly depressed left ventricular ejection fraction and provides guidance in the assessment of indications and timing for transplantation.

Aim of this study was to evaluate the factors affecting the duration of the recovery time (RT) after a positive exercise stress test and to define its relationship with the extent of coronary artery disease (CAD).We studied 109 consecutive patients with a positive exercise test and proven coronary disease.RT was neither related to the severity of CAD, nor to exercise duration, rate-pressure product at the end of the exercise and maximum ST segment depression. A significant linear relationship was found between RT and the time of ischemia during exercise (IT) (r = 0.66, p.001). This relationship was analyzed separately in patients (pts) with advanced (Group I) and in pts with less severe CAD (Group II). The regression line of the data showed a similar slope but a higher y-axis intercept in Group I than in Group II (p.05). The RT/IT ratio was in fact significantly higher in Group I than in Group II (3.0 +/- 1.3 vs 1.7 +/- 0.7, p.0001). Discriminant analysis was performed to predict the presence of advanced CAD: using the RT/IT ratio instead of RT correct classification rate of the model increased from 81.4 to 86.7%, predictive accuracy from 73.7 to 85.3% and true negative rate from 85.3 to 87.4%.These results suggest that the normalization of the recovery time by time of ischemia during the test provides a simple and useful index for the prediction of the extent of coronary artery disease.

The dependence of survival time on a set of prognostic factors was explored by means of Cox's regression model in 137 cases of myelofibrosis with myeloid metaplasia (MMM). The following parameters recorded at diagnosis proved to be important independent indicators of a poor prognosis: a higher value for age, a lower value for Hb concentration, a higher value for immature myeloid cells in peripheral blood (IMC), a lower value for total erythroid iron turnover (TEIT), and a bone marrow red cell aplasia (RCA). A prognostic classification tree was constructed whose terminal nodes (risk groups), described by simple logical conditions upon important indicators, were characterized by significantly different expected survival. The two extreme risk groups lend themselves to a simple, but complete description. The low-risk group (19.7% of the sample) comprises cases who had the diagnosis of MMM before age 45 and a number of IMC constantly lower than 24%. The actuarial proportion of patients surviving at 15 years was 100%. The high-risk group (29.9% of cases) comprises patients with age greater than 45 and Hb lower than 13 g/dl, associated with RCA, or with a relatively decreased erythropoiesis (TEIT lower than 2 times the normal) or with IMC greater than 24%. Seven out of the 11 who died within this group developed blastic crisis. Median survival time of the group was 69 months.