Impact of proton pump inhibitor treatment on gastrointestinal bleeding associated with non-steroidal anti-inflammatory drug use among post-myocardial infarction patients taking antithrombotics: nationwide study

Study question What is the effect of proton pump inhibitors (PPIs) on the risk of gastrointestinal bleeding in post-myocardial infarction patients taking antithrombotics and treated with non-steroidal anti-inflammatory drugs (NSAIDs)? Methods This was a nationwide cohort study based on linked administrative registry data from all hospitals in Denmark between 1997 and 2011. The study included patients aged 30 years and over admitted with a first myocardial infarction who survived at least 30 days after discharge. The association between PPIs and risk of gastrointestinal bleeding according to NSAID plus antithrombotic therapy was estimated using adjusted time dependent Cox regression models. Study answer and limitations The use of PPIs was independently associated with decreased risk of gastrointestinal bleeding in post-myocardial infarction patients taking antithrombotics and treated with NSAIDs. Of 82 955 post-myocardial infarction patients (mean age 67.4 years, 64% (n=53 070) men), all of whom were taking single or dual antithrombotic therapy, 42.5% (n=35 233) filled at least one prescription for NSAIDs and 45.5% (n=37 771) received PPIs. Over a mean follow-up of 5.1 years, 3229 gastrointestinal bleeds occurred. The crude incidence rates of bleeding (events/100 person years) on NSAID plus antithrombotic therapy were 1.8 for patients taking PPIs and 2.1 for those not taking PPIs. The adjusted risk of bleeding was lower with PPI use (hazard ratio 0.72, 95% confidence interval 0.54 to 0.95) regardless of antithrombotic treatment regimen, type of NSAID, and type of PPI used. The main limitation of the study is its observational non-randomised design. The results suggest that PPI treatment probably has a beneficial effect regardless of underlying gastrointestinal risk and that when NSAIDs cannot be avoided in post-myocardial infarction patients, physicians might prescribe a PPI as well. The study does not clarify whether PPIs might be safely omitted in specific subgroups of patients with a low risk of gastrointestinal bleeding. What this study adds In post-myocardial infarction patients, bleeding complications have been associated with both antithrombotic and NSAID treatment. Concurrent use of PPIs was independently associated with a decreased risk of gastrointestinal bleeding in post-myocardial infarction patients taking antithrombotics and NSAID, regardless of antithrombotic treatment regimen, type of NSAID, and type of PPI used. Funding, competing interests, data sharing AMSO has received a grant from the Danish Council of Independent Research (grant 12-132760). GHG is supported by an unrestricted research scholarship from the Novo Nordisk Foundation

A Guided Workbook Intervention (WorkPlan) to Support Work-Related Goals Among Cancer Survivors: Protocol of a Feasibility Randomized Controlled Trial

Background: Returning to and staying at work following illness is associated with better physical and psychological functioning. Not working has been shown to be associated with reduced self-esteem, lowered self-efficacy, and decreased belief in one's ability to return to the workplace. Although there is a growing body of research looking at what predicts return to work following cancer treatment, there are fewer studies examining interventions targeting return to work. Objective: The primary objective is to assess the feasibility and acceptability of a theoretically led workbook intervention designed to support cancer patients in returning to work to inform a fully powered randomized controlled trial (RCT). Methods: This is a multicenter feasibility RCT where the main analysis uses a qualitative approach. Sixty participants (aged 18-65 years) who have received a diagnosis of cancer and who intend to return to work will be randomized to either the WorkPlan intervention group or a usual care group (ratio 1:1). Participants in the intervention group will receive a guided workbook intervention (which contains activities aimed at eliciting thoughts and beliefs, identifying targets and actions, and concrete steps to achieve goals) and will receive telephone support over a 4-week period. The primary outcome measure is time taken to return to work (in days), and secondary outcome measures include mood, quality of life, illness perceptions, and job satisfaction. Data will be collected through postal questionnaires administered immediately postintervention and at 6- and 12-month follow-ups. In addition, interviews will be undertaken immediately postintervention (to explore acceptability of the intervention and materials) and at 12-month follow-up (to explore perceptions of participation in the trial and experiences of returning to work). Results: Enrollment for the study will be completed in May 2016. Data analysis will commence in April 2017, and the first results are expected to be submitted for publication in late 2017. Conclusions: Currently no standardized return-to-work intervention based on targeting cancer patient beliefs is in existence. If the intervention is shown to be feasible and acceptable, the results of this study will inform a future full RCT with the potential to provide a valuable and cost-efficient tool in supporting cancer survivors in the return-to-work process

PredictABEL: an R package for the assessment of risk prediction models

The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL (http://www.genabel.org) and CRAN (http://cran.r-project.org/)

The aging Canadian population and hospitalizations for acute myocardial infarction: projection to 2020

<p>Abstract</p> <p>Background</p> <p>The risk of experiencing an acute myocardial infarction (AMI) increases with age and Canada's population is aging. The objective of this analysis was to examine trends in the AMI hospitalization rate in Canada between 2002 and 2009 and to estimate the potential increase in the number of AMI hospitalizations over the next decade.</p> <p>Methods</p> <p>Aggregated data on annual AMI hospitalizations were obtained from the Canadian Institute for Health Information for all provinces and territories, except Quebec, for 2002/03 and 2009/10. Using these data in a Poisson regression model to control for age, gender and year, the rate of AMI hospitalizations was extrapolated between 2010 and 2020. The extrapolated rate and Statistics Canada population projections were used to estimate the number of AMI hospitalizations in 2020.</p> <p>Results</p> <p>The rates of AMI hospitalizations by gender and age group showed a decrease between 2002 and 2009 in patients aged ≥ 65 years and relatively stable rates in those aged < 64 years in both males and females. However, the total number of AMI hospitalizations in Canada (excluding Quebec) is projected to increase by 4667 from 51847 in 2009 to 56514 in 2020, a 9.0% increase. Inflating this number to account for the unavailable Quebec data results in an increase of approximately 6200 for the whole of Canada. This would amount to an additional cost of between $46 and$54 million and sensitivity analyses indicate that it could be between $36 and$65 million.</p> <p>Conclusions</p> <p>Despite projected decreasing or stable rates of AMI hospitalization, the number of hospitalizations is expected to increase substantially as a result of the aging of the Canadian population. The cost of these hospitalizations will be substantial. An increase of this extent in the number of AMI hospitalizations and the ensuing costs would significantly impact the already over-stretched Canadian healthcare system.</p

The impact of emotional well-being on long-term recovery and survival in physical illness: a meta-analysis

This meta-analysis synthesized studies on emotional well-being as predictor of the prognosis of physical illness, while in addition evaluating the impact of putative moderators, namely constructs of well-being, health-related outcome, year of publication, follow-up time and methodological quality of the included studies. The search in reference lists and electronic databases (Medline and PsycInfo) identified 17 eligible studies examining the impact of general well-being, positive affect and life satisfaction on recovery and survival in physically ill patients. Meta-analytically combining these studies revealed a Likelihood Ratio of 1.14, indicating a small but significant effect. Higher levels of emotional well-being are beneficial for recovery and survival in physically ill patients. The findings show that emotional well-being predicts long-term prognosis of physical illness. This suggests that enhancement of emotional well-being may improve the prognosis of physical illness, which should be investigated by future research

Evaluating the Quality of Research into a Single Prognostic Biomarker: A Systematic Review and Meta-analysis of 83 Studies of C-Reactive Protein in Stable Coronary Artery Disease

Background Systematic evaluations of the quality of research on a single prognostic biomarker are rare. We sought to evaluate the quality of prognostic research evidence for the association of C-reactive protein (CRP) with fatal and nonfatal events among patients with stable coronary disease. Methods and Findings We searched MEDLINE (1966 to 2009) and EMBASE (1980 to 2009) and selected prospective studies of patients with stable coronary disease, reporting a relative risk for the association of CRP with death and nonfatal cardiovascular events. We included 83 studies, reporting 61,684 patients and 6,485 outcome events. No study reported a prespecified statistical analysis protocol; only two studies reported the time elapsed (in months or years) between initial presentation of symptomatic coronary disease and inclusion in the study. Studies reported a median of seven items (of 17) from the REMARK reporting guidelines, with no evidence of change over time. The pooled relative risk for the top versus bottom third of CRP distribution was 1.97 (95% confidence interval [CI] 1.78–2.17), with substantial heterogeneity (I2 = 79.5). Only 13 studies adjusted for conventional risk factors (age, sex, smoking, obesity, diabetes, and low-density lipoprotein [LDL] cholesterol) and these had a relative risk of 1.65 (95% CI 1.39–1.96), I2 = 33.7. Studies reported ten different ways of comparing CRP values, with weaker relative risks for those based on continuous measures. Adjusting for publication bias (for which there was strong evidence, Egger's p<0.001) using a validated method reduced the relative risk to 1.19 (95% CI 1.13–1.25). Only two studies reported a measure of discrimination (c-statistic). In 20 studies the detection rate for subsequent events could be calculated and was 31% for a 10% false positive rate, and the calculated pooled c-statistic was 0.61 (0.57–0.66). Conclusion Multiple types of reporting bias, and publication bias, make the magnitude of any independent association between CRP and prognosis among patients with stable coronary disease sufficiently uncertain that no clinical practice recommendations can be made. Publication of prespecified statistical analytic protocols and prospective registration of studies, among other measures, might help improve the quality of prognostic biomarker research