Progress in Cardiovascular Diseases RSS feed: Current Issue. Each issue of Progress in Cardiovascular Diseases comprehensively covers a single topic in the understanding and treatment of disorders of the heart and circulation. Some issues include special articles, definitive reviews that capture the state of the art in the management of particular clinical problems in cardiology. Recent Topics The Myths Surrounding Diastolic Heart Failure Guest Editor: Dirk L. Brutsaert Hypertension Guest Editor: Franz Messerli Resynchronization Therapy Guest Editor: Jonathan S. Steinberg Atrial Fibrillation Guest Editor: Albert L. Waldo Diastolic Heart Failure Guest Editor: Michael R. Zile Troponins Drug Class Effects Guest Editor: James A. Reiffel Chest Pain Units Guest Editors: Ezra A. Amsterdam and J. Douglas Kirk http://www.onlinepcd.com/?rss=yesElsevier Inc.en © 2011 Published by Elsevier Inc. All rights reserved. Progress in Cardiovascular Diseases0033-0620544January 2012 © 2011 Published by Elsevier Inc. All rights reserved. healthpermissions@elsevier.comhttp://www.onlinepcd.com/article/PIIS0033062011002313/abstract?rss=yesMasthead10.1016/S0033-0620(11)00231-3Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5IFCIFChttp://www.onlinepcd.com/article/PIIS0033062011002283/abstract?rss=yesThis special issue focuses on strengths and weaknesses of conducting secondary analyses in clinical trials and other studies. A discussion of the analytic approaches and limitations of such analyses are presented. Secondary analyses are defined as any analyses that are not concerned with the primary outcome(s) and the primary hypothesis on which the study sample size is based.IntroductionBarbara C. Tilley, Barry R. Davis10.1016/j.pcad.2011.11.003Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations329329http://www.onlinepcd.com/article/PIIS0033062011001356/abstract?rss=yesAbstract: There are two types of data analyses of randomized clinical trials (RCTs). The primary analyses are pre-specified in the protocol and the findings form the basis for recommendations and clinical decisions. They typically adhere to the intention-to-treat principle. Secondary analyses are supplemental and of various sorts. Although some may be pre-specified, many are not. We encourage the use of the rich sources of data from large RCTs for these secondary purposes. Depending on the kinds of secondary analyses, whether they are pre-specified, and whether intention-to-treat analysis is used, the results range from being quite conclusive to being hypothesis generating. In this article we answer four questions related to secondary analysis with emphasis on sharing of data primarily from NIH-sponsored trials: Who has access to this information? What questions can be asked? What are the requirements? What are the common challenges?Approaches to Data Analyses of Clinical TrialsCurt D. Furberg, Lawrence M. Friedman10.1016/j.pcad.2011.07.002Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations330334http://www.onlinepcd.com/article/PIIS0033062011001800/abstract?rss=yesAbstract: There is concern in published reports and reviews that patients are being harmed or denied effective treatment by the use of questionable results from secondary analyses of data from clinical trials. A well-reported secondary analysis must make clear to the reader the uncertainty of the result --so clear, in fact, that it should be an obvious part of the conclusions that implementation should await confirmation as the primary outcome in an adequately powered trial. Those who write, review and publish these reports have a responsibility to ensure that reports accurately describe the sources of uncertainty, explain complex methods and their weaknesses with clarity, and convince readers to require better evidence before changing their practice.Secondary Analysis of Clinical Trials—A Cautionary NoteJohn R. Marler10.1016/j.pcad.2011.09.006Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations335337http://www.onlinepcd.com/article/PIIS0033062011001381/abstract?rss=yesAbstract: Subgroup analysis in a clinical trial is the evaluation of the effect of a randomly allocated intervention within only a fraction of the patients in the entire research cohort. This article provides several examples of the use of subgroup analysis, discusses some of the interpretative difficulties that occur during the assessment of the effect of therapy within subgroups, and provides a summary of recent recommendations on reporting subgroup analyses in the literature. Although subgroup analyses can provide new, provocative, and sometimes clinically relevant findings, this group of evaluations must be handled with extreme care.Rudiments of Subgroup AnalysesLemuel A. Moyé10.1016/j.pcad.2011.07.005Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations338342http://www.onlinepcd.com/article/PIIS0033062011001812/abstract?rss=yesAbstract: A surrogate end point is one that is used as a substitute for a clinical end point of more direct interest, usually for reasons of practicality, and that is expected to predict clinical benefit. Surrogate end points play a critical role in the advancement of all medical research, and cardiovascular (CV) research in particular. However, the relationship between a surrogate end point and its clinical end point is usually complex, and there are many examples where results based on surrogates have proved to be misleading. Secondary analyses of existing clinical trial data are likely to involve surrogate end points, if only because clinical end points will have been extensively studied as part of the primary analysis of a trial large enough to collect useful clinical end point data. Validation of a surrogate end point is a laudable goal for a secondary analysis of a large clinical end point trial (or meta-analysis of multiple smaller trials), and the result may be an important new tool for further study of a class of compounds in a particular disease context. Secondary analyses using surrogate end points may also provide new insight into disease or treatment mechanism, but as with any surrogate end point analysis, the results can mislead, and the existing literature is heavy on application and light on methodology. Surrogate end points often substitute efficiency for clarity, and while many interesting and potentially informative secondary analyses of CV trials will involve surrogates, results are likely to be ambiguous and should be interpreted with care.Surrogate End Points in Secondary Analyses of Cardiovascular TrialsKevin A. Buhr10.1016/j.pcad.2011.09.007Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations343350http://www.onlinepcd.com/article/PIIS003306201100171X/abstract?rss=yesAbstract: Clinical trials may furnish data to conduct economic analyses. An economic analysis requires us to identify all opportunity costs associated with the intervention over the time horizon chosen for the analysis and enumerate the improvements in benefits from the intervention of interest. We review the basic steps used when performing economic studies based on secondary analysis of data from clinical trials using examples from myocardial infarction studies. Different types of economic analyses and the potential contributions of Markov modeling are described. Issues of measuring quality of life, patient utilities, cost of care, and potential sources of cost data are reviewed. The interpretation of incremental cost-effectiveness ratios is discussed and economic benchmarks for defining good and poor value interventions are provided.Economic Analysis of Secondary Trial DataKit N. Simpson, Barbara C. Tilley10.1016/j.pcad.2011.08.004Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations351356http://www.onlinepcd.com/article/PIIS003306201100226X/abstract?rss=yesAbstract: Multiple outcomes (or multiple endpoints), such as mortality and recurrent myocardial infarction, are increasingly common in clinical trials and are often of interest in secondary analyses. Traditionally, a clinical trial protocol is built around a single event as its primary outcome, with several secondary outcomes specified, the analyses for which lack the same level of power. To accommodate all the relevant outcomes and to increase the power of the comparison in trials evaluating the efficacy of treatments for coronary heart disease, investigators often chose to construct a composite outcome. The more conventional composite outcome fails to account for the relative importance and the relationship (correlation) among its components. The purpose of this work is to demonstrate the usefulness of the Global Statistical Test, which considers the correlation between multiple outcomes, as an alternative strategy for these situations and to demonstrate its effect on hypothesis testing and power analysis issues in comparison with the traditional composite outcome analysis. Data from the cardiovascular clinical trial Systolic Hypertension in the Elderly Population are used as an example.Comparison of the Global Statistical Test and Composite Outcome for Secondary Analyses of Multiple Coronary Heart Disease OutcomesSarah Baraniuk, Roann Seay, Arup K. Sinha, Linda B. Piller10.1016/j.pcad.2011.11.001Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations357361http://www.onlinepcd.com/article/PIIS0033062011002258/abstract?rss=yesAbstract: Coronary artery disease and myocardial infarction represent a major cause of morbidity and mortality. Four randomized, controlled, double-blind clinical trials —VALIANT, EPHESUS, OPTIMAAL, and CAPRICORN evaluated pharmacologic intervention in a total of 28,771 high-risk patients following acute MI complicated with signs of heart failure or evidence of left ventricular dysfunction. The demographic profiles of the 4 study cohorts were similar. The High-Risk MI Database Initiative constructed a common database by merging the data captured by these 4 large trials. The merged data set did not contain the randomized study treatment, so no comparisons could be made between the agents investigated. A total of more than 17,600 subjects experienced a cardiovascular end point. Approximately 5100 deaths occurred, and more than 15,700 subjects experienced a hospitalization.The primary objectives of this initiative were to use this large database to define more precisely the prognostic profile of this high-risk population, to perform rigorous, adequately-sized, subset analyses, to provide epidemiologic information and event rate estimation based on baseline demographics.The methodological challenges and limitations of such an analyses are discussed. It is proposed that some thoughtful foresight and planning could enable us to use the large number of clinical events that accrue during randomized clinical trials to address questions of scientific and clinical interest.The High-Risk Myocardial Infarction Database InitiativeKenneth Dickstein, Judith Bebchuk, Janet Wittes10.1016/j.pcad.2011.10.001Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations362366http://www.onlinepcd.com/article/PIIS0033062011001708/abstract?rss=yesAbstract: Randomized clinical trials (RCTs) are considered the gold standard approach to establish relationships between exposures/treatments and outcomes. Analyses that examine the association between the randomized factor and outcomes are “protected by randomization” from potential confounding factors. Despite limitations largely arising from the lack of generalizability of findings, RCTs offer a rich environment to assess associations between other factors and outcomes which are by definition observational epidemiological studies. Herein we discuss the limitations of these analyses, but also the opportunities that arise from the use of observational epidemiological assessments that can be performed: 1) between factors assessed prior to randomization, 2) analyses of longitudinal outcomes both in the cohort all together, and among subjects randomized to placebo treatment, and 3) analyses of “associated” series of patients (such as non-randomized registries or screenees for the RCT). While these assessments of associations are not protected by randomization, with proper planning these assessments within the RCT framework can be done in a powerful and effective manner.Observational Epidemiology Within Randomized Clinical Trials: Getting a Lot for (Almost) NothingGeorge Howard, Virginia J. Howard10.1016/j.pcad.2011.08.003Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Secondary Analyses in Cardiovascular Clinical Trials - Statistical and Other Considerations367371http://www.onlinepcd.com/article/PIIS0033062011002271/abstract?rss=yesAbstract: Implantable cardioverter-defibrillator (ICD) therapy improves survival in patients with significant left ventricular systolic dysfunction. Although this lifesaving therapy has many benefits, inappropriate ICD shocks may increase morbidity and mortality. With rates of inappropriate therapy quoted as high as 35% at 3 years after device implantation, numerous strategies have been evaluated to decrease the overall incidence of inappropriate therapy. Changes in programming algorithms, which allow for longer detection windows for rhythm analysis, extended the use of antitachycardia pacing, and improved supraventricular tachycardia discriminators, hold promise for decreasing inappropriate ICD therapy. In this review, we discuss the data summarizing the adverse effects of ICD shocks on outcomes, clinical trial–based programming algorithms to decrease inappropriate shocks, and the expanded role of antitachycardia pacing in ventricular arrhythmia management.Expanding the Benefits of Implantable Cardioverter-Defibrillator Therapy: “Is Less More”?Larry R. Jackson, James P. Daubert, Kevin L. Thomas10.1016/j.pcad.2011.11.002Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5Special Article372378http://www.onlinepcd.com/article/PIIS0033062011002325/abstract?rss=yesContents10.1016/S0033-0620(11)00232-5Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5FrontmatterA1A1http://www.onlinepcd.com/article/PIIS0033062011002337/abstract?rss=yesRecent Topics10.1016/S0033-0620(11)00233-7Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5FrontmatterA2A2http://www.onlinepcd.com/article/PIIS0033062011002349/abstract?rss=yesEditorial Board10.1016/S0033-0620(11)00234-9Progress in Cardiovascular Diseases 54, 4 (2012)2012-01-01Progress in Cardiovascular Diseases2012-01-01544S0033-0620(11)X0007-5FrontmatterA6A6