bluuebunny/crossref_metadata_2025_split huggingface dataset:
Postmenopausal Estrogen/Progestin Intervention Trial (
PEPI
)
Authors: Langer Robert D. 
Published: June 2008

Abstract
The Postmenopausal Estrogen/Progestin Interventions (PEPI) trial was a 3‐year randomized double‐masked placebo controlled trial conducted between 1989 and 1994. This aim of this study was to test the effects of four active hormone replacement treatments (HRT) on cardiovascular risk factors in women between 1 and 10 years postmenopausal after multiple observational studies suggested that HRT might reduce cardiovascular disease. Primary endpoints were changes in HDL cholesterol, systolic blood pressure (SBP), 2‐hour post‐challenge insulin, and fibrinogen. It enrolled 875 women into five groups defined by estrogen, progestin, and dosing pattern. Groups were placebo/placebo, daily conjugated equine estrogen 0.625 mg (CEE)/placebo, CEE/medroxyprogesterone acetate (MPA) 10 mg for 12 days per month, CEE/MPA 2.5 mg daily, and CEE/micronized progesterone (MP) 200 mg for 12 days per month. Compared with placebo, all treatments improved HDL except CEE alone; CEE/MP was significantly better than CEE/either MPA. All treatments reduced fibrinogen. No significant differences were observed in SBP or insulin. Endometrial safety was a secondary endpoint for the 60% of subjects with a uterus. CEE/placebo was associated with > 20% annual incidence of hyperplasia, whereas all regimens with a progestin were effective in preventing disease. Bone mineral density, which was another secondary endpoint, was improved by all treatments.
Women's Health Initiative Dietary Trial
Authors: Mossavar‐Rahmani Yasmin , Tinker Lesley F. 
Published: June 2008

Abstract
The Women's Health Initiative (WHI) Dietary Modification Randomized Controlled Trial (DMT) was the largest randomized, controlled clinical trial to test the effects of a low‐fat dietary pattern on decreasing the risk of incident breast cancer, colorectal cancer, and heart disease. In all, 48,835 healthy post‐menopausal women aged 50–79 years were recruited across 40 clinical centers throughout the United States. Among postmenopausal women, a low‐fat dietary pattern did not result in a statistically significant reduction in invasive breast cancer risk, colorectal cancer risk, or heart disease risk over an 8.1 year average follow‐up period; however, some evidence suggests that risk for breast cancer was reduced among women who entered the study consuming dietary fat within the highest quartile and who demonstrated the greatest overall reduction in dietary fat intake in response to the dietary intervention. Furthermore, the nonsignificant trends observed suggest that any reduced risk associated with a low‐fat dietary pattern may only be evident after a longer follow‐up period. Thus, a planned, nonintervention follow‐up is underway to allow for continued longitudinal evaluation and potentially a more definitive comparison.
Global Assessment Variables
Authors: Tilley Barbara , Huang Peng , O'Brien Peter C. 
Published: June 2008

AbstractMultiple outcomes are often collected for an evaluation of a treatment's effect on disease or quality of life or other underlying condition. When multiple outcomes are being assessed, and no predefined and validated composite outcome (summary measure) exists, two classes of statistical tests have been developed that address two different scientific questions. Tests in one class are designed to test whether a treatment effect is observed for any of the outcomes. Tests in the other class are designed to test whether a treatment confers an overall benefit (or harm) to patients. We provide a brief survey of global statistical tests (GST) of the second class. Each GST is discussed in terms of its motivation, approach to conducting the test, and some basic properties of the test. To facilitate the interpretation of the GST, we use the concept of a global treatment effect (GTE) to quantify the treatment's overall effect on multiple outcomes. We provide examples of the application of GSTs to clinical trials along with recommendations for choosing outcomes to include in the GST.
Drift (For Interim Analysis)
Authors: Reboussin David M. 
Published: June 2008

AbstractDrift, in the context of the design and analysis of group sequential plans for clinical trials, refers to the mean of a Brownian motion process describing the accumulating evidence on the treatment difference. Although the implementation of group sequential testing does not require explicit reference to Brownian motion process, some understanding of it simplifies the discussion of certain aspects, especially sample size determination, estimation, and stochastic curtailment.
Mother to Child Human Immunodeficiency Virus Transmission Trials
Authors: Shapiro David E. 
Published: June 2008

Abstract
Mother‐to‐child transmission (MTCT) of human immunodeficiency virus type 1 (HIV) can occur through three major routes: through the placental barrier during gestation, via contact with maternal bodily fluids during labor and delivery, and by ingestion of breast milk after delivery; most MTCT is believed to occur close to the time of or during childbirth. Prevention of MTCT (PMTCT) is one of the most successful areas in HIV clinical research. Interventions to prevent MTCT have been developed for two different settings: the United States and other developed countries with access to medications, medical infrastructure, and safe replacement feeding so that breastfeeding can be discouraged; and resource‐limited countries with limited access to medications and clean water, and where breastfeeding is critical. This article describes four important PMTCT randomized trials, including two trials of key interventions used in developed countries and two trials of interventions feasible in resource‐limited settings.
Stepped Wedge Design
Authors: Hughes James P. 
Published: June 2008

Abstract
Stepped wedge trials are randomized trials in which each randomization unit first receives the control condition and then crosses over to receive the intervention. However, the time at which the intervention is provided to each unit is randomized. Stepped wedge trials may be either individually or cluster‐randomized. The stepped wedge design is particularly useful when it is not feasible to provide the intervention to everyone or every community at once, and for evaluating the effectiveness of interventions that have been shown to be efficacious in a more limited, research setting and are now being scaled up to the community level. This design is also useful for evaluating temporal changes in the intervention effect.
Cox Proportional Hazard Model
Authors: Cai Jianwen , Zeng Donglin 
Published: June 2008

AbstractIn this article, we provide an overview on the Cox proportional hazards model. We discuss the partial likelihood approach for parameter estimation and inference. Some practical issues in using the Cox regression model are discussed, including how to handle tied data, incorporate time‐dependent covariates, and fit the Cox regression model in stratified population. The article also reviews some practical ways for assessing proportional hazards assumption; one authentic example is used to illustrate data analysis using the Cox regression model. Finally, we list a few extensions of the Cox regression model.
Intraclass Correlation Coefficient
Authors: Campbell Marion K. , Grimshaw Jeremy M. , Piaggio Gilda 
Published: June 2008

Abstract
Increasingly researchers are recognizing that in many situations, using a cluster‐randomized trial (in which groups of individuals are randomized rather than individuals directly) may be more appropriate than an individually randomized trial. Cluster‐randomized trials are more complex to design, however, primarily because observations on individuals within the same cluster tend to be correlated. The statistical measure of this correlation within clusters is known as the intraclass or intracluster correlation coefficient (ICC). In this article, we discuss the measurement and impact of the ICC on the design and analysis of cluster‐randomized trials. In particular we outline how an ICC can be calculated, the likely magnitude of ICCs in specific settings, the factors that influence the ICC estimate, how an ICC should be reported, and the impact of the ICC on sample‐size requirements and analysis.
Regulatory Definitions
Authors: Traverso Kelly L. 
Published: June 2008

Abstract
Since President Roosevelt signed the Federal Food, Drug and Cosmetic law in 1938, drugs in clinical development must be tested for safety before they can be marketed. As a result, the role of safety in premarketing development is to determine that the product benefit exceeds the risks, which contributes in the efficacy of clinical drug development. This assessment is done throughout the phases of clinical development (See “Study Design: Phases I–V”). For the product benefit to be evaluated, safety information needs to be collected on the patients that are involved in the clinical studies. One of the markers that is evaluated is whether the patient had an adverse event (often referred as a side effect) while enrolled in the study. Sponsors of clinical studies are mandated by the Food and Drug Administration (FDA) and other global health authorities to report these adverse events (see also “Regulatory Issues”). These events are reported in timeframes outlined in the regulations and differ depending on the type of adverse event. This section will define what an adverse event is, the timeframe that sponsors have to report the event, and how the sponsor reports the information collected to the regulatory agencies.
Sensitivity, Specificity and Receiver Operator Characteristic (
ROC
) Methods
Authors: Kraemer Helena Chmura 
Published: June 2008

Abstract

Three of the most common problems in medical research are as follows: (
1
) evaluating a medical test against a diagnostic criterion in a population, (
2
) choosing the best among available tests, and finally (
3
) developing the best combination of medical tests. In 1979, a
Lancet
editorial commented that
“The assessment of diagnostic methods belongs to the backwoods of clinical research. New treatments are submitted to thorough testing and books are written on the methodology of the controlled therapeutic trial; but no standards have been fixed for the assessment of diagnostic methods.”
Since 1979, some progress has been reflected in the Standards for Reporting of Diagnostic Accuracy (STARD) guidelines, but statistical methods remain much less developed than the methods for the assessment of treatments in randomized clinical trials. As a result, medical tests often enter general clinical use with little or no convincing documentation of their accuracy, which then has major repercussions on patient health and medical costs.
Microarray
Authors: Page Grier P. , Cui Xiangqin 
Published: June 2008

Abstract
Microarray technology had a troubling beginning, but many problems resulted from the growing pains of this technology that, like many new things, was initially more promise than delivery. However, the promise has finally come to fruition, and microarray technology has developed into a mature technology that can generate valid and useful results in basic, translational, clinical trials, and now clinical practice. Much maturity resulted from the realization that microarrays are not some magic tool, but rather are like any other measurement device and that unless microarray experimentation is coupled with good experimental practices, it will not yield valid results or, worse yet, may lead to misleading results.
Treatment Interruption
Authors: Grund Birgit 
Published: June 2008

AbstractInterruption of active drug treatment in clinical trials can be classified broadly as therapeutic treatment interruption (TI), in which the potential therapeutic benefit of supervised interruption of treatment is investigated, and analytic TI, in which participants are randomized to stopping versus continuing active treatment; the TI arm serves as control group. Design issues for therapeutic TI trials are discussed in the example of a trial in HIV/AIDS.Analytic TIs are used in therapeutic HIV vaccine trials, in randomized discontinuation designs, and in other situations. The use of a randomized discontinuation design for a Phase II drug trial in cancer is discussed.
Hypothesis Testing
Authors: LaVallee Nicole M. , Stepanians Miganush N. 
Published: June 2008

Abstract

The objectives and methods of hypothesis testing are described. Key concepts in hypothesis testing are defined and explained, including null and alternative hypotheses, one‐sided and two‐sided tests, Type I and Type II errors, significance level, power, test statistic, critical value, statistical significance, and
P
‐value. Examples of one‐sample and two‐sample tests of population means are provided to illustrate how hypothesis tests are performed and interpreted.
Dermatology Trials
Authors: Feldman Steven R. , Clark Adele R. 
Published: June 2008

AbstractOne characteristic of many skin disease clinical trials is that they involve topical treatments. The direct application of potent topical medications can have excellent efficacy while minimizing the potential for systemic side effects. A limitation of trials in dermatology is that topical treatment tends to be more difficult for patients to use than oral medications. An advantage of dermatologic trials is that the outcomes are readily visible on the skin. Investigator and patient assessed outcomes can be used. A trial of a topical clobetasol illustrates the rapid effects of the drug and the relative safety over the short term.
Logrank Test
Authors: Hopkins Alan 
Published: June 2008

AbstractThe nonparametric log‐rank test compares two or more independent estimated time‐to‐event curves (survival functions) based on censored data. Right‐censored data originates in clinical trials when measuring time‐to‐an‐event. Time‐to‐infection, time‐to‐disease progression, and time‐to‐death are examples of clinical endpoints that may not be observed on all subjects randomized in a clinical trial because of a fixed follow‐up period or dropout. We shall refer to time‐to‐event data with right censoring as survival data. The log‐rank test is the most commonly used test for comparing survival functions among a class of weighted log‐rank statistics. The log‐rank test is the most powerful nonparametric test to detect proportional hazards alternatives. It is closely related to the Cox regression model.
Eastern Cooperative Oncology Group (
ECOG
)
Authors: Gray Robert J. 
Published: June 2008

Abstract
Eastern Cooperative Oncology Group ECOG) is an NCI‐funded cooperative group that conducts clinical trials in oncology. Over many years, ECOG has developed efficient systems for conducting high‐quality clinical trials with limited funding. Because ECOG runs many studies in the same network of institutions, a key factor is that quality control procedures focus on the performance of the sites across studies rather than on the individual study. ECOG has also achieved efficiencies through standardization of data elements and evaluation criteria and through use of a single data monitoring committee for the Group's entire portfolio of Phase III trials, while ensuring patient safety through an aggressive program of adverse‐event monitoring. These procedures have enabled ECOG to make major contributions advancing the treatment of cancer patients within the funding constraints of the NCI's Cooperative Group program.
Institutional and Independent Review Boards
Authors: Fish Susan S. 
Published: June 2008

Abstract
Institutional Review Boards (IRBs), or Independent Ethics Committees (IECs) as they are known around the world, are a cornerstone of the system of protections human research subjects. An IRB is a committee that functions as a regulatory and ethics review board for research that involves human subjects. In countries that regulate research in humans, IRBs/IECs are required to approve research studies prior to performing any research intervention, which includes screening, on any subject. In countries without research regulations, IRBs/IECs may also review research. This article focuses mainly on IRBs that are regulated by U.S. agencies.
Central Nervous System (CNS)
Authors: Sommer David B. , Goldstein Larry B. 
Published: June 2008

AbstractModern clinical trials have revolutionized the practice of neurology. This introduction examines some of the issues and challenges involved in therapeutic trials for six common conditions that affect the central nervous system (ischemic stroke, Alzheimer's disease, migraine headache, epilepsy, Parkinson's disease, and multiple sclerosis) and explores how trials in these areas influence clinical practice. Examples of ongoing trials in each of these areas are also identified.
Proportional Odds Model
Authors: Liu Ivy , Mukherjee Bhramar 
Published: June 2008

AbstractOutcomes recorded on an ordinal scale, such as severity of migraine, stages of progression of disease, or degree of relief caused by treatment, occur commonly in clinical trials. Questionnaire data, which are often collected at each visit to gauge patient condition, routinely contain responses on an ordinal scale. Naïve dichotomization of the full ordinal scale leads to loss of information and efficiency while analyzing such outcomes. The proportional odds model is a popular choice for analyzing such ordinal outcomes. The current article provides a concise introduction to the proportional odds model and proceeds to review some more recent work related to this model. Specifically, we discuss the problem of analyzing stratified ordinal data in which observations from the same strata are correlated. Such correlated ordinal data may develop in multicenter clinical trials or with ordinal responses measured repeatedly on the same subject in longitudinal studies. Certain computing tools for fitting such models are discussed.
Open‐Labeled Trial
Authors: Day Simon 
Published: June 2008

Abstract
This article discusses open‐labeled studies; that is, studies that are not blinded. It is usually assumed that lack of blinding is “total,” not just single‐blinded (either patient‐ or investigator‐blinded). Different levels and aspects of blinding can often be achieved so that trials may be only partially open label. In some cases, open‐label trials might be practically more acceptable, and in some studies, they may even be preferred to blinded studies.
Coronary Drug Project
Authors: Canner Paul L. 
Published: June 2008

Abstract

The Coronary Drug Project, which was conducted during 1966 to 1974, was a randomized, double‐blind, placebo‐controlled trial of five lipid‐modifying agents—estrogens at two dosage levels, dextrothyroxine, clofibrate, and niacin—in 8341 men with previous myocardial infarction. The primary efficacy outcome was all‐cause mortality for the entire follow‐up period. The first three named regimens were terminated early because of adverse effects. Only niacin significantly reduced the risk of (
1
) cardiovascular events during a mean follow‐up of 6.2 years and (
2
) all‐cause mortality during 6.2 years with study treatment plus an additional 9 years of post‐trial follow‐up. Analyses of treatment–placebo differences with respect to all‐cause mortality, subdivided by level of adherence to the study prescription and by amount of change in serum cholesterol level, could not be properly interpreted because reasons for good/poor adherence and for cholesterol changes in the placebo group were not well defined.
National Cooperative Gallstone Study
Authors: Lachin John M. 
Published: June 2008

AbstractThe National Cooperative Gallstone Study (NCGS), funded by the National Institute of Arthritis, Metabolism and Digestive Diseases of the National Institutes of Health, evaluated dietary supplementation with a natural bile acid (chenodiol) for the dissolution of cholesterol gallstones. Since the compound occurred naturally, there was no industrial sponsor. Thus, the study group also conducted preliminary studies of animal toxicology and hepatic morphology, among others, in addition to a randomized, double‐masked, long‐term, multiple‐dose, Phase III clinical trial. The study employed central units for the evaluation of all outcomes with rigorous quality assurance procedures. The study results, study issues, and statistical considerations are described.
Prostate Cancer Prevention Trial
Authors: Weizer Alon Z. , Hussain Maha H. 
Published: June 2008

Abstract
Prostate cancer is the most common malignancy diagnosed and the second most common cause of cancer death in American men. Although effective treatment strategies exist, the prolonged natural history of the disease makes prevention attractive. Androgens are involved in the development and progression of prostate cancer. Finasteride (a 5‐alpha‐reductase inhibitor) prevents the conversion of testosterone to dihydrotestosterone within the prostate decreasing prostate growth. The Prostate Cancer Prevention Trial randomized 18,882 men 55 years or older to finasteride versus placebo in order to assess the medication's ability to decrease the prevalence of prostate cancer over a seven‐year period. Finasteride resulted in a 24.8% reduction in the prevalence of prostate cancer; however, men diagnosed with prostate cancer in the treatment arm were found to have higher grade prostate cancer. Secondary data analyses have sought explanations for this finding as well as provided additional insight into the use of prostate‐specific antigen in clinical practice.
On the impact of uncorrelated variation in regression mathematics
Authors: Gottfries Johan , Johansson Erik , Trygg Johan 
Published: July 2008

AbstractThe objective of the present study is to investigate if, and if so, how uncorrelated variation relates to regression mathematics as exemplified by partial least squares (PLS) methodology. In contrast to previous methods, orthogonal partial least squares (OPLS) method requires a multi‐focus, in the sense that in parallel to calculation of correlation it requires an analysis of orthogonal variation, i.e. the uncorrelated structure in a comprehensive way. Subsequent to the estimation of the correlation is the remaining orthogonal variation, i.e. uncorrelated data, divided into uncorrelated structure and stochastic noise by the ‘OPLS component’. Thus, it appears obvious that it is of interest to understand how the uncorrelated variation can influence the interpretation of the regression model. We have scrutinized three examples that pinpoint additional value from OPLS regarding the modelling of the orthogonal, i.e. uncorrelated, variation in regression mathematics. In agreement with the results, we conclude that uncorrelated variations do impact interpretations of regression analyses output and provides not only opportunities by OPLS but also an obligation for the user to maximize benefit from OPLS. Copyright © 2008 John Wiley & Sons, Ltd.
Variational‐based finite element method for inverse shape design of heat conduction
Authors: Wu Zhao‐Chun 
Published: June 2008

AbstractAn inverse shape design of heat conduction is considered for optimizing the geometrical shape from prescribed temperature distribution and heat flux distribution on the unknown surface. A variational theory is established by the semi‐inverse method suggested by Ji‐Huan He for the problem discussed; we make the obtained variational principle stationary with moving boundaries until the natural boundary conditions on the unknown shape meet the prescribed condition on the unknown boundary, making the problem well‐posed and easy to incorporate with the finite element simulation. Numerical results show that the present technique is robust and convenient. Copyright © 2008 John Wiley & Sons, Ltd.