bluuebunny/crossref_metadata_2025_split huggingface dataset:
Response Adaptive Randomization
Authors: Coad D.Stephen 
Published: October 2008

AbstractWhen two or more treatments are being compared in a clinical trial, information accrues on the treatments as the trial proceeds. However, there may be evidence suggesting that some treatments are more promising than others, and consequently, there may be interest in applying response adaptive randomization, which uses the current data to assign more patients to the treatments that are performing better thus far in the trial. In this way, patients have a higher probability of being assigned to these treatments. Examples of this type of randomization are given, such as urn models and sequential maximum likelihood estimation rules, and some of their properties are described. The issue of inference after trials that use response adaptive randomization is then discussed. For example, this approach can lead to a loss in power when using standard tests and the problem of estimation can be considerably more complicated than in a trial that uses complete randomization. The use of stopping rules is also addressed, since, in practice, there may be interest in stopping a trial early if there is convincing evidence of a treatment difference or less promising treatments may be dropped from additional consideration. An indication is given of possible future work.
CFR
21 Part 11
Authors: Owings Michael P. , Bleicher Paul A. 
Published: October 2008

Abstract

21CFR11: ELECTRONIC RECORDS; ELECTRONIC SIGNATURES, commonly referred to as “Part 11” was enacted in 1997 to provide criteria under which the FDA will consider electronic records to be equivalent to paper records, and electronic signatures equivalent to traditional handwritten signatures. Part 11 applies to
persons
who, in fulfillment of a requirement in a statute or regulation, have chosen to maintain records or submit designated information electronically to the FDA, and to
records
in electronic form that are created, modified, maintained, archived, retrieved, or transmitted under any records requirements set forth in Agency regulations.
Metadata
Authors: Christiansen David H. 
Published: October 2008

Abstract
Clinical trial metadata, or “data about data” define the characteristics of data and documents related to clinical trials. The most common metadata are attributes of clinical trial datasets submitted in support of a regulatory application for a new medical treatment. Clinical trial reports, regulatory submissions, and statistical analyses can also profit from metadata that clearly describe the content, structure, and use of these documents. Several organizations, including the U.S. Food and Drug Administration, are actively engaged in developing standard metadata for clinical trials. The increasing use of electronic regulatory submissions has heightened the interest in computerized or machine‐readable metadata. Standardized, predictable metadata in a computerized form provide the framework for the development of tools to assist in the creation and review of clinical trial reports and regulatory submissions. Furthermore, standardized metadata will provide the basis for development of review and analysis tools that can be used by both industry and regulators to expedite the timely and accurate evaluation of new medical treatments.
Subgroup
Authors: Wittes Janet 
Published: October 2008

AbstractRandomized clinical trials are usually designed to show an effect of treatment in the study population at large. Trials rarely have sufficient statistical power to measure reliably the effect of a treatment within a subgroup of that population. They are even less likely to provide reliable information on whether the effect of a treatment differs from subgroup to subgroup. This article defines various terms related to analysis of subgroups. It distinguishes between subgroups defined on the basis of baseline variables from “improper” subgroups defined on the basis of variables measured after randomization. It also discusses hypotheses defined a priori and those identified after the results have emerged. It emphasizes that random variation arising from small sample sizes can lead to unrealistically large or small observed effects and warns investigators to interpret findings from subgroups with caution.
Regression Models to Incorporate Patient Heterogeneity
Authors: O'Quigley John 
Published: October 2008

Abstract
Although we anticipate heterogeneity among patients included in a dose finding study, given the typically small number of patients available, it is common to group all the patients under a single heading. However, careful modeling can still enable us to make gains when dealing with clearly defined subgroups. Rather than carry out separate independent studies, it is possible via the use of simple regression models to include all patients under one heading while still allowing for the possibility that the groups behave differently. Different schedules of treatment may also lead to different behaviors and, under a working assumption that the groups behave similarly, it is important to have a mechanism that will indicate to us that the accumulating evidence suggests the groups are behaving differently. Regression models can enable us to do this. Certain studies involve more than a single grouping covariable, an example is the two prognostic groups based on heavily and lightly pretreated patients, together with a variable that labels the scheduling. For three different schedules and two prognostic groups, we have a total of six subgroups. Separate analyses are not feasible, and a regression model can be of great use in such situations.
UGDPTrial
Authors: Meinert Curtis 
Published: October 2008

AbstractThe UGDP (University Group Diabetes Program) was a multicenter, randomized, placebo‐controlled trials aimed at assessing the efficacy of antidiabetic treatments in delaying or preventing the long‐term complications of adult‐onset diabetes (type‐2 diabetes). The trial was in the carly vanguard of trials aimed at assessing efficacy of approved treatments for chronic conditions—phase IV trials in the vernacular of trials. The trial involved two oral agents, tolbutamide and phenformin, and matching placebos and two insulin‐assigned treatment groups (insulin dosage as determined by body surface and insulin dosage as needed to “normalized” blood glucose levels). The trial generated a firestorm of controversy in 1970 with presentation and publication of results suggesting that a widely used oral agent—tolbutamide (Orinase, Upjohn, Kalamazoo now part of Pfizer)—was of no value in reducing the risk of morbiarty or in prolonging life. The FDA used its results to revise the label for the drug to include a special warning concerning the possibility cardiovascular risks associated with the drug, but only after a prolonged battle that raged on for more than a decade—a battle that ultimately ended up in front of the U.S. Supreme Court.
Conditional Power in Clinical Trial Monitoring
Authors: Tan Ming T. 
Published: October 2008

Abstract
For ethical, economical, and scientific reasons, clinical trials may be terminated early for treatment efficacy or the lack thereof. In addition to group sequential tests and type I error‐spending functions, another approach is to ask more directly whether the accumulated evidence is sufficiently convincing for efficacy. Or, if evidence is lacking, one would ask whether the trial should continue to the planned end and whether the conventional fixed sample (nonsequential) test should be employed. Conditional power is one way to quantify this evidence. It is the power of the conventional nonsequential test conditional on interim data. This article introduces the versatile conditional power and related stochastic curtailment approaches in the monitoring of clinical trials.
Phase I Trials
Authors: Chevret Sylvie 
Published: October 2008

Abstract
Phase I trials, which are also called first‐into‐human studies, try to determine dosing, to document how a drug is metabolized and excreted, and to identify acute side effects. Usually, a small number of healthy volunteers (between 20 and 40) is used. They evaluate how well a new drug is tolerated, with the principal observations of interest being the pharmacokinetic and pharmacodynamic endpoints. Designs are often fixed, in which several dose levels and a placebo are randomly given, possibly in different periods, although some ascension is often conducted over the periods. At the other end of the severity spectrum, oncology Phase I trials are conducted in patients to determine the highest dosage that can be given safely, which is usually called the maximum tolerated dose (MTD). The designs are sequential and adaptive in some sense, because each patient is administered a dose level on the light of previous doses, and outcomes are observed in the trial. Two main adaptive designs are used, with dose allocation either algorithm‐ or model‐guided. They differ in terms of underlying interpretation of the MTD. The aim of this article is to summarize the most usual Phase I designs and analyses conducted in healthy volunteers and in oncology patients, separately. Differences between these approaches are stressed out, with some practical recommendations.
Therapeutic Dose Range
Authors: Sylvie Chevret 
Published: October 2008

Abstract
After preclinical assessments, the therapeutic dose range emphasizes the importance of the margin of safety that exists between the dose required for the desired effects of the drug and the dose that produces unwanted—potentially dangerous—side effects in determining the usefulness of a drug. The narrower the margin, the more likely it is that the drug will produce unwanted effects. This therapeutic index relies of the assessment of dose–response relationship. Traditional drug development consists of a sequence of independent trials organized in different phases. However, when establishing dose–response relationships and potential therapeutic dose range, over‐reliance on premarketing clinical trials has been pointed out. Assessment of dose–response relationships should occupy a prominent role in drug development with clinical studies designed to assess dose response as an inherent part of establishing the safety and effectiveness of the drug. This research relies on phase I studies in healthy volunteers with collected data on safety, tolerability, and effectiveness, as well as pharmacokinetics and pharmacodynamics. By contrast, drug development in life‐threatening diseases specifically uses the maximum tolerated dose as the only dose of interest. In all cases, note that the therapeutic dose range is based on small sample studies; thus, it makes it difficult or even impossible to individualize treatment based on patients' specific characteristics such as age, size, state of health, or use of concomitant medications. This discrepancy deserves additional attention.
Intrarater Reliability
Authors: Gwet Kilem L. 
Published: October 2008

Abstract
Intrarater reliability refers to the ability of a rater or a measurement system to reproduce quantitative or qualitative outcomes under the same experimental conditions. In this article, we review two statistical measures often used in the literature for quantifying intrarater reliability. The first measure is the intraclass correlation coefficient (ICC), which is the preferred measure for continuous data. The second measure is the kappa coefficient and its many kappa‐like variants recommended for nominal data. Also included in this article are guidelines for optimizing the number of subjects and number of replicates per subject when designing an intrarater reliability study for quantitative measurements. We also explore important extensions of the kappa coefficient to ordinal and interval data, which may also be used to analyze multivariate ratings obtained by rating subjects on multiple characteristics. For the intraclass correlation coefficient and kappa‐like statistics, we discuss a framework for statistical inference within which to evaluate the precision of estimations.
The FDA and Regulatory Issues
Authors: Rzeszotarski W. Janusz 
Published: October 2008

Abstract
A brief outline of information that is available on the Web pertinent to the FDA and regulatory issues. The process of new drug approval and its continuous modification reflects both the progress of science and the globalization of the world's economy. The reader is encouraged to follow the changes by constant monitoring of the FDA and the industry sites dedicated to these issues. The history of drug regulation in the United States, the evolving structure of the FDA, the steps to be taken in the process of obtaining the approval to market the new molecular entity, and the post‐approval requirements are briefly described.
Censored Data
Authors: Andersen Per Kragh 
Published: October 2008

AbstractThe concepts of independent right censoring and noninformative right censoring in survival analysis are defined. Dependent censoring is a kind of selection bias and adds to biased inference for the survival time distribution. Informative censoring typically leads to inefficient inference. Examples are presented and relations between right censoring and competing risks are discussed. Other kinds of censoring, including interval censoring are touched upon.
Kappa
Authors: Cook Richard J. 
Published: October 2008

Abstract
The kappa statistic is a widely used measure for quantifying agreement between two methods of classification into nominal categories. Part of the appeal of the kappa statistic is that it is a “chance‐corrected” measure, which reflects agreement beyond the level expected by chance based on the marginal frequencies. Generalizations to weighted kappa statistics are appealing for the analysis of ordinal data. Generalizations of the original kappa statistic facilitate agreement analyses between three or more raters.
Nonparametric Methods
Authors: Wolfe Douglas A. 
Published: October 2008

AbstractThe motivation behind distribution‐free hypothesis tests and confidence intervals based on signs and ranks is discussed and standard text references are provided. Distribution‐free test and confidence interval procedures for the one‐sample, two‐sample, one‐way analysis of variance, two‐way analysis of variance, and independence settings are presented. Point estimation techniques, including Hodges–Lehmann estimators and contrast estimation, and multiple comparisons procedures are described. Basic references for censored data approaches and bootstrapping are provided.
P

Value
Authors: Goodman Steven N. 
Published: October 2008

Abstract

The
P
value is the probability, under a given simple hypothesis, of the observed or a more extreme value of a test statistic. Problems discussed include that of the choice of test statistic, the relevance of alternative hypotheses, ambiguity about the sample space, and the interpretation generally. The distinction between one‐sided and two‐sided tests is a source of confusion. Bayesian considerations are discussed.
Survival Analysis, Overview
Authors: Andersen Per Kragh , Keiding Niels 
Published: October 2008

AbstractSurvival analysis is the generic name for analysis of time‐to‐event data. The distinguishing feature of such data is the presence of right‐censored observations. Thus, for some subjects, instead of observing the real time to the event, only a lower limit for this time, the right‐censoring time, is known. This kind of incomplete data calls for special statistical techniques for the analysis. This article reviews such methods with cross‐references to other articles dealing with special techniques.
Benefit/Risk Assessment in Prevention Trials
Authors: Costantino Joseph P. 
Published: October 2008

AbstractBenefit/risk assessment (B/RA) is a mathematical procedure to estimate the probability of detrimental outcomes, beneficial outcomes and the net‐effect anticipated from exposure to a given agent or procedure. B/RAs of health‐related outcomes are used for public health planning, decision‐making regarding health care financing, and therapeutic decision‐making in clinical practice. Information obtained from B/RAs based on findings from controlled clinical trials, particularly those with double‐masking of treatment, are most informative for health care planning and decision making because such information is less likely to be bias than is information obtained from observational studies. Thus, B/RAs in prevention trials are an excellent source of information to use as the basis for health care planning and decision‐making. Applications of R/BA in prevention trials are performed as supplements for planning, monitoring and analyzing the trial. These applications can be categorized into three types of assessments. This article provides a description of the three types of assessment performed in prevention trials, defines the statistical algorithms used for each type of assessment and discusses several key methodological and practical issues involve with the application of B/RA to health‐related outcomes.
Compliance and Survival Analysis
Authors: Goetghebeur Els 
Published: October 2008

Abstract
Partial compliance with assigned treatment can act as both cause and effect of survival experiences in randomized clinical trials. Structural failure time models have been developed for causal inference on the effect of resulting exposure patterns on survival time. In this setting, we review randomization based estimation methods that protect the standard α level. We also point to alternative methods relying on the assumption of no unmeasured time‐dependent confounders.
Pharmacoepidemiology, Overview
Authors: Suissa S. 
Published: October 2008

AbstractPharmacoepidemiology is the study of patterns of medication use in the populations and their effects on diseases. Particular interest is focused on unexpected risks, especially events such as rare side effects. These can typically not be adequately assessed in the context of randomized clinical trials. This entry describes the use of Pharmacoepidemiology through the case‐crossover design, dealing with confounding in observational studies, the specification of appropriate risk functions over time, the probabilistic assessment of causality, and study methods based on the use of prescription data.
Genetic origins and clinical phenotype of familial and acquired erythrocytosis and thrombocytosis
Authors: Percy Melanie J. , Rumi Elisa 
Published: October 2008

AbstractFamilial and acquired erythrocytosis and thrombocytosis are characterized by myeloid lineage hyperproliferation, which is either single or multi‐lineage in origin. The single lineage disorders exhibit Mendelian inheritance with polyclonal hematopoiesis and often arise from a single genetic defect. In contrast, the multi‐lineage disorders exhibit complex patterns of inheritance with multi‐genetic origins and clonal hematopoiesis. They have the potential to acquire JAK2 somatic mutations, but this is not the primary event. Identification of the disease‐causing genes will enable better classification of familial and acquired erythrocytosis and thrombocytosis. Furthermore, it will provide an insight into the mechanisms regulating myeloid cell proliferation. Am. J. Hematol., 2009. © 2008 Wiley‐Liss, Inc.
Tetra‐amelia and lung hypo/aplasia syndrome: New case report and review
Authors: Sousa Sérgio B. , Pina Raquel , Ramos Lina , Pereira Naigel , Krahn Martin , Borozdin Wiktor , Kohlhase Jürgen , Amorim Marta , Gonnet Katia , Lévy Nicolas , Carreira Isabel M. , Couceiro Ana Bela , Saraiva Jorge M. 
Published: October 2008

AbstractTetra‐amelia is a rare malformation that may be associated with other anomalies and is usually inherited in an autosomal recessive pattern. We describe a fetus, born to a nonconsanguineous couple, with tetra‐amelia, bilateral cleft lip and palate and bilateral lung agenesis, without other anomalies. Karyotype was normal (46,XX) and premature centromere separation was excluded. No mutation was identified upon molecular analysis of WNT3, HS6ST1, and HS6ST3. We reviewed the literature and the differential diagnosis to clarify the clinical delineation of conditions associated with tetra‐amelia. The present report describes the sixth family with this pattern of malformations and reinforces the evidence that the “tetra‐amelia and lung hypo/aplasia syndrome” is a distinct autosomal recessive condition, with no identified gene thus far. © 2008 Wiley‐Liss, Inc.
Testing the function of reconciliation and third‐party affiliation for aggressors in hamadryas baboons (Papio hamadryas hamadryas)
Authors: Romero Teresa , Colmenares Fernando , Aureli Filippo 
Published: October 2008

AbstractIn social groups, agonistic conflicts can have different negative consequences. Several post‐conflict interactions have been suggested as post‐conflict management behaviors to mitigate those negative effects. In this study, we investigated the function of two post‐conflict behaviors—reconciliation and aggressor‐initiated third‐party affiliation—on the aggressor's levels of post‐conflict anxiety and aggression in a large colony of hamadryas baboons. We also examined variation in the aggressor's levels of post‐conflict anxiety as a function of relationship quality between the opponents as predicted by the Integrated Hypothesis. We found that after conflicts hamadryas baboon aggressors showed increased rates of anxiety‐related behaviors and that they were also more likely to be involved in renewed aggressive interactions. Although both reconciliation and aggressor‐initiated third‐party affiliation reduced the probability of receiving post‐conflict aggression, only reconciliation reduced the rates of anxiety‐related behaviors, suggesting that the aggressors' post‐conflict anxiety might be owing mainly to the damage that the conflict causes to their relationship with the victim. Furthermore, aggressor's rates of post‐conflict anxiety were higher after conflicts with individuals with whom they had a high‐quality relationship, supporting the idea that levels of post‐conflict anxiety mediate the occurrence of reconciliation depending on the quality of the relationship with former opponent as predicted by the Integrated Hypothesis. Am. J. Primatol. 71:60–69, 2009. © 2008 Wiley‐Liss, Inc.
Opsin gene polymorphism predicts trichromacy in a cathemeral lemur
Authors: Veilleux Carrie C. , Bolnick Deborah A. 
Published: October 2008

AbstractRecent research has identified polymorphic trichromacy in three diurnal strepsirrhines: Coquerel's sifaka (Propithecus coquereli), black and white ruffed lemurs (Varecia variegata), and red ruffed lemurs (V. rubra). Current hypotheses suggest that the transitions to diurnality experienced by Propithecus and Varecia were necessary precursors to their independent acquisitions of trichromacy. Accordingly, cathemeral lemurs are thought to lack the M/L opsin gene polymorphism necessary for trichromacy. In this study, the M/L opsin gene was sequenced in ten cathemeral blue‐eyed black lemurs (Eulemur macaco flavifrons). This analysis identified a polymorphism identical to that of other trichromatic strepsirrhines at the critical amino acid position 285 in exon 5 of the M/L opsin gene. Thus, polymorphic trichromacy is likely present in at least one cathemeral Eulemur species, suggesting that strict diurnality is not necessary for trichromacy. The presence of trichromacy in E. m. flavifrons suggests that a re‐evaluation of current hypotheses regarding the evolution of strepsirrhine trichromacy may be necessary. Although the M/L opsin polymorphism may have been independently acquired three times in the lemurid–indriid clade, the distribution of opsin alleles in lemurids and indriids may also be consistent with a common origin of trichromacy in the last common ancestor of either the lemurids or the lemurid–indriid clade. Am. J. Primatol. 71:86–90, 2009. © 2008 Wiley‐Liss, Inc.