Biostatistical Methodology Research Articles

Clinical Trial Data Analysis UsingR

Clinical Trial Data Analysis Using R is the latest member in the family of “Using R” books from CRC biostatistics series. The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully, and does a nice job covering most, if not all major aspects of clinical trial statistics. For those who are well versed in R, this book can serve as a good reference to the established clinical biostatistics methodology; for veteran biostatisticians, this book provides a gentle introduction to the use of R in clinical trial analysis.

Proceedings of the University of Pennsylvania Annual Conference on Statistical Issues in Clinical Trials: Early, translational and proof of concept studies: The ‘Go/No Go’ Decisions

Proceedings of the University of Pennsylvania Annual Conference on Statistical Issues in Clinical Trials: Early, translational and proof of concept studies: The ‘Go/No Go’ Decisions

Dr. Andrei Yakovlev: Visionary, Leader, Iconoclast

Dr. Andrei Yakovlev: Visionary, Leader, Iconoclast

European Federation of Statisticians in the Pharmaceutical Industry

The Quality Assurance JournalVolume 7, Issue 2 p. 130-132 ProfileFree Access European Federation of Statisticians in the Pharmaceutical Industry David Morgan, David Morgan President EFSPI, Resources for Business Ltd., South Park Road, Macclesfield SK11 6SH, UKSearch for more papers by this authorLesley Smith, Corresponding Author Lesley Smith EFSPI, Executive Secretary efspi@resources.demon.co.uk EFSPI, Resources for Business Ltd., South Park Road, Macclesfield SK11 6SH, UKResources for Business Ltd., South Park Road, Macclesfield SK11 6SH, UKSearch for more papers by this author David Morgan, David Morgan President EFSPI, Resources for Business Ltd., South Park Road, Macclesfield SK11 6SH, UKSearch for more papers by this authorLesley Smith, Corresponding Author Lesley Smith EFSPI, Executive Secretary efspi@resources.demon.co.uk EFSPI, Resources for Business Ltd., South Park Road, Macclesfield SK11 6SH, UKResources for Business Ltd., South Park Road, Macclesfield SK11 6SH, UKSearch for more papers by this author First published: 29 April 2003 https://doi.org/10.1002/qaj.219AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. REFERENCES 1 CPMP Working Party on Efficacy of Medicinal Products. Biostatistical Methodology in Clinical Trials in Applications for Marketing Authorisations for Medicinal Products. European Commission, Brussels, 1994. 2 EFSPI Working Group. Qualified statisticians in the Euro-pean pharmaceutical industry. Drug Inform. J 1999; 33: 407– 415. 3 Huitfeldt B, Danielson L, Ebbutt A, Schmidt, K. Choice of control groups in clinical trials. Drug Inform J 2001; 35: 1147– 1156. Volume7, Issue2June 2003Pages 130-132 ReferencesRelatedInformation

Genes or environment? The difficulties of disentangling these effects in human genetic data analysis

Biostatistical methodology to accommodate genotype by environment (G-E) interactions in planned breeding trials for animals and for plants (such as crop variety trials) is well-advanced. Incorporation of environmental effects into genetic models for human data is generally more problematic. For continuous traits, such as height, IQ, blood pressure and cholesterol level measurements (to name a few), there is a vast literature on approaches that can be traced back over 80 years. However, many of the more modern approaches to realistic biostatistical modelling have not penetrated recent analyses of such data. For complex traits, like autoimmune diseases, cancer, cardiovascular disorders, obesity, psychiatric disorders, for example, recent emphasis has been on mapping supposed susceptibility (genetic) loci. Massive enterprises have been undertaken, but the outcomes have been mixed, and usually only applicable for subforms of the disease under study. Nevertheless, there is currently great enthusiasm for undertaking linkage studies for these diseases. Here a brief overview of some of the difficulties in realistically disentangling environmental and genetic effects in models for human genetic data is given.

European Regulatory Authorities and Pediatric Labeling

### The Need for Medicinal Product Testing in Children #### Ethical Considerations Children should not be given medicines that have not been evaluated adequately for use in that age group. There is a responsibility, shared by applicants and the appropriate authorities, to ensure that children have timely access to safe and effective medicines that have accurate, scientifically justified prescribing information. Applicants are encouraged to investigate the safety and efficacy of a product in children, if it is likely to be of therapeutic benefit in this age-group, and to develop suitable formulation, even if use is likely to be small. However important a clinical trial may be to prove or disprove the value of a treatment, individual members of one or both of the groups—subject or control—can suffer injury as a result of inclusion in the trial, even if the whole community benefits. As with adults who participate in clinical trials and who understand the issues involved in giving their informed consent, consent should be obtained from the legal guardian of children in accordance with national legislation. Children should be fully informed about the trial in language and terms they understand and, if able, should personally sign and date the written informed consent. The child should be made aware of his/her rights to decline to participate. The child's wish to be withdrawn from a study must be respected. These measures should be applied in conjunction with 1) part 4 of Directive 75/318/EEC, as amended, which requires “… details concerning patients who may be at increased risk”; the CPMP/ICH guideline for good clinical practice; and 3) the CPMP guideline on biostatistical methodology in clinical trials in applications for marketing authorizations for medicinal products. These measures are intended to assist applicants with specific problems presented by medicinal product testing in children. The child should stand to obtain some direct benefit from the clinical trial, except … Address correspondence to Elisabeth Autret, MD, Hopital Bretonneau, Pharmacologie Clinique, Boulevard Tonnele, 37044 Tours, France.

Interrater Reliability Levels of Multiple Clinical Examiners in the Evaluation of a Schizophrenic Patient: Quality of Life, Level of Functioning, and Neuropsychological Symptomatology

Sir Ronald Fisher used a single-subject design to derive the concepts of appropriate research design, randomization, sensitivity, and tests of statistical significance. The seminal work of Broca demonstrated that valid and generalizable findings can and have emerged from studies of a single patient in neuropsychology. In order to assess the reliability and/or validity of any clinical phenomena that derive from single subject research, it becomes necessary to apply appropriate biostatistical methodology. The authors develop just such an approach and apply it successfully to the evaluation of the functioning, quality of life, and neuropsychological symptomatology of a single schizophrenic patient.

Statistics and Statisticians in European Drug Regulatory Agencies

The importance of adequate provision for expert statistical review of license applications by European regulatory agencies has been increased by several developments including moves toward international harmonization. A brief questionnaire on the roles of statisticians and statistical review procedures was sent to the director of the national drug regulatory agency in each of 18 European countries (current and prospective members of the European Union [EU] and other related countries). The topics covered included: 1. The number of statisticians employed by the authority or used as advisers, and the extent of this use, 2. Which license applications are statistically reviewed, how these are selected, and which parts of applications are considered, and 3. The potential impact of the setting up of the European Medicines Evaluation Agency and adoption of the EU Note for Guidance on Biostatistical Methodology in Clinical Trials.

Influence of HLA and CREG matching in African-American primary cadaver kidney recipients: UNOS 1991–1995

There have been only limited investigations on the influence of HLA match on organ transplant outcome in African-Americans.1,2 To obtain this information, a multivariate analysis was performed of 31,291 cases of primary cadaver kidney transplantation reported to the UNOS Scientific Registry between 1991 and 1995.3 The collection included 8111 African-Americans, for whom follow-up was to January 1, 1997. The study involved a triple university collaboration involving experts in clinical transplantation, histocompatibility, and biostatistical methodology.

Biostatistical methodology in clinical trials--a European guideline.

Biostatistical methodology in clinical trials--a European guideline.

The case for cross-over trials in phase III.

There is a common belief that cross-over trials should not be used in phase III of drug development. This was reinforced by a statement in the draft CPMP Note for Guidance on biostatistical methodology in clinical trials which was circulated for review in March 1993: 'Hence crossover trials in patients should be avoided as far as possible'. We do not share this belief. Historically, many successful drug developments in indications such as hypertension and asthma have depended heavily on cross-over trials in their phase III programmes, leading to regulatory approval for a number of well established medicines. The evidence on which these developments were based appeared sound at the time, and has not been questioned by later experiences with these medicines. Furthermore, the general level of understanding of these medical indications is now even more well developed, and hence the circumstances under which cross-over trials may be used to advantage for new drugs in phase III are even more likely to be correctly identified. There are some well-known disadvantages of cross-over trials relative to parallel group trials. These are reviewed and the ways in which early indications of such problems might be detected in phases I and II or elsewhere will be discussed. However, there are also two key advantages, the well-known one of study size and a less well-known one arising in the context of treatment-by-patient interaction. In phases I and II these advantages lead routinely to the use of the cross-over design. Some methods of analysing cross-over trials have been criticized in a number of recent articles. We compare the properties of a number of alternative analysis strategies by means of simulation and conclude that these concerns about methods of analysis do not imply that cross-over trials should be avoided, especially if baseline measurements can be included in the design. Any small risks attached to their use should not normally concern the regulator as they will tend to diminish estimates of treatment effects rather than enhance them. In summary, cross-over trials remain a potentially valuable research tool in the development of new medicines at all stages including phase III. It is unnecessary and counterproductive to exclude them from use.

Guest Editor's Note: A European Concept for Good Statistical Practices in Global Drug Development

GUEST EDITOR’S NOTE: A EUROPEAN CONCEPT FOR GOOD STATISTICAL PRACTICES IN GLOBAL DRUG DEVELOPMENT ANDREAS ZIPFEL Section Biometric & Data Management, Department des Enregistrements et de L’Information Scientifique, Synthelabo Recherche, Bagneux Cedex, France, and Program Co-chairperson THIS NOTE INTRODUCES discussion papers from the DIA Workshop “European Concept for Good Statistical Practice in Global Drug Development,” April 27-28, 1994, Edinburgh, Scotland, United Kingdom. Since its release, the draft version of the “Note for Guidance on Biostatistical Methodology

Statistical issues in the regulation of medicines

The recent release within the European Union of a draft Note for Guidance from the Commission for Proprietary Medical Products (CPMP) entitled 'Biostatistical methodology in clinical trials in applications for marketing authorisations for medicinal products' has stimulated widespread discussion of the relevant statistical issues. This discussion contains echoes of an earlier debate concerning a closely related U.S. Guideline. The areas of agreement and disagreement between the two guidelines bear close examination as they provide lessons for all statisticians involved in the design and analysis of clinical trials. Notable areas of debate include crossover designs, multi-centre trials, the intention to treat principle, pre-specification of statistical analysis and the ability to generalize results to the wider population of patients. The consequences for the routine involvement of statisticians in this area of work in general, and in the regulatory process in particular, are especially important. This is an illustration of the extent to which drug regulation has influenced, and is continuing to influence, the development of medical statistics throughout the world.

A model for the development, conduct, and monitoring of multicenter clinical trials in the veterans administration

In the past 20–30 years, increased interest on the part of biostatisticians and medical investigators has been exhibited in clinical trial research. In the mid-1940's, the Veterans Administration Hospital system was recognized as an ideal environment for the conduct of multicenter clinical trials, with the initiation of a study to determine the effectiveness of chemotherapy in the treatment of tuberculosis, in a joint effort with the United States Armed Forces. This research effort later evolved into what is presently known as the Cooperative Studies Program of the Medical Research Service. Within the past seven years, this program has undergone considerable growth and reorganization. This paper describes a system for the review, operation, and conduct of multicenter clinical research in a wide variety of medical specialty areas. In particular, it stresses the importance of core biostatistical coordinating centers where biostatisticians and other key support personnel constitute an integral part of the planning and development, implementation, conduct, and reporting of many cooperative studies in diverse disciplines. The paper also describes the interaction of various review bodies and a check and balance system to promote sound management and opportunity for the exchange of clinical and biostatistical methodology in the cooperative study setting.