Study design and methods

For human pharmacokinetic studies, infonnation on study design and methods used along with the pharmacokinetic data... 

Evaluation of appropriateness requires a detailed description of the conditions, study designs and methods under which data were collected or information was developed, so that the exposure assessor or other users of the data can judge their relevance for their purposes. An exposure assessor must further document any additional assumptions and simplifications made when using the data in a particular assessment. The determination of appropriateness therefore requires the application of one of the other hallmarks of data quality discussed below, transparency (see section 3.4). 

More details about when such studies may or may not be important, and other aspects as study design and methods, can be found in CPMP/EWP/23339/02 2004 and Guidance for Industry 2003. 

Feldman HI, Appel LJ, Chertow GM, et al. The Chronic Renal Insufficiency Cohort (CRIC) Study Design and Methods. J Am Soc Nephrol 2003 14(7 Suppl 2) S 148-153. 

Descriptions of the study design and methods (e.g. sample recruitment, attrition and characteristics, data collection, and analytical methods) are available elsewhere (Bellinger et al, 1984 Rabinowitz et al, 1985 Needleman et al, 1981). Briefly, infants were recruited on the basis of umbilical cord... 

Accurate, precise and sensitive analytical methods are important to the collection of data needed for regulatory decisions about pesticide registration. This article describes the various components of analytical method development, validation and implementation that affect the collection of pesticide residue distribution data for regulatory assessment of environmental fate and water quality impacts. Included in this discussion are both the technical needs of analytical methods and the attributes of study design and sample collection needed to develop data that are useful for regulatory purposes. 

The industry task forces (ARTF, ORETF, and others) are generating model protocols, efficient and accurate methods of sample collection, and analytical methods of appropriate detectability for use in field-worker exposure studies. Subsequently, the task forces are conducting field studies that will generate data for inclusion in several generic databases. It is understood that the databases will be the property of the member companies who have financed the work of the task forces. It is hoped, however, that the task forces will see fit to publish their protocols, methods, study designs, and other useful information in a volume like this one so that other scientists working in this discipline may access the information. 

Mosca L, Barrett-Connor E, Wenger NK, Collins P, Grady D, Kornitzer M, Moscarelli E, Paul S, Wright TJ, Helterbrand JD, Anderson PW (2001a) Design and methods of the Raloxifene Use for The Heart (RUTH) study. Am J Cardiol 88 392-395... 

Yin R.K., 1994. Case Study Research Design and Methods, 2nd ed. Sage Publications, London. 

In an attempt to provide this focus, forty-seven active receptor model users from government, university, consulting and industry met for 2 1/2 days in February 1980 it. They addressed the models and the information required to use them in six separate task forces 1) Chemical Element Balance Receptor Models, 2) Multivariate Receptor Models, 3) Microscopic Identification Receptor Models, 4) Field Study Design and Data Management, 5) Source Characterization, and 6) Analytical Methods. The objectives of these interrelated task forces were to ... 

The measurements required for the present receptor models Include particulate matter composition, size and variability for both source and receptor. Obtaining these data requires attention to field study design and data management, source characterization, and analytical methods. 

The previous chapter discussed the (currently) relatively loosely defined statistical approaches to safety data collected in clinical trials. In contrast, there are widely accepted statistical methods for demonstrating efficacy in clinical trials. As has been noted several times in this book, if the study design and methodology have been appropriate and have led to the collection of optimum quality data, the statistical analysis and interpretation of efficacy data are relatively straightforward. The clinical (biological) interpretation of efficacy data is typically not quite as clear-cut, but there are widely accepted methodologies that are very useful in this realm too. Of particular importance here is the expert judgment of the clinicians who will review the statistical results with the statisticians and the rest of the study team. 

Although the concept of patient variability had been articulated by the middle of the twentieth century, the concept that a difference between two groups could be due to chance was slow to be accepted. The first clinical trial to use a formal statistical analysis reportedly occurred in 1962. The study involved a comparison of antibody production after yellow fever vaccination by two different methods. Several years later (1966) a critique of statistical methods used in medical journal manuscripts suggested a lack of proper study design and data analysis. In this critique, the authors canonized the criterion of P < 0.05 for a difference between two groups to be considered not due to chance. 

If the sample is representative, then the second consideration is how artefacts of randomly choosing the samples lead to random variation in the estimate of statistics of interest, such as the mean or standard deviation of sample distribution of interindividual variability. While it is often assumed that a small sample of data is not or could not be representative, this is a common misconception. The issue of representativeness is one of study design and sampling strategy. If one has a representative sample, even if very small, then conventional statistical methods can be used to make inferences regarding sampling distributions of statistics, such as... 

The analytical plan of epidemiological studies should use descrip tive and analytical techniques in describing the sample and results. Descriptive statistics, such as frequency distributions, cross-tabulations, measures of central tendency, and variation, can help explain underlying distributions of variables and direct the assessment of appropriateness of more advanced statistical techniques. Careful weighing of study findings with respect to the design and methods helps to ensure the validity of results. 

Recordkeeping is essential and it begins with a protocol that delineates the objectives of the study and outlines the experimental design and methods. To comply with the GLP requirements, the final test report on the toxicological effects of the test chemical substance includes specific descriptions. These may be listed as ... 

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