The planning of clinical studies: a matterof choice

Although some medical studies defy classificationwith respect to their design, they can often be cate-gorized according to several features. Some of thesefeatures have implications for the type of analysisthat follows; others have consequences related tothe inferences that can be made. Some affect both. Aclear statement of the design features of a study is agreat help to the critical reader.

Assignment of study factor

Because the focus of this column is on compara-tive studies, probably the most important distinc-tion from the perspective of the inferences that canbe made is whether the study is experimental orobservational. This is because, in comparing an out-come of interest in 2 groups, one with and the otherwithout a factor, a well-conducted experiment canlead to cause-and-effect conclusions, whereas anequally well-conducted observational study cannotreadily go beyond a statement of presence orabsence of association between the factor and theoutcome. What distinguishes one type of study fromthe other is the process by which the factor comes tobe assigned to the subjects. In an experiment, thefactor is randomly assigned to a predeterminednumber of members of an initially homogeneousgroup, with the goal of having the presence orabsence of the factor as their only distinguishingcharacteristic. In an observational study, subjectstypically have self selected to have or not have thefactor, and because of that, observed differences inoutcome between the 2 groups may be attributableto causes other than the factor.

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By the Numbers S Debanne

Directionality of sampling

Frequently, experiments cannot be done and inves-tigators must rely on observational studies. Althoughthe factor under study has to precede the outcomepresumably associated with it, the investigator hasdifferent choices with respect to the strategy used toselect subjects. In a nondirectional study, both factorand outcome are observed simultaneously. In a cohortstudy, subjects are selected on the basis of the pres-ence or absence of the factor and their experiencewith respect to the outcome is then observed. In acase-control study, subjects are selected on the basisof their disease status, and their prior experiencewith respect to the factor is then ascertained. Thechoices made with respect to the directionality ofsampling have profound implications regarding themethods of analysis and the conclusions that can bemade. It is obvious, for instance, that a nondirection-al study cannot focus on incident cases of a diseasebut has to be limited to observing its prevalence.Further, because the factor and the outcome areobserved at the same time, this type of study can onlyexamine the presence or absence of association, withno discussion of temporality. Case-control studies arewell suited for studying rare diseases because, bysampling by disease status, the cases are already“visible,” and all that is needed is the selection of anappropriate control group of nondiseased individuals.One can then ascertain the presence or absence of thefactor of interest in each individual’s past. In practice,findings of most case-control studies can be ques-tioned because of potential biases that can arise whenchoosing a control group.

Frequency of sampling

Observational studies may also be classified asbeing cross-sectional, in the sense that patients arestudied at a single point in time, or they may be lon-gitudinal, where repeated observations are made onthe patients over time. This distinction impacts themethod of analysis. Data measured repeatedly overtime typically require more sophisticated treatmentthan cross-sectional data. Often, the longitudinaldata is of the “time to event” type, requiring the useof techniques of survival analysis for descriptionand for analysis. Further, longitudinal studies mayfollow the same group of patients over a period oftime (fixed cohort) or they may allow the cohort torenew itself so that its composition changes overtime (dynamic cohort).

Units of observation

The units of observation may differ depending on

the goals of the study. In some situations, the indi-vidual patients may be the units whereas in othersituations it may be that the units are entities suchas stents; a patient may give rise to more than oneunit. This distinction has a great influence withrespect to the choice of analytic technique. Manystatistical techniques are based on the assumptionof independence of observations. This does not holdin situations in which a single individual gives riseto multiple data points, as would be the case when apatient receives more than one stent.

Main purpose of data collection

Another characteristic is the timing of data col-lection, in relation to the date of the study, so thatthe data may be collected prospectively or retro-spectively. Although this characteristic does not nec-essarily affect the choice of statistical testing, itinfluences the quality of the data and the inferencesto be made. Typically, data collected prospectivelyand specifically for a study whose objectives arealready specified (primary data) will be of higherquality than data recorded previously for anotherpurpose (secondary data).

Other types of studies, often involving develop-ment of estimates, include those related to diagnos-tic testing, to decision analysis or economic analysis,and to meta-analysis. Some studies are simplydescriptive in nature. But for almost every studysome of the features listed above can be used to clas-sify it, albeit partially.

A database study of characteristics of successivecolorectal polyps seen over a 20-year period in 1000patients who underwent periodic examinationsafter an initial finding could be characterized as alongitudinal study of a dynamic cohort, based onsecondary data that were collected prospectively.Each patient would give rise to multiple data pointsand this would require a nonstandard analysis. Inthe absence of a particular factor and a particularoutcome, such a study could not be classified withrespect to the directionality of sampling. A compre-hensive treatment of these issues can be found inKleinbaum et al.1

Sara M. Debanne, PhDCleveland, Ohio

REFERENCE

1. Kleinbaum DG, Kupper LL, Morgenstern H. Epidemiologicresearch: principles and quantitative methods. Belmont (CA):Lifetime Learning Publications, Wadsworth, Inc; 1982.

doi:10.1067/mge.2001.111567

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