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Recruitment and Enrollment Assessment in Clinical Trials (REACT), an NHLBI-sponsored substudy of the Cardiac Arrhythmia Suppression Trial (CAST), was conducted to assess factors associated with enrollment in clinical trials. We report on the relationships of institutional factors at CAST sites to patient enrollment. The proportion of CAST-eligible patients enrolling at each CAST site during the REACT study period was defined as the number of subjects enrolled divided by the sum of (1) the number enrolled plus (2) the number of eligibles who refused plus (3) the number of eligibles whose physicians refused to permit CAST personnel to attempt to enroll them. A questionnaire that included 78 questions regarding factors hypothesized to be associated with enrollment was completed between August 1988 and February 1990 by the nurse coordinators at all 112 CAST sites in the United States and Canada. Sixteen items were unanalyzable, and 37 of the remaining 62 were grouped into seven scales. The remaining items were analyzed individually. Enrollment proportions varied widely across the 112 CAST sites (mean 32.7% SD 22.6). Five variables or scales were included in the final multiple regression model (multiple R2 = .39). The most important of these was the proportion of eligible patients at a site cared for by medical staff other than private attending physicians (multiple R2 for this variable alone, .26). This proportion tended to be high in teaching hospitals. Other variables in this model that were associated with higher enrollment proportions included the number of days per week a nurse coordinator was present at the site, the number of nurse coordinator full-time equivalents at the site, fewer other clinical trials for which the nurse coordinator was responsible, and fewer perceived obstacles to enrollment. These findings indicate that enrollment was more successful at hospitals with higher proportions of eligible subjects cared for by fellows, housestaff, and service attending physicians and at institutions with the committed presence of a nurse-coordinator.

Meta-analysis, a set of statistical tools for combining and integrating the results of independent studies of a given scientific issue, can be useful when the stringent conditions under which such integration is valid are met. In this report we point out the difficulties in obtaining sound meta-analyses of either controlled clinical trials or epidemiological studies. We demonstrate that hastily or improperly designed meta-analyses can lead to results that may not be scientifically valid. We note that much care is typically taken when meta-analysis is applied to the results of clinical trials. The Food and Drug Administration, for example, requires strict adherence to the principles we discuss in this paper before it allows a drug's sponsor to use a meta-analysis of separate clinical studies in support of a New Drug Application. Such care does not always carry over to epidemiological studies, as demonstrated by the 1986 report of the National Research Council concerning the purported association between exposure to environmental tobacco smoke and the risk of lung cancer. On the basis of a meta-analysis of 13 studies, 10 of which were retrospective and the remaining 3 prospective in nature, the Council concluded that non-smokers who are exposed to environmental tobacco smoke are at greater risk of acquiring lung cancer than non-smokers not so exposed. In our opinion, this conclusion in unwarranted given the poor quality of the studies on which it is based.

Because the clinics in a multiclinic randomized clinical trial represent neither fixed stratification effects nor random classificatory effects, the appropriate analysis of data from such a trial has been the subject of controversy and debate. The following are some of the elements of controversy that are discussed and for which some bases for resolution are proposed. Is it ever valid to ignore the effects of clinics in the analysis? Is it ever valid to drop clinics from the analysis? Is a multiclinic clinical trial similar in structure or not to a single-clinic clinical trial in which patients have been stratified on a classificatory factor? Assuming that clinics will be taken account of in the analysis, should it be the weighted or the unweighted average of within-clinic treatment differences that is to be taken as the best estimate of the overall difference between the treatments? How should the data be analyzed if there is evidence of treatment-by-clinic interaction?

Most large comparative trials of therapeutic agents are now conducted as multicentre studies. Some of the major studies designed by Bradford Hill were also multicentre, and his methods of design and conduct remain valid today, even though improved methods for analysing the data have appeared subsequently.

A critical review is provided of recent articles on two-treatment crossover trials that purport to provide solutions to the problems caused by the existence of differential carryover effects. Included in the review are papers suggesting that extra-period designs be employed in which treatments follow themselves, that the bias caused by a difference between the carryover effects may sometimes be ignored, that changes from baseline be analyzed, and that a series of preliminary tests using baseline values be performed. The validity of many of these suggestions is shown to depend on whether mathematical assumptions that are generally unverifiable are satisfied. The two-period crossover design is recommended only when prior experience suggests that its assumptions are likely to be satisfied.