Allocated to intervention (n = )  Declined to   participate (n = )
Allocated to intervention (n = )
Analyzed (n = )  Excluded from analysis  (give reasons) (n = ) Lost to follow-up (give reasons) (n = ) Discontinued intervention (give reasons (n = ) Analyzed (n = )  Excluded from analysis  (give reasons) (n = ) Lost to follow-up (give reasons) (n = ) Discontinued intervention (give reasons (n = ) Analysis
Figure 4.1 CONSORT ﬂow diagram.
Randomized controlled trials should be evaluated with an intention-to-treat analysis, which means that all of the people randomized at the initiation of the trial should be accounted for in the analysis with the group to which they were assigned. Unless part of the overall study design, even if a participant stopped participating in the assigned treatment or “crossed over” to another treatment during the study, they should be analyzed with the group to which they were initially assigned. All of these considerations help to minimize bias in the design, implementation, and interpretation of a clinical trial (6).
Observational Studies In cases where the exposure and outcome are not amenable to an experimental design, because the exposure is known or suspected to have harmful effects, observational studies may be used to assess association. Observational studies, including cohort, case-control, and cross-sectional studies, are analytic studies that take advantage of “natural experiments” in which exposure is not assigned by the investigator; rather, the individuals are assessed by the investigator for a potential exposure of interest (present or absent) and outcomes (present or absent). The timing of the evaluation of the exposure and outcome defines the study type.
No disease Disease Prospective 2011 Historical cohort 1988 2028 2011 Exposed group Unexposed group Disease-free population No disease Prospective assessment of the outcome Prospective assessment of the outcome Disease
Figure 4.2 Schematic of prospective and retrospective cohort study designs.
Cohort Studies Cohort studies often are referred to as longitudinal studies. Cohort studies involve identifying a group of exposed individuals and unexposed individuals and following both groups over time to compare the rate of disease (or outcome) in the groups. Cohort studies may be prospective, meaning that the exposure is identified before outcome, or retrospective, in which the exposure and outcome have already occurred when the study is initiated. Even in a retrospective cohort study, the study is defined by the fact that the cohorts were identified based on the exposure (not the outcome), and individuals should be free of disease (outcome) at the beginning time point for the cohort study (Fig. 4.2).
In a study that includes a survival analysis, the two cohort groups (exposed and nonexposed) begin with a population that is 100% well (or alive) at the beginning of the study. The groups are followed over time to calculate the percentage of the cohort still well (or alive) at different time points during the study and at the end of the study. Although a survival analysis typically describes mortality after disease (i.e., cancer patients who died within 5 years), it can be adapted to other events and outcomes (e.g., the percentage of women who become pregnant while using long-acting contraceptives).
Strengths of cohort studies include the ability to obtain both attributable and relative risks because the occurrence of the outcome is being compared in two groups (see the section on Presenting and Understanding the Results of Analytic Studies). However, only associations can be established, not causality. Because randomization is not part of the study design, the investigator must consider that a factor associated with the exposure may lead to the outcome rather than the exposure itself. Misclassifying the exposure or the outcome and confounding variables are potential sources of bias in cohort studies.
Given that truly prospective cohort studies can be expensive and take a long time for completion, there should be compelling evidence for the public health importance of the exposure(s) and association(s) being addressed. Issues related to sample size and participant retention in the study protocol are as important in cohort studies as they are in randomized controlled trials.