people who did or did not use cannabis – a cohort study – sometimes termed a cohort analytic study, thereby emphasizing the comparative (or analytic) objective of the investigation. In this hypothetical example, the subjects of the research would have been divided by the researcher according to whether they were cannabis users or not. In the earlier, real, case–control study the study participants were divided by whether they had the disease (psychosis in this case) or not; the designs are quite different.
In a real example of a cohort analytic study shown in Figure 6.4, researchers looked into whether open rather than laparoscopic surgery – in the abdomen or pelvis – is a risk factor for later readmission as a consequence of surgical adhesions. Adhesions are a kind of scar tissue that develop in most patients who have abdominal or pelvic surgery, and they are a major cause of long‐term morbidity. The researchers used National Health Service data from Scotland to determine whether each woman who had an abdominal or pelvic operation had been readmitted as a consequence of a disorder caused by adhesions over the next five years and, in each case, whether the original surgery was by laparoscopic or open procedure. The likelihood of a readmission due to adhesions was compared between the women who had laparoscopic and open surgery.
Figure 6.4 A retrospective cohort analytic study examining the relation between readmission to hospital for disorders directly related to adhesions and earlier open or laparoscopic abdominal surgery.
Source: From Krielen et al. (2020), © 2019, Elsevier.
Prospective and Retrospective Cohort Designs
The research shown here investigating the possible relation between open (rather than laparoscopic) surgery and adhesions‐related readmission is an example of a retrospective cohort study. The researchers looked back into the Scottish record‐linkage data to determine the presence or absence of the risk factors of interest (open surgery versus laparoscopic surgery) and examined the occurrence of adhesions‐related readmission to hospital over the years between the operation and some recent time. More often, cohort analytic studies are prospective in their design. In one example (Figure 6.5), Canadian researchers recruited a consecutive series of over 300 women who had a child delivered at the hospital. As it happened, around half of the women opted for epidural anaesthesia, allowing a comparison between them and women whose labour was assisted by alternative forms of pain relief – to determine whether new back pain had higher incidence among those who had received an epidural.
Figure 6.5 Prospective cohort analytic study examining the relation between post‐partum back pain and epidural anaesthesia during labour.
Source: From Macarthur et al. (1995), © 1995, BMJ Publishing Group Ltd.
You may have noticed one prominent feature that distinguishes case–control from cohort designs: case–control studies ask the question by looking backwards (asking whether more cases than controls had been exposed to some risk factor), while cohort analytic studies ask their question by looking forwards (asking whether more people who were exposed to the risk, than people who weren't exposed, developed the outcome in question). But you need to be careful with your thinking and your terminology in relation to the words retrospective and prospective because, as we have seen, it is possible to ask the (forward‐going) question of the cohort study by starting now and looking ahead (Figure 6.5), or by starting with the presence and absence of the risk factor some time previously and following up until lately (Figure 6.4). Put another way, case–control studies are retrospective but cohort studies may be described, quite properly, as either prospective or retrospective.
VARIATIONS IN CASE–CONTROL AND COHORT DESIGNS
So‐called nested case–control studies are found in the health literature in abundance. The concept is very similar to the standard version of the case–control study, but the cases and controls are selected from a large cohort study, reducing the research work that would be needed were the whole cohort to be analysed. All the cases in the cohort will usually be selected, together with several (usually one to five) controls per case. Suppose we have decided to have five controls per case – to maximize statistical provision (more than five controls per case offer little extra precision). The controls could be selected randomly from the people in the cohort who are still at risk at the time of the index case and are time‐matched with their specific ‘case' – creating a ‘risk‐set', in this illustration consisting of one case and five controls. There are several advantages over the conventional case–control study. First, conventional case–control studies often struggle to determine control groups that truly represent the study population, and use convenience samples; here, the randomly selected controls are a representation of the people in the cohort and thereby in the study population. Second, the exposure data in the cohort design will have been collected prospectively and are thereby free of recall bias – a common problem with case–control studies (see Chapter 16). Nested studies may differ in their analysis from conventional case–control studies (see Chapter 28), but this matter is beyond the scope of this book.
Much less frequently encountered, but also derived from a large cohort study, is the case‐cohort design. In such a study, a sub‐cohort is selected from a large cohort study at the start of the follow‐up; the sub‐cohort is not time‐matched with the cases. The analysis is relatively complicated, partly because it involves the sub‐cohort and cases outside the sub‐cohort, but it offers some advantages over the conventional case–control analysis (see Chapter 28).
COMPARING AND CONTRASTING CASE–CONTROL AND COHORT STUDIES
Compared with cohort studies, case–control studies are cheap and cheerful. First, they can be completed without waiting for the outcome to develop. Second, there is no need for enormous numbers of study subjects who do not develop the outcome; because in a case–control study it is already clear who has the outcome, only a convenient number (needed for reasonable statistical precision) of these 'controls' is needed. In a cohort study, however, there is no way of knowing who will get and not get the outcome – so everyone has to be included until the study end‐point reveals who has developed the condition so far. For a great many relatively uncommon outcomes the case–control study is favoured for just these reasons. Examples of case–control studies include investigating whether deep venous thrombosis is related to taking the oral contraceptive pill, and whether depressive illness is related to adverse life events and difficulties.
On the other hand, there are serious shortcomings with case–control studies. They are prone to extra biases – in particular those concerned with recollection of past events. Suppose, for example, that a study hypothesis is that an adult condition such as motor neurone
