Understanding Clinical Papers. David Bowers
socio‐economic classes. What is a lot less clear is whether lower socio‐economic status is a risk factor for schizophrenia or, conversely, whether schizophrenia causes a slide down the socio‐economic scale. The cross‐sectional study design – in which the researcher measures in each subject a supposed risk factor at the same time as recording the presence of a condition – will nearly always have this chicken or egg problem (which comes first?).
In a study of bullying (Figure 6.2), the researchers persuaded 904 co‐educational secondary school pupils aged 12–17 years to declare whether they were bullied or not and to self‐report their feelings – including a scale that measured their level of anxiety. They found that those who reported being bullied also reported more anxiety. Notice that the study design does not preclude either possibility: that bullying exacerbates anxiety or that anxious children are more likely to be targets for bullies.
Figure 6.2 Extract from table of summary statistics from cross‐sectional study of bullying and self‐reported anxiety (values are numbers of schoolchildren unless stated otherwise).
Source: From Salmon et al. (1998), © 1998, BMJ Publishing Group Ltd.
It is a limitation of cross‐sectional designs that the direction of any effect cannot be determined because the supposed risk factor and the outcome are identified at the same time. The next two analytic study designs tackle this weakness and are able to identify the direction of any effect.
CASE–CONTROL STUDIES
A more satisfactory way of investigating cause and effect is to concentrate on a clinical scenario in which the characteristic that you suspect might be a risk factor and the outcome can only have arisen in that order. Consider for a moment smoking and lung cancer: it is plain that contracting lung cancer cannot have led someone to become a long‐standing heavy smoker.
Notice though that it is the pre‐existence of heavy smoking that defines the difference between this example and the cross‐sectional example above. If a researcher wanted to know whether high blood pressure made stroke more likely and chose to measure blood pressure in two groups of patients, who were and were not victims of stroke, then any finding that hypertension was more prevalent in stroke patients might be a consequence of the stroke rather than a contributory cause. If, on the other hand, each set of patients had previously had their blood pressure recorded some years before, then the finding that stroke patients had a past excess of hypertension might very well point to high blood pressure being a risk factor for stroke.
Case–control study is the label applied to a study such as the one just mentioned, about high blood pressure and stroke. The group of people with the condition are called the cases and they are compared with another group who are free of the disease and are called the controls. The comparison to be drawn is the exposure of each of the two groups to a supposed risk factor: were the cases more often exposed to the risk than were the controls? For further discussion of cases and controls, see Chapters 16 and 17.
In the study in Figure 6.3, mental health researchers undertook a case–control study to help to determine the role of cannabis in the incidence of psychosis. They recruited, from 11 sites across Europe and Brazil, 901 consecutive patients with first‐episode psychosis. They also recruited 1237 controls – people who did not have psychosis – from the same geographical catchment areas, using various sampling strategies involving random selection, from lists of postal addresses and from general practitioner lists. Using a modified version of the Cannabis Experience Questionnaire, they asked all participants about their use of cannabis and other recreational drugs. They found, for example, that there was a much higher risk of psychosis among people who reported daily cannabis use than among those who had never used the drug (after adjusting for various possibly confounding factors): the adjusted odds ratio was 3.2 – see Chapter 28 for an explanation of odds ratios in case–control studies, and Chapter 17 for material about confounding.
Figure 6.3 A case–control study examining the relation between cannabis use and onset of psychosis.
Source: From Di Forti et al. (2019), © 2019, Elsevier.
COHORT ANALYTIC STUDIES
Another way of identifying any relation between cannabis and onset of psychosis would have been to compare the eventual outcome for 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),