13th February 2024

Study design

Primary versus secondary research

Medical research can be divided into two main forms: primary and secondary research. Primary research involves collecting new data, which can be further divided into experimental studies (including lab-based), clinical, and epidemiological studies. Secondary research involves drawing conclusions from pre-existing primary data and summarising them, most commonly in systematic reviews or meta-analyses.

Hierarchy of study design

In general, there is a recognised hierarchy of studies for obtaining evidence, with a more rigorous methodology and reduced risk of bias as one moves up the pyramid:

That being said, the “hierarchy” of evidence also depends on the type of question being answered, e.g. treatment benefits, prognosis, and cost-effectiveness. Here is a summary:

That being said, the “hierarchy” of evidence also depends on the type of question being answered, e.g. treatment benefits, prognosis, and cost-effectiveness. Here is a summary:

Randomised controlled trials (RCTs)

RCTs, particularly when double-blinded and with placebo controls where possible, are typically regarded as the gold standard of clinical research. Participants are randomly assigned to two or more groups to maximise homogeneity between groups to test a specific intervention, ideally with one group as a control or placebo group. Blinding participants and researchers to the intervention can also reduce the risk of bias. Participants are then followed up to determine the effectiveness of the experimental intervention over the control, and outcomes are measured accordingly.

Cohort studies

Also known as longitudinal studies, cohort studies follow groups of people over specified periods to ascertain how a chosen variable, e.g. occupation, dietary habits, or smoking status, may lead to different outcomes. They can also be divided into prospective and retrospective studies. Well-designed prospective studies are less likely to lead to bias than retrospective ones, but they can take years to perform and incur more significant costs. Famous examples of prospective studies include the British Doctors’ Study, which ran for 50 years from 1951 to 2001, and the ongoing Framingham Heart Study, now in its third generation of participants. Common statistical outcomes of cohort studies include cumulative incidence and incidence rates and ratios.

Cross-sectional studies

In cross-sectional studies, participants are selected based on a pre-defined set of inclusion and exclusion criteria. Then, the investigator measures the exposures and the outcomes of the selected participants at the same time. Therefore, this study design is ideal for assessing the prevalence of an outcome, exposure or disease in a specified population. Associations between an exposure/risk factor and an outcome may be explored, but it is difficult to establish causal relationships from a cross-sectional study. It is also important to remember that the prevalence of a disease (total number of cases, including both old and new) is dependent on its incidence (number of new cases) and length of survival. Hence, a cross-sectional study is not always sufficient to understand the trend of a disease. Important statistical outcomes used for analysis include prevalence and odds ratios.

Case-control studies

Case-control studies are retrospective observational studies typically used to determine the causality or exposure(s) related to a disease or outcome by comparing a group of people with the disease to another similarly matched group without the disease (controls). By knowing the outcome and assigning subjects to their respective groups, one can investigate exposures by tracing them back in time. Hence, they are particularly advantageous when investigating disease outbreaks or rare diseases. Odds ratios are typically used for comparing statistical outcomes in these studies.

Systematic reviews and meta-analyses

When primary data is pooled together, secondary research can be performed in the form of systematic reviews. By pooling data from multiple smaller trials, a meta-analysis could statistically combine results from ten trials of 500 patients each and be used to draw appropriate conclusions as if it were analysing a trial with 5,000 patients. A well-conducted systematic review, such as those published by the Cochrane Library, addresses a focussed, well-formulated clinical question, draws from multiple primary sources, synthesises material in the form of meta-analyses and conducts a rigorous critical appraisal to summarise the results of its included studies. In this way, it could provide a high level of evidence on the effectiveness of an intervention, which can be used to inform recommendations and guidelines.

References

Röhrig B, du Prel JB, Wachtlin D, Blettner M (2009). Types of study in medical research: Part 3 of a series on evaluation of scientific publications. Dtsch Arztebl Int, 106(15), 262-268.

Kapoor MC (2016). Types of studies and research design. Indian J Anaesth, 60(9), 626–630.

Setia MS (2016). Methodology Series Module 1: Cohort Studies. Indian J Dermatol, 61(1), 21-25.

Setia MS (2016). Methodology Series Module 3: Cross-sectional Studies. Indian J Dermatol, 61(3), 261-264.

Lewallen S, Courtright P (1998). Epidemiology in practice: case-control studies. Community Eye Health, 11(28), 57–58.

Deeks JJ, Higgins JPT, Altamn DG (ed.). Chapter 10: Analysing data and undertaking meta-analyses. In: Higgs JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (ed.) (2021). Cochrane Handbook for Systematic Reviews of Interventions. Accessed on 2022 Jan 11. Available from: https://training.cochrane.org/handbook/current/chapter-10.

Møller AM, Myles PS (2016). What makes a good systematic review and meta-analysis? British Journal of Anaesthesia, 117(4), 428-430.