Study Design 101



A subset of systematic reviews; a method for systematically combining pertinent qualitative and quantitative study data from several selected studies to develop a single conclusion that has greater statistical power. This conclusion is statistically stronger than the analysis of any single study, due to increased numbers of subjects, greater diversity among subjects, or accumulated effects and results.

Meta-analysis would be used for the following purposes:

If the individual studies utilized randomized controlled trials (RCT), combining several selected RCT results would be the highest-level of evidence on the evidence hierarchy, followed by systematic reviews, which analyze all available studies on a topic.



Design pitfalls to look out for

The studies pooled for review should be similar in type (i.e. all randomized controlled trials).

Are the studies being reviewed all the same type of study or are they a mixture of different types?

The analysis should include published and unpublished results to avoid publication bias.

Does the meta-analysis include any appropriate relevant studies that may have had negative outcomes?

Fictitious Example

Do individuals who wear sunscreen have fewer cases of melanoma than those who do not wear sunscreen? A MEDLINE search was conducted using the terms melanoma, sunscreening agents, and zinc oxide, resulting in 8 randomized controlled studies, each with between 100 and 120 subjects. All of the studies showed a positive effect between wearing sunscreen and reducing the likelihood of melanoma. The subjects from all eight studies (total: 860 subjects) were pooled and statistically analyzed to determine the effect of the relationship between wearing sunscreen and melanoma. This meta-analysis showed a 50% reduction in melanoma diagnosis among sunscreen-wearers.

Real-life Examples

Bahekar, A.A., Singh, S., Saha, S., Molnar, J., Arora, R. (2007). The prevalence and incidence of coronary heart disease is significantly increased in periodontitis: A meta-analysis. American Heart Journal, 154(5), 830-7.

Previous studies have shown conflicting results as to whether periodontitis (PD) is associated with increased risk of coronary heart disease. Meta-analysis of the 5 prospective cohort studies (86,092 patients) indicated that individuals with PD had a 1.14 times higher risk of developing CHD than the controls (relative risk 1.14, 95% CI 1.074-1.213, P < .001), indicating that both the prevalence and incidence of CHD are significantly increased in PD and PD may be a risk factor for CHD.

Ageno, W., Becattini, C., Brighton, T., Selby, R., Kamphuisen, P.W. (2008). Cardiovascular risk factors and venous thromboembolism: A meta-analysis. Circulation, 117(1), 93-102.

The concept that venous thromboembolism (VTE) and atherosclerosis are two completely distinct entities has recently been challenged because patients with VTE have more asymptomatic atherosclerosis and more cardiovascular events than control subjects using meta-analysis techniques to assess the association between cardiovascular risk factors and VTE. Twenty-one case-control and cohort studies with a total of 63,552 patients were included, showing the risk of VTE was 2.33 for obesity (95% CI, 1.68 to 3.24), 1.51 for hypertension (95% CI, 1.23 to 1.85), 1.42 for diabetes mellitus (95% CI, 1.12 to 1.77), 1.18 for smoking (95% CI, 0.95 to 1.46), and 1.16 for hypercholesterolemia (95% CI, 0.67 to 2.02). This demonstrated that cardiovascular risk factors are associated with VTE, which is clinically relevant with respect to individual screening, risk factor modification, and primary and secondary prevention of VTE. Prospective studies should further investigate the underlying mechanisms of this relationship.

Related Terms

Now test yourself!

1. A Meta-Analysis pools together the populations from different studies, such as Randomized Controlled Trials, into one statistical analysis and treats them as one large study population with one conclusion.

a) True
b) False

2. One potential design pitfall of Meta-Analyses that is important to pay attention to is:

a) Whether it is evidence-based.
b) If the authors combined studies with conflicting results.
c) If the authors appropriately combined studies so they did not compare apples and oranges.
d) If the authors used only quantitative data.

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