Info

Study design

Description

+ -

Summarize findings from a number of studies addressing a given clinical question; meta-analyses quantitatively estimate effects based on combining data from different studies.

Systematic reviews and meta-analyses

Randomized clinical trial

Prospective cohort study (includes nested case-control study)

Retrospective cohort study

Case-control study

Summarize findings from a number of studies addressing a given clinical question; meta-analyses quantitatively estimate effects based on combining data from different studies.

Subjects randomly assigned to an intervention or control group.

Randomization ensures that the intervention is the only factor to vary between the comparison groups.

Exposures of subjects assessed at beginning of study; disease or other outcomes evaluated over time.

Exposures of subjects assessed retrospectively, e.g., occupational exposures via historic job records.

Prior exposure and disease assessed at a point in time. Subjects selected on the basis of disease status (with or without); past exposures evaluated retrospectively.

Meta-analyses have greater statistical power than single studies to address questions. Convenient way to summarize findings from a range of studies.

Represents true experiment.

Randomization removes effects of confounding and bias.

Considered gold standard among clinical studies.

The most efficient method to test definitively for causal relationships between an intervention and health outcomes.

More efficient for common diseases.

Allows assumption that exposure precedes disease.

Allows consideration of a wide range of confounders.

Useful for assessing past exposures of large numbers of subjects over time.

More efficient for relatively rare diseases such as cancer. May allow consideration of a wide range of confounders.

Must meet assumption that studies can legitimately be combined (based on population, study design, etc.).

Literature searches must be performed systematically and studies included without bias.

Expensive: requires extensive study infrastructure and training of staff.

May be unethical or impracticable for some hypotheses.

Often expensive: requires large study infrastructure.

Time consuming (subjects often followed for years).

Subject to confounding (measured or unmeasured).

Attrition of study population can affect generalizability.

Assumption that exposure precedes disease may be less strong than in prospective design.

Confounders may have to be assessed at the present, and proxies for nonliving subjects may introduce bias.

Disease itself may affect evaluation of exposure (changes to biochemical measurement, selective recall).

Subject to various types of error in evaluation of past exposure.

Subject to confounding (measured or unmeasured).

Exposure does not necessarily precede disease.

can distort estimates of risk and benefit. Such unmeasured confounding is believed to have resulted from the crucial bias (selection bias) that rather impressively provided such consistency of results among observational studies of combined hormone therapy. The Women's Health Initiative, in contrast, was able to eliminate whatever confounders were at play by virtue of its randomized placebo-controlled design.

A Disquistion On The Evils Of Using Tobacco

A Disquistion On The Evils Of Using Tobacco

Among the evils which a vitiated appetite has fastened upon mankind, those that arise from the use of Tobacco hold a prominent place, and call loudly for reform. We pity the poor Chinese, who stupifies body and mind with opium, and the wretched Hindoo, who is under a similar slavery to his favorite plant, the Betel but we present the humiliating spectacle of an enlightened and christian nation, wasting annually more than twenty-five millions of dollars, and destroying the health and the lives of thousands, by a practice not at all less degrading than that of the Chinese or Hindoo.

Get My Free Ebook


Post a comment