Observational study

Jump to navigation Jump to search

WikiDoc Resources for Observational study

Articles

Most recent articles on Observational study

Most cited articles on Observational study

Review articles on Observational study

Articles on Observational study in N Eng J Med, Lancet, BMJ

Media

Powerpoint slides on Observational study

Images of Observational study

Photos of Observational study

Podcasts & MP3s on Observational study

Videos on Observational study

Evidence Based Medicine

Cochrane Collaboration on Observational study

Bandolier on Observational study

TRIP on Observational study

Clinical Trials

Ongoing Trials on Observational study at Clinical Trials.gov

Trial results on Observational study

Clinical Trials on Observational study at Google

Guidelines / Policies / Govt

US National Guidelines Clearinghouse on Observational study

NICE Guidance on Observational study

NHS PRODIGY Guidance

FDA on Observational study

CDC on Observational study

Books

Books on Observational study

News

Observational study in the news

Be alerted to news on Observational study

News trends on Observational study

Commentary

Blogs on Observational study

Definitions

Definitions of Observational study

Patient Resources / Community

Patient resources on Observational study

Discussion groups on Observational study

Patient Handouts on Observational study

Directions to Hospitals Treating Observational study

Risk calculators and risk factors for Observational study

Healthcare Provider Resources

Symptoms of Observational study

Causes & Risk Factors for Observational study

Diagnostic studies for Observational study

Treatment of Observational study

Continuing Medical Education (CME)

CME Programs on Observational study

International

Observational study en Espanol

Observational study en Francais

Business

Observational study in the Marketplace

Patents on Observational study

Experimental / Informatics

List of terms related to Observational study

Editor-In-Chief: C. Michael Gibson, M.S., M.D. [1]


In statistics, the goal of an observational study is to draw inferences about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator. This is in contrast with controlled experiments, such as randomized controlled trials, where each subject is randomly assigned to a treated group or a control group before the start of the treatment.

The assignment of treatments may be beyond the control of the investigator for a variety of reasons:

  • A randomized experiment would violate ethical standards. Suppose one wanted to investigate the abortion–breast cancer hypothesis, which postulates a causal link between induced abortion and the incidence of breast cancer. In a hypothetical controlled experiment, one would start with a large subject pool of pregnant women and divide them randomly into a treatment group (receiving induced abortions) and a control group (bearing children), and then conduct regular cancer screenings for women from both groups. Needless to say, such an experiment would run counter to common ethical principles. (It would also suffer from various confounds and sources of bias, e.g., it would be impossible to conduct it as a blind experiment.) The published studies investigating the abortion–breast cancer hypothesis generally start with a group of women who already have received abortions. Membership in this "treated" group is not controlled by the investigator: the group is formed after the "treatment" has been assigned.
  • The investigator may simply lack the requisite influence. Suppose a scientist wants to study the public health effects of a community-wide ban on smoking in public indoor areas. In a controlled experiment, the investigator would randomly pick a set of communities to be in the treatment group. However, it is typically up to each community and/or its legislature to enact a smoking ban. The investigator can be expected to lack the political power to cause precisely those communities in the randomly selected treatment group to pass a smoking ban. In an observational study, she would typically start with a treatment group consisting of those communities where a smoking ban is already in effect.
  • A randomized experiment may be impractical. Suppose a researcher wants to study the suspected link between a certain medication and a very rare group of symptoms arising as a side effect. Setting aside any ethical considerations, a randomized experiment would be impractical because of the rarity of the effect. There may not be a subject pool large enough for the symptoms to be observed in at least one treated subject. An observational study would typically start with a group of symptomatic subjects and work backwards to find those who were given the medication and later developed the symptoms. Thus a subset of the treated group was determined based on the presence of symptoms, instead of by random assignment.

In all of those cases, if a randomized experiment cannot be carried out, the alternative line of investigation suffers from the problem that the decision which subjects receive the treatment and which subjects do not is not entirely random and thus is a potential source of bias. A major challenge in conducting observational studies is to draw inferences that are acceptably free from influences by overt biases, as well as to assess the influence of potential hidden biases.

Statistical methods

In observational studies, investigators may use propensity score matching (PSM) in order to reduce overt biases.

Reporting guidelines

The STROBE criteria can help report observational studies[1].

There is a checklist for each of three study designs:

  • cohort studies
  • case-control studies
  • cross-sectional studies

Risk of bias assessment

The minors criteria can help asses the risk of bias[2].

The criteria are:

  1. A stated aim of the study
  2. Inclusion of consecutive patients
  3. Prospective collection of data
  4. Endpoint appropriate to the study aim
  5. Unbiased evaluation of endpoints
  6. Follow-up period appropriate to the major endpoint
  7. Loss to follow up not exceeding 5%

And in the case of comparative studies

  1. A control group having the gold standard intervention
  2. Contemporary groups
  3. Baseline equivalence of groups
  4. Prospective calculation of the sample size
  5. Statistical analyses adapted to the study design

See also

References

  • Paul R. Rosenbaum (2002). Observational Studies, 2nd edn. New York: Springer-Verlag.


Template:WikiDoc Sources

  1. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; et al. (2007). "The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies". Ann Intern Med. 147 (8): 573–7. doi:10.7326/0003-4819-147-8-200710160-00010. PMID 17938396. https://www.equator-network.org/reporting-guidelines/strobe/
  2. Slim K, Nini E, Forestier D, Kwiatkowski F, Panis Y, Chipponi J (2003). "Methodological index for non-randomized studies (minors): development and validation of a new instrument". ANZ J Surg. 73 (9): 712–6. doi:10.1046/j.1445-2197.2003.02748.x. PMID 12956787.