Types of studies, their advantages and disadvantages

Descriptive studies

These are of the form of "we cannulated the coronary arteries of a dog and recorded the changes in SVR when vasopressin was infused". They describe, and that is essentially all. One ought to be careful relating these studies to clinical practice.

Animal Studies

Rationale for animal studies

  • Only useful as hypothesis-generating studies
  • generally held to be the lowest level of evidence


  • Its cheaper
  • Adequate physiological/biochemical surrogate for humans
  • Limits human suffering due to experimentation

Disadvantages: lack of applicability to humans

  • Animals have different metabolic pathways; drug pharmacokinetics may be affected
  • Animals used for research are young and have no comorbidities
  • Differences in age (usually, only young healthy animals are used)

Defects of methodology

  • Statistically, less rigorous
  • a posteriori reasoning is common
  • Short follow-up; slowly manifesting effects may be missed
  • Outcome measures are frequently unrelated to clinically relevant parameters

Case reports

  • This is usually the lowest or second lowest level of evidence (just above animal studies).
  • However, there is still a role for them to play:
    • They identify rare complications
    • They identify new avenues for research
    • Rare conditions are only known though case reports

Case series

  • No control group
  • Observational studies
  • Merely a series of case reports

Cross-sectional surveys

  • No control group
  • Observational studies
  • Merely a large series of case reports

Case-controlled studies

  • Retrospective: looks backwards to identify risk factors associated with outcomes. Some sort of historical controls are used.
  • Measures exposure to risk factors
  • Odds ratio is used to quantify risk

These are a type of analytical observation study. The investigators choose a group with a shared feature (the cases) and another group without those features (the controls). The groups are compared retrospectively, to see if in the past the groups differed in their exposure to something of interest - a risk factor, a treatment, etc. Essentially, it is a case of selecting the outcome you are interested in, and working backwards from it.

Cohort studies

  • Prospective
  • Observes exposure, and then observes the development of disease
  • Relative risk is used to quantify risk

These are another type of analytical observation study. The investigators choose a group who have been exposed to some sort of treatment or risk, and a control group which is identical in every way other than that exposure. the groups are then followed prospectively, to see the difference in their outcomes.

Obviously, all of these sorts of "non-trial" studies suffer from inherent bias. In a perfect world, one would not have to base one's clinical decisionmaking on evidence such as this.

Cross-over trials

  • Each patient acts as their own control
  • Patients cross over from one treatment to the next
  • There is usually a "washout" period between treatments
  • There is usually randomisation

Self-controlled studies

  • Each patient is their own control
  • post treatment measurements for each patient are compared to pre-treatment measurements

Randomised controlled trials

Gold standard for evidence. LITFL has a detailed breakdown.


  • This is the only sort of study which can establish causation
  • Minimises bias and confounding
  • More publishable


  • Sometimes it is impossible to randomise (eg. unethical)
  • Expensive and difficult to run
  • By the time its finished, clinical practice may have moved on
  • Inclusion/exclusion criteria may limit external validity
  • Subject to practice misalignment

Standardised reporting of trial results

  • Reporting of trial data is governed by the CONSORT statement, which describes how trials should be reported. It is designed to produce literature with the highest degree of transparency, so that people are able to easily interpret the results.

Meta-analysis and systematic review

Meta-analysis is a tool of quantitative systematic review. It is used to weigh the available evidence from RCTs and other studies based on the numbers of patients included, the effect size, and on statistical tests of agreement with other trials.

So much detail has been expected from CICM exam candidates in regards to meta-analysis, that the topic merits a chapter all of its own.


Gurwitz, Jerry H., et al. "Reader's guide to critical appraisal of cohort studies: 1. Role and design." BMJ: British Medical Journal 330.7496 (2005): 895. Mamdani, Muhammad, et al.

"Reader's guide to critical appraisal of cohort studies: 2. Assessing potential for confounding." BMJ: British Medical Journal330.7497 (2005): 960. Normand, Sharon-Lise T., et al.

"Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding." BMJ: British Medical Journal 330.7498 (2005): 1021.

von Elm, Erik, et al. "The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies." International Journal of Surgery 12.12 (2014): 1495-1499.

Sanderson, Simon, Iain D. Tatt, and Julian PT Higgins. "Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: a systematic review and annotated bibliography." International journal of epidemiology 36.3 (2007): 666-676.

Carlson, Melissa DA, and R. Sean Morrison. "Study design, precision, and validity in observational studies." Journal of palliative medicine 12.1 (2009): 77-82.