Before you watch this video you should check out the 2 previous videos in the Biostatistics & Epidemiology section which cover Validity & Bias as well as Confounding & Types of Bias. Those videos have principles that will be applied to this video on Types of Study Design.
Hierarchy of Evidence
Based on the types of bias that are inherent in some study designs we can rank different study designs based on their validity. The types of research studies at the top of the list have the highest validity while those at the bottom have lower validity. In most cases if 2 studies on the same topic come to different conclusions, you assume the trial of the more valid type is correct. However, this is not always the case. Any study design can have bias. A very well designed and executed cohort study can yield more valid results than a clinical trial with clear deficiencies.
- Meta-analysis of multiple Randomized Trials (Highest Validity)
- Randomized Trial
- Prospective Cohort Studies
- Case Control Studies or Retrospective Cohort
- Case Series (Lowest Validity)
Meta-analysis is the process of taking results from multiple different studies and combining them to reach a single conclusion. Doing this is sort of like having one huge study with a very large sample size and therefore meta-analysis has higher power than individual studies.
Randomized Clinical Trials (RCT)
Clinical trials are the gold standard of research for therapeutic and preventative interventions. The researchers have a high level of control over most factors. This allows for randomization and blinding which aren’t possible in many other study types. Participant’s groups are assigned by the researcher in clinical trials while in observational studies “natural conditions” (personal preference, genetics, social determinants, environment, lifestyle …) assign the group. As we will see later, the incidence in different groups is compared using Relative Risk (RR).
Cohort Studies are studies where you first determine whether or not a person has had an exposure and then you monitor the occurrence of health outcomes overtime. It is the observational study design with the highest validity. Cohort is just a fancy name for a group, and this should help you remember this study design. You start with a group of people (some of whom happen to have an exposure and some who don’t). Then you follow this group for a certain amount of time and monitor how often certain diseases or health outcomes arise. It is easier to conceptually understand cohort studies that are prospective. However, there are retrospective cohort studies also. In this scenario you identify a group of people in the past. You then first identify whether or not these people had the particular exposure at that point in time and determine whether or not they ended up getting the health outcomes later on. As we will see later, the incidence in different groups in a cohort study is compared using Relative Risk (RR).
Case-Control Studies are retrospective and observational. You first identify people who have the health outcome of interest. Then you carefully select a group of controls that are very similar to your diseased population except they don’t have that particular disease. Then you try to determine whether or not the participants from each group had a particular exposure in the past. I remember this by thinking that in a case control study you start off knowing whether a person is diseased (a case) or not diseased (a control). There isn’t a huge difference between retrospective cohort and case-control. You are basically doing the same steps but in a slightly different order. However, the two study designs are used in different settings. As we will see later, the incidence in different groups in a case-control study is compared using Odds Ratio (OR).
A Case-Series is a small collection of individual cases. It is an observational study with a very small sample size and no control group. Basically you are just reviewing the medical records for a few people with a particular exposure or disease. A study like this is good for very rare exposures or diseases. Obviously the small sample size and lack of a control group limits the validity of any conclusions that are made, but in certain situations this is the best evidence that is available.
Cross Sectional Studies are different from the others we have discussed. While the other studies measure the incidence of a particular health outcome over time, a cross-sectional study measures Prevalence. In this observational study the prevalence of the exposure and the health outcome are measured at the same time. You are basically trying to figure out how many people in the population have the disease and how many people have the exposure at one point in time. It is hard to determine an association between the exposure and disease just from this information, but you can still learn things from these studies. If the exposure and disease are both common in a particular population it may be worth investing more resources to do a different type of study to determine whether or not there is a causal relationship.