Epidemiological Studies

Observational Studies

Observational studies are used to observe and measure outcomes in a cohort with no control over risk factors or variables. They are often retrospective. Types of observational studies include cross-sectional studies, case-control studies, and cohort studies.

Cross-sectional studies

• Collect data about an entire population at a single point in time (cross-section of time)
  • Participants are not followed over time.
• Typically used to measure prevalence Prevalence The total number of cases of a given disease in a specified population at a designated time. It is differentiated from incidence, which refers to the number of new cases in the population at a given time. Measures of Disease Frequency (i.e., how many people have the disease in a population)
  • Also called prevalence Prevalence The total number of cases of a given disease in a specified population at a designated time. It is differentiated from incidence, which refers to the number of new cases in the population at a given time. Measures of Disease Frequency studies
• Advantages:
  • Inexpensive, if making use of routinely collected data
  • Easy to perform
• Disadvantages:
  • Unable to determine causality Causality Causality is a relationship between 2 events in which 1 event causes the other. Simply because relationships are observed between 2 variables (i.e., associations or correlations) does not imply that one variable actually caused the outcome. Demonstrating causality between an exposure and an outcome is the main objective of most published medical research. Causality, Validity, and Reliability because exposures and outcomes are measured simultaneously
  • Unable to include data on confounding variables Confounding variables A confound is an additional variable other than the independent variable that has an effect on the dependent variable, causing an erroneous relationship to be inferred between them. Types of Biases

Case-control studies

• Start from an outcome and work backward (retrospectively) in time to see who had an exposure
• 2 groups are compared based on an outcome or the presence of disease:
  1. Cases: those who have or have had the outcome or disease
  2. Control: those who lack the outcome or disease
• The proportions of those with an exposure in the case and control groups are compared to see if there is an association.
• Matching: selecting controls so that they share similar characteristics with cases that are identified as possible confounding factors (e.g., sex Sex The totality of characteristics of reproductive structure, functions, phenotype, and genotype, differentiating the male from the female organism. Gender Dysphoria, age, smoking Smoking Willful or deliberate act of inhaling and exhaling smoke from burning substances or agents held by hand. Interstitial Lung Diseases status) in an effort to remove the confounding effect
  • Individual matching: matching an individual control to an individual case
  • Group or frequency matching: equal percentages of controls and cases with a characteristics group with characteristics (e.g., 50% of cases and controls are men)
• Advantages:
  • Inexpensive
  • Can be carried out by small groups of investigators
  • Shorter in duration
• Disadvantages:
  • Cannot measure the incidence Incidence The number of new cases of a given disease during a given period in a specified population. It also is used for the rate at which new events occur in a defined population. It is differentiated from prevalence, which refers to all cases in the population at a given time. Measures of Disease Frequency
  • Cannot reliably determine a subject’s exposure status over time (subject to observation bias Bias Epidemiological studies are designed to evaluate a hypothesized relationship between an exposure and an outcome; however, the existence and/or magnitude of these relationships may be erroneously affected by the design and execution of the study itself or by conscious or unconscious errors perpetrated by the investigators or the subjects. These systematic errors are called biases. Types of Biases)
  • Identifying a sample of controls can be difficult and subject to selection Selection Lymphocyte activation by a specific antigen thus triggering clonal expansion of lymphocytes already capable of mounting an immune response to the antigen. B cells: Types and Functions bias Bias Epidemiological studies are designed to evaluate a hypothesized relationship between an exposure and an outcome; however, the existence and/or magnitude of these relationships may be erroneously affected by the design and execution of the study itself or by conscious or unconscious errors perpetrated by the investigators or the subjects. These systematic errors are called biases. Types of Biases.

Cohort studies

• An observational study that chooses a cohort that shares a common exposure and observes this group over time (prospectively) to see who develops the outcome of interest
• A longitudinal study in which the temporal relationship Relationship A connection, association, or involvement between 2 or more parties. Clinician–Patient Relationship between exposure and outcome is established
  • Cohorts can also be “retrospective” (i.e., looking into medical records and seeing if the outcome developed itself prospectively in the past), but this restricts the ability of the investigator to control for confounding and bias Bias Epidemiological studies are designed to evaluate a hypothesized relationship between an exposure and an outcome; however, the existence and/or magnitude of these relationships may be erroneously affected by the design and execution of the study itself or by conscious or unconscious errors perpetrated by the investigators or the subjects. These systematic errors are called biases. Types of Biases.
• Typically used for establishing possible cause and effect before randomized control trials (RCTs) are undertaken

Interventional Studies

Interventional studies are prospective experimental trials in which investigators compare the effects of an intervention on subjects with a control group. The most compelling type of interventional study is the RCT.

Randomized controlled trial

• Also called randomized clinical trials
• Gold standard for evidence:
  • Provides the strongest evidence for establishing causation
• Used to:
  • Compare the efficacy of new therapy regimens and drugs against current therapies
  • Evaluate new screening Screening Preoperative Care and prevention strategies
  • Come up with new ways to organize and deliver healthcare
• Can be performed in both clinical and community settings
• Study groups: also called study arms
  • Intervention/experimental group: Participants are exposed or receive the intervention.
  • Control group: Participants receive the current standard of care Standard of care The minimum acceptable patient care, based on statutes, court decisions, policies, or professional guidelines. Malpractice, a placebo, or nothing at all.
• Groups are chosen so that the 2 groups have almost identical conditions, except for the exposure of interest.
• Groups must be balanced: equivalent in size
• Principle of intention to treat:
  • If subjects change groups, the results should be analyzed according to the initial group allocation of subjects.
• Randomization:
  • Random allocation of subjects to either intervention or control group
  • Participants are assigned to either group by chance.
  • Reduces the chances of selection Selection Lymphocyte activation by a specific antigen thus triggering clonal expansion of lymphocytes already capable of mounting an immune response to the antigen. B cells: Types and Functions bias Bias Epidemiological studies are designed to evaluate a hypothesized relationship between an exposure and an outcome; however, the existence and/or magnitude of these relationships may be erroneously affected by the design and execution of the study itself or by conscious or unconscious errors perpetrated by the investigators or the subjects. These systematic errors are called biases. Types of Biases because the chance of being in either group is 50/50
• Blinding:
  • Subjects and/or investigators don’t know the groups to which subjects are assigned.
  • Single-binding: Subjects do not know if they are getting the intervention or a placebo.
  • Double-blinding: Both participants and investigators do not know to which groups subjects are assigned.
  • Triple-blinding: blinding of the meta-analyst
  • Blinding reduces the chances of the Hawthorne and Rosenthal effects
    • Hawthorne effect Hawthorne effect Refers to the tendency of subjects in a study to behave or act differently (i.e., work harder) when they know they are being watched. Types of Biases: the tendency of subjects to behave differently if they know they are being studied
    • Rosenthal effect Rosenthal effect Refers to the tendency of subjects or investigators to behave differently based on other’s expectations. Types of Biases: changes in the behavior of subjects based on the researcher’s expectations
• Placebo:
  • A medically ineffective intervention that mimics a real intervention so that a subject will not know to which study group they are assigned
  • Placebo effect: Any treatment, even if ineffective, results in improvement because the recipient believes it will.

Quasi-experiment

• A study that lacks the randomization and often the blinding component
• The investigator decides who will be assigned to which group.
• Lacks internal validity Internal validity Causality, Validity, and Reliability but has great external validity External validity Causality, Validity, and Reliability

Natural experiments

• Resembles an RCT but the allocation is decided by an external force (e.g., natural disaster)

Ecological studies

• Populations are the unit of analysis instead of individuals.
• Ecological fallacy: Associations for populations cannot be applied to individuals.