Cohort study
A cohort study is a particular form of longitudinal study that samples a cohort (a group of people who share a defining characteristic, typically those who experienced a common event in a selected period, such as birth or graduation), performing a cross-section at intervals through time.
In medicine for instance, while clinical trials are used primarily for assessing the safety of newly developed pharmaceuticals before they are approved for sale, epidemiological analysis on how risk factors affect the incidence of diseases is often used to identify the causes of diseases in the first place, and to help provide pre-clinical justification for the plausibility of protective factors (treatments).
[citation needed] Double-blind randomized controlled trials (RCTs) are generally considered superior methodology in the hierarchy of evidence in treatment, because they allow for the most control over other variables that could affect the outcome, and the randomization and blinding processes reduce bias in the study design.
A cohort is a group of people who share a common characteristic or experience within a defined period (e.g., are currently living, are exposed to a drug or vaccine or pollutant, or undergo a certain medical procedure).
However, cohort studies are expensive to conduct, are sensitive to attrition and take a long follow-up time to generate useful data.
Some cohort studies track groups of children from their birth, and record a wide range of information (exposures) about them.
In a cohort study, the population under investigation consists of individuals who are at risk of developing a specific disease or health outcome.
[4] An example of an epidemiological question that can be answered using a cohort study is whether exposure to X (say, smoking) associates with outcome Y (say, lung cancer).
Cohort Succession can explain most change in literature, art, intellectualism, political opinions, and phonology.
Key findings of NCDS and a detailed profile of the study appear in the International Journal of Epidemiology.
Other famous examples are the Grant Study tracking a number of Harvard graduates from ca.
[7] The ASPREE-XT study is designed to determine whether there are long-lasting effects of an average of four–five years of treatment with daily low-dose aspirin, with outcome measures including cancer mortality.
[12] In a historical cohort study the data concerning exposure and occurrence of a disease, births, a political attitude or any other categorical variable are collected after the events have taken place, and the subjects (those exposed and unexposed to the agent under study) are assembled from existing records or health care registers.
The procedure begins like a normal cohort study, however, as participants develop the outcome of interest they are selected as cases.
[15] Nested case-controls have the advantage of reducing the number of participants that require details follow up or diagnostic testing to assess outcome or exposure status.
Conventionally, cohort studies require manual definitions of the common characteristics, which are time-consuming and labor-intensive, demanding extensive domain expertise.
For example, in healthcare, we can identify patients with a certain combination of feature conditions as a specific cohort, typically resulting in a similar outcome or end-point.
These AI-derived cohorts not only enhance the ability to evaluate new patients but also hold significant potential to accelerate medical research and discovery.
