Cohort studies

• Cohort studies:

  • Observes people over time
  • can be for weeks, months or years
  • Exposures (agents/risk factors) & outcomes are record
  • Purpose
  • To understand the natural history of a disease
  • To evaluate long term patient health or quality of life
  • Analyse the relationship between risk factors & disease
• Cohort studies:

  • Cohort = group of people who share common exposure (e.g. year of birth)
  • E.G.
  • start with people without the disease, document exposures, follow through time
  • Includes those with & without risk factors
  • Determines incidence (new cases) of disease
  • Research question: Whether exposure to factor ‘x’ leads to disease ‘Y'?
• Model of Cohort studies:

  • find a population of interest and select a sample population
  • measures the exposure level of the sample population at baseline to see who is exposed and who isnt exposed
  • follow them for a set period of time and see who had the outcome and who didnt have the outcome in the exposed and unexposed groups

  
• Model of Cohort Studies Examples:

  • sample population of a healthy group to see who develops a disease
  • sample population with acute disease to see who recovers and who becomes chronic - this would be considered a inception cohort as we're starting the study after the disease has already started
  • sample population with chronic disease to see who recovers
• ‘Landmark’ cohort studies:

  • UK Doctors Cohort Study (1950s) - 40,000 UK doctors
  • USA Nurses Cohort Study (mid-1970s) - > 121,700 female nurses (Oral contraceptive and breast cancer)
  • UK Oral Contraceptive Pill cohort study (1968 - present) - 46,000 women, all cause mortality
  • The million women study - women > 50 years (1 in 4 women in UK) HRT, cancer, other disease
• UK Doctors Cohort Study:

  • 1951: Smoking questionnaire from 40,000 British doctors (Doll & Hill)
  • Assessed: 1951, 1957, 1966, 1971, 1978, 1991, 2001....
  • Analysis
  • Excess mortality in smokers
  • Reversal of effect in ex-smokers
  • Other diseases eg IHD, respiratory disease, CVD, bladder cancer, etc
  • cessation at
  • 30 y/o - gain 10 years life expectancy
  • 40 y/o - gain 9 years life expectancy
  • 50 y/o - gain 6 years life expectancy
  • 60 y/o - gain 3 years life expectancy

  
• Strengths of cohort design:

  • Can directly estimate risk and relative risk of disease in a population
  • Can determine the natural history of a condition
  • Can calculate incidence
  • Can demonstrate temporal sequence
  • Analysis of many different exposures/outcomes
  • Less prone to bias than case-control and cross-sectional studies
• Weaknesses of cohort studies:

  • SELECTION BIAS e.g. unrepresentative population
  • MEASUREMENT OR CLASSIFICATION BIAS e.g. poor standardisation, unblinded assessors, changes in diagnostic criteria
  • ATTRITION BIAS e.g. loss to follow up (not at random)