Download presentation
Presentation is loading. Please wait.
Published byMarilynn Powers Modified over 9 years ago
1
11/20091 EPI 5240: Introduction to Epidemiology Cohort studies: A return November 23, 2009 Dr. N. Birkett, Department of Epidemiology & Community Medicine, University of Ottawa
2
11/20092 John Snow, 1860: According to a return which was made to Parliament, the Southwark and Vauxhall Company supplied 40,046 houses from January 1 to December 31, 1853, and the Lambeth Company supplied 26,107 houses during the same period; consequently, as 286 fatal attacks of cholera took place, in the first four weeks of the epidemic, in house supplied by the former company, and only 14 in houses supplied by the latter, the proportion of fatal attacks to each 10,000 houses was as follows: Southwark and Vauxhall 71, Lambeth 5. The cholera was therefore fourteen times as fatal at this period, amongst persons having the impure water of the Southwark and Vauxhall Company as amongst those having the purer water from Thames Ditton.
3
11/20093 Some issues with Snow’s report: Dynamic populations. Sort of a ‘rate’ since the denominator is ‘family-years’. –Are families the same size in the two cohorts? –Lack of control for age differences. –Other confounders. –SES factors. –mortality vs. disease incidence. –Validity of exposure allocation people have S&V water linkage but use water from a well –this is happening now with ‘bottled water’.
4
11/20094 General types of Study Populations (1) Type #1 –Recruit subjects at a fixed point in time (eg. people exposed to the Hiroshima atomic bomb). –Population involve a fixed list of people –Follow-up is complete on everyone. Type #2 –Recruit subjects at a fixed point in time (eg. people exposed to the Hiroshima atomic bomb). –Population involve a fixed list of people –Some people are lost-to-follow-up (drop-outs, censored)
5
11/20095 General types of Study Populations (2) Type #3 –Recruit subjects over time (eg. recruit people newly diagnosed with HIV starting in Jan, 2003 and ending in Dec. 2005) –Population involve a fixed list of people –Follow-up may or may not be complete on everyone. Type #4 –Define a cohort based on criteria such geography, etc. (eg. people living in the boundaries of Ottawa-Carleton). –Follow-up the group over time. –You DO NOT have a list of who is in the group. –People will move in and out of the group during follow-up.
6
11/20096 General types of Study Populations (3) TERMINOLOGY Fixed:The membership of the group is known at the ‘start’; in-migration is not allowed. This definition is sometimes extended to require people to remain in the same exposure group; Closed:A ‘fixed’ group in which no-one is allowed to leave (ie. follow-up is 100% complete). Open:A group in which people are allowed to both enter and leave during follow-up. Dynamic:The same as ‘open’. Cohort vs. population/group –The term ‘cohort’ is usually reserved for groups which are ‘fixed’ while ‘population’ is used when membership is open. Needs definition
7
11/20097 General types of Study Populations (4) Type #1:Closed cohort (fixed) Type #2:Fixed cohort Type #3:Fixed cohort Type #4:Dynamic (open) population
8
11/20098 KEY ISSUES (1) Defining cohort membership –ALL cohorts will have losses and late entry. Therefore, model for cohort is based on person-year rather than persons Logistics of retaining participation and obtaining the information Exposure measurement, not only the practicalities but also the theory of what to measure. –How to account for time variability of exposure? –Simplifying assumption: use a simple numerical summary (eg. average, peak, cumulative, lagged). CAN BE BIASSED. Person-time allocation. Outcome assessment
9
11/20099 EXPOSURE ISSUES (1) Depends on your hypothesis. Should be as SPECIFIC as possible. –Acute exposure to ionizing radiation will increase risk of colon cancer, starting 5 years after exposure. Time for accumulating exposure VS Time at risk for outcomes. –Lags (induction period) –Changes in risk with time. Acute vs chronic exposure.
10
11/200910 EXPOSURE ISSUES (2) Atomic bomb exposure Acute exposure (almost a point source in time) No risk of cancer in first few months/years A simple ID will give average effect and thus will under-estimate effect. –Look at risk in various post-exposure time windows.
11
11/200911 ID Time
12
11/200912 EXPOSURE ISSUES (4) CHRONIC EXPOSURES (e.g. smoking) Exposures can be: –Fixed Occur once –Atomic bomb exposure Have a single onset but then remain as an exposure –Fluoride added to drinking water (fixed levels) –Dixon from a spill (decaying levels) –Time varying Start/stop –Smoking, drugs, work exposures Continuous but level varies –Diet –Background & continuous radiation
13
11/200913 EXPOSURE ISSUES (5) CHRONIC EXPOSURES (e.g. smoking) Fixed exposures –Can be measured once at baseline –Assumed to not change during follow-up –Defines exposure groups –Suitable for count data but also person-time data. Time varying exposures –Requires multiple measurements (at baseline and during follow- up) to determine change in exposure status –Only usable in person-time studies –Need a rule to determine whether person-time/outcomes between measures accumulates to ‘exposed’ or ‘non-exposed’ group.
14
11/200914 EXPOSURE ISSUES (6) PY’s accumulate in exposure group at the time. Assign outcome to exposure group which is accumulating PY’s at time of event. Need to consider induction time. –Delay from exposure to earliest onset of any disease due to exposure. Atomic bomb exposure on January 1, 2000 Leukaemia diagnosed on January 2, 2000 CAN NOT be causally linked. –Common to assume induction time is ‘0’ in the absence of detailed information True in most situations. Analogous thing happens when exposure is stopped –Risk continues for some time and may not decline to ‘0’ (another issue)
15
11/200915 EXPOSURE ISSUES (6) ‘Unexposed’ time accumulates in exposed group. –prior to end of induction period (after 1 st exposure) –after end of ‘at risk’ period (when exposure stopped). –during induction/risk period for exposure changes during follow- up Example –‘moderate’ smoking is 20-40 pack-years with 5 year induction time. Person remains in ‘mild’ smoking group until 5 years after acquiring 20 pack-years. Immortal Person Years –Follow-up time during which a subject can never get the outcome (because of the study design) subjects were recruited two years after starting to work Cohort starts at time of first employment Everyone must have survived at least two years
16
11/200916 EXPOSURE ISSUES (7) CHRONIC EXPOSURES (cont.) Types of exposure measures –Ever/never –Maximum level –Average level –Cumulative Exposure Pack-years (smoking cumulative exp measure) –Add up number of cigarettes smoked in life-time; –Divide by 7305 (1 P-Y = 20 cigs/pack * 365.25 days) –Composite measure of duration and intensity. –Assumes: 0.5 packs/day x 20 years = 4 packs/day x 5 years Consider separate duration and intensity variables.
17
11/200917 Change to overhead file
18
11/200918 EXPOSURE ISSUES (8) Post-exposure events Objective: Effect of quitting smoking on CHD risk. –What to do with someone who quits and then starts smoking again? –Censor at time of recidivism Objective: Effect of having stopped smoking for five (or more) years)? –Include only people with 5+ years of time after stopping smoking. –Treat first five years post-stopping as Immortal PY’s. Criteria for exposure grouping for continuous exposure Quintiles or quartiles are common Can base on distribution in cohort or on external data about exposure risk.
19
11/200919 Outcome issues Timing of event Definition of outcome Logistics of determining if (and when) an outcome occurred.
20
11/200920 Logistic Issues Expense Related to large size and induction period. Worse with rare outcomes and long induction periods. Try to reduce cost by: –Using administrative system to detect outcome events; –Historical designs; –Use the ‘general population’ as the unexposed cohort; –Nested case-control study. Tracking subjects –Need at LEAST 60% follow-up with 80% (or higher) being the target. Should you change measurement methods during follow-up?
21
11/200921 Keeping participation up Subject’s need to develop committment with study (identify with it) –Regular contacts –Newsletters –Web site –Paraphernalia –Highlight key information, papers, awards, contributions to policy Contact name, address, e-mail,etc. –Up-date regularly –Obtain contact info for at least one friend/relative –Professional organization, church, etc.
22
11/200922 Estimating ‘Incidence’ (1) Fixed Population (cohort) –Select all members at a Pre-determined point Jan 1, 2010 1 st diagnosis of disease Type A: –Equal, known follow-up in ALL subjects Type B –Variable but known follow-up Some lost-to-follow-ups (censored) Variable time of entry Type C –Variable F/U and some people have unknown exact length of follow-up
23
11/200923 Estimating ‘Incidence’ (2) Dynamic Population –Does not start with a pre-determined, named, fixed group MONICA study –People living in Halifax between 1980 and 1990 –Not the same people each year. Type A: –Variable but known follow-up times Really is a type C fixed cohort Type B –Variable unknown exact length of follow-up for individual subjects The ‘classic’ dynamic population Cancer incidence studies
24
11/200924 Switch to overhead slides
25
11/200925 How much lung cancer can be attributed to smoking? Measure of exposure IMPACT rather than strength. There are many AR measures, often with similar names. Makes things confusing. One book used the same abbreviation for 4 different measures in five pages! Attributable risks (1)
26
11/200926 In exposed subjects Attributable risks (2) ExpUnexp RD or Attributable Risk I exp I unexp RD = AR = I exp - I unexp I exp – I unexp AR(%)=AF= ----------------------- I exp
27
11/200927 In the exposed group, the impact of the exposure on outcome depends on RR only: 1 –AR(%) = 1 - -------- RR A value of ‘0’ shows no impact. Shouldn’t compute AR’s unless causation has been established. Attributable risks (3)
28
11/200928 My actual question was: in the general population, how much lung cancer was due to smoking? Depends on two factors: –Strength of the smoking/lung cancer relationship (RR). –How common smoking is in the population (exposure prevalence). Attributable risks (4)
29
11/200929 Attributable risks (5) Exp Unexp Attributable Risk, population I exp I unexp Population I pop
30
11/200930 Switch to overhead slides
Similar presentations
© 2025 SlidePlayer.com Inc.
All rights reserved.