lecture 6: descriptive follow-up studies
DESCRIPTION
Lecture 6: Descriptive follow-up studies. Natural history of disease and prognosis Survival analysis: Kaplan-Meier survival curves Cox proportional hazards analysis, hazard ratio . Natural history (clinical course) and prognosis of a disease. Why? Patient/family counseling - PowerPoint PPT PresentationTRANSCRIPT
1
Lecture 6: Descriptive follow-up studies
• Natural history of disease and prognosis• Survival analysis: Kaplan-Meier survival
curves• Cox proportional hazards analysis, hazard
ratio
2
Natural history (clinical course) and prognosis of a disease
• Why?– Patient/family counseling– Development and evaluation of interventions
• Types of study– Descriptive (persons with the disease only)– Analytical (comparison group) – Prognostic factors (risk factors for poor
prognosis)
3
Natural history/prognosis studies: Aspects of interest
• stages of the disease (subclinical, clinical)• outcomes
– death– disease (cure, progression)– disability (physical, mental)– distress (pain, other symptoms)
4
International Classification of Impairments, Disabilities, and Handicaps (ICIDH)
• IMPAIRMENT:– ...loss or abnormality of psychological, physiological, or
anatomical structure or function.• DISABILITY:
– ...restriction or lack (resulting from an impairment) of ability to perform an activity …
• HANDICAP: – ...disadvantage... resulting from an impairment or
disability, that limits or prevents the fulfillment of a role ….that is normal for that individual….
5
Measures of mortality/survival
• case-fatality rate• survival rate (1-year, 5-year etc)• median survival time• relative survival• survival curves (life-tables)
6
Measures of disease
• Disease definition– diagnostic criteria– clinical measures, pathology etc
• Time to key events:– Progression to another stage
• Prevalence of disease at specified follow-up time(s)
7
Measures of disability
• Activities of daily living (ADL)– independencein:
• basic ADL (e.g., feeding, washing)• instrumental ADL (e.g., telephone, money management)
• Sources of information– observation (performance)– self-report– proxy report
8
Measures of distress
• Subjective experience of disease– e.g., pain, discomfort, psychological distress,
depressive symptoms• Sources of information
– primarily self-report– for subjects unable to self-report, observational
methods may be needed
9
What is time zero?
• Date of first symptoms?• Date of detection?• Date of diagnosis?• Beware of differences in “time zero”between study
groups:– screening/early detection intervention shifts time zero– intervention appears to lengthen time to outcome without
real change in prognosis– “lead time” bias
10
Example: evaluation of the effectiveness of breast cancer
screening (HIP study)
• Possible outcomes:– survival rate (1 year, 5 year)– case-fatality rate– mortality rate
• Which is most appropriate?
11
12
Computation of lead-time of breast cancer screening (HIP study)
• using relationship between incidence, prevalence and mean duration
• data available:– incidence rate of clinical breast cancer = 1.84/1,000 per year– prevalence of pre-clinical breast cancer (from screening) = 2.73
per 1,000– average duration of pre-clinical breast cancer = 2.73/1.84 = 1.48
years– assumption: on average, patients are detected halfway through the
pre-clinical stage– lead-time = duration of pre-clinical stage = 1.48/2 = 0.74 years 2
13
Life-table methods: why are they needed?
• Not needed if all members of a cohort have complete follow-up to death
• Patients drop out of follow-up studies:– how should they be treated?
• At any point in time in a study, patients have been followed for different periods of time
14
Censoring of follow-up data• Censoring: loss of subjects from follow-up at time when outcome of
interest has not occurred:– Death– Enrolled too recently– Did not complete follow-up interview:
• moved away• refused• could not contact• did not attend follow-up appointment
• Assumption: Reason for censoring is independent of the outcome of interest
15
Types of life-tables
• Kaplan-Meier (clinical) life tables:– exact time to outcome is known
• Actuarial (population) life tables:– exact time to outcome unknown– outcome occurs in interval– estimation of average time to outcome within
interval
16
17
18
19
Summarizing survival-type data
• Mean or median?• Absolute or relative?
20
Cox proportional hazards analysis
• Multivariate technique, allowing adjustment for covariates (confounding variables)
• Similar to multiple logistic regression, except that dependent variable is time to outcome
• Hazard ratio (HR) interpretation similar to risk ratio
21
Example: Prognosis of delirium
• Study population: hospitalized patients aged 65+
• Time zero: hospital admission• Outcomes:
– survival (over 1 year)– cognitive impairment and disability (at 2, 6, 12
months)
Selection of cohorts
• Delirium cohort (n=243): patients meeting CAM criteria (DSM-IIIR) for delirium either at enrolment (prevalent cases) or during next week (incident cases)
• Control cohort (n=118): selected from patients without delirium, with weighted sampling to reduce confounding by dementia.
23
24
Mortality by delirium and dementia (adjusted)
Hazard ratios and 95% confidence intervals:
• No delirium or dementia 1.0• Delirium no dementia 3.77 (1.30-10.20)• Dementia no delirium 1.57 (0.52 - 4.71)• Both 1.98 (0.76 - 5.05)
25
Results: worse cognitive status
Mea
n M
MS
E S
core
Figure 1: Mean (95% Confidence Intervals) of MMSE scores at enrolment and follow-upby delirium and dementia at enrolment
05
1015
2025
30
Enrolment 2 6 12
Neither (n=42,40,35,33)Dementia only (n=52,46,39,37)Delirium only (n=56,44,33,24)Delirium & Dementia (n=164,139,112,93)
Time (months)
26
Results: worse physical function
Mea
n B
arth
el In
dex
Sco
re
Figure 2: Mean (95% Confidence Intervals) of Barthel Index scores at enrolment and follow-upby delirium and dementia at enrolment
020
4060
8010
0
Enrolment 2 6 12
Neither (n=42,39,36,35)Dementia only (n=53,48,42,41)Delirium only (n=56,43,34,27)Delirium & Dementia (n=164,136,114,95)
Time (months)
27
Example: effect of drug abuse rehabilitation programs on time
to first drug use
• 2 concurrent randomized controlled trials of residential drug abuse treatment programs of different planned duration:– traditional therapeutic community (TC)
• abstinence-oriented• 6 vs 12 months
– modified TC with relapse prevention approach• relapse prevention/health education orientation• 3 vs 6 months
28
Example: effect of drug abuse rehabilitation programs on time
to first drug use
• PRIMARY OUTCOME: time to first drug use (measured at follow-up interviews)
• PROBLEM:– high rates of attrition from treatment – patients assumed drug-free during treatment
• TIME ZERO?– Date of admission?– Date of discharge/exit
29
Methodological Questions• Censoring:
• loss to follow-up:– outcome or censored data?
• Decision on time zero:– primary analyses using admission, secondary analyses
using exit• Decision on censoring:
– primary analyses: censoring of loss to follow-up– secondary analyses: loss to follow-up considered to have
used drugs on day after exit from program
30
31
32