Randomized Trials: the Evidence in EvidenceBased - PowerPoint PPT Presentation

Loading...

PPT – Randomized Trials: the Evidence in EvidenceBased PowerPoint presentation | free to view - id: 1ea1d-ZGI1M



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Randomized Trials: the Evidence in EvidenceBased

Description:

'Benefits (for CHD, osteoporosis) outweigh risks (breast cancer) and ... Clinical trials needed to establish cause and effect. Beta carotene: Clinical trial #1 ... – PowerPoint PPT presentation

Number of Views:181
Avg rating:3.0/5.0
Slides: 45
Provided by: denn2
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Randomized Trials: the Evidence in EvidenceBased


1
Randomized Trials the Evidence in
Evidence-Based
  • Today
  • Randomized trials why bother?
  • Randomization
  • Selection of participants (Inclusion/exclusion)
  • Design options for trials
  • Dennis Black, PhD
  • Dblack_at_psg.ucsf.edu
  • 597-9112

2
Randomized Controlled Trial (RCT)
  • A study design in which subjects are randomized
    to intervention or control and followed for
    occurrence of disease
  • Experimental (as opposed to observational)
  • Definitive test of intervention
  • Confounders are equally distributed across
    intervention groups
  • Treated not younger, richer, healthier,
    better dieters

3
Examples of interventions
  • Drug vs. placebo
  • Low fat diet vs. regular diet
  • Exercise vs. CPP

4
Number of randomized trials published
8000
7000
6000
5000
4000
3000
2000
1986
1988
1990
1992
1994
1996
1998
Based on Medline search for Randomized
5
Disadvantages of RCTs
  • Expensive
  • Time Consuming
  • Can only answer a single question
  • So, why bother?

6
Alternatives to RCTs(30 second Epi. Course)
  • Case-control studies
  • Compare those with and without disease
  • Cohort studies (prospective)
  • Identify those with and without risk factor
  • Follow forward in time to see who gets
    disease
  • Cohort and case-control are observational (not
    experimental)

7
Reasons for doing RCTs
  • Only study design that can prove causation
  • Required by FDA (and others) for new drugs and
    some devices
  • Most influential to clinical practice

8
Example Estrogen Replacement Therapyin
post-menopausal women
  • Important therapeutic question
  • Applies to 30 (?) million women in US
  • Prempro (estrogen/progestin combo)may be most
    prescribed drug in US
  • Potentially huge impact on public health
  • Complex, ERT effects multiple diseases

9
Estrogen Replacement Therapy (ERT)
  • Disease Effect on Risk
  • Coronary heart disease Decrease by 40 -
    80Osteoporosis (hip fx) Decrease by 30 -
    60Breast cancer Increase by 10 -
    20Endometrial cancer Increase by 700
  • Alzheimers Decrease by ?
  • Pulmonary embolism Increase by 200 - 300deep
    vein thrombosis

From observational (case-control and cohort)
studies
10
Nurses Health Study (NEJM, 9/12/91)
  • Prospective cohort study, n 48,470
  • 337,000 person years of follow-up
  • Risk of Major Estrogen Use Coronary
    Disease Relative Risk
  • Never Used 1.4 1.0
  • Current user 0.6 0.56 (0.40-0.80)
  • Former user 1.3 0.83 (0.65-1.05)

Events per 1000 women-years of follow-up
Relative Risk (95 CI) compared to never users
11
Meta-analysis of ERT, Published 4/10/97
  • Benefits (for CHD, osteoporosis) outweigh risks
    (breast cancer) and side effectsAll
    post-menopausal women should be taking ERT

CNN, 4/10/97
12
Virtually all estrogen results arebased on
observational data
  • Women chose to take ERT
  • Are ERT users different from non-users?
  • Age
  • Health status
  • More exercise
  • Health behaviors (see Dr.)
  • SES
  • Try to adjust in analysis, but may not be
    possible
  • Randomized trials alleviate these problems

13
Heart and Estrogen-Progestin Replacement Study
(HERS)
  • Secondary prevention of heart disease
  • HRT (Prempro) vs. placebo (4-5 years)
  • 2763 women with established heart disease
  • Postmenopausal,
  • 20 clinical centers in U.S./UCSF Coordinating
    center
  • Funding by Wyeth-Ayerst (post-NIH refusal)
  • Expected results????
  • Real results JAMA 8/98

14
HERS Summary of results
  • Endpoint Placebo HRT RR P
  • New CHD 176 172 0.99 0.91
  • Any fracture 138 130 0.95 0.70
  • Conclusion Randomized trials can lead to big
    surprises!

15
Other surprisesBeta Carotene and cancer
  • Strong suggestions that beta carotene would
    prevent cancer
  • 1. Observational epi. (diets high in fruits
    and vegetables with beta carotene
    lower cancer risk)
  • 2. Pathophysiology
  • Clinical trials needed to establish cause and
    effect

16
Beta carotene Clinical trial 1
  • The Alpha-Tocopherol, Beta CaroteneCancer
    Prevention Study
  • RQ Do vitamin E and beta-carotene prevent lung
    cancer in smokers?
  • Design RCT, factorial, 6.1 years
  • Subjects 29,133 smokers, Finnish men aged 50-69
  • Intervention 1. Alpha-tocopherol, 50 mg/day vs.
    placebo(factorial) 2. Beta-carotene, 20 mg/day
    vs. placebo
  • Outcome Lung cancer incidence

17
Beta-carotene Clinical Trial 1Results
Incidence per 10,000 person years
  • Beta-Carotene Control RR
  • Lung Cancer Cases 56.3 47.5 1.19
  • Lung Cancer Deaths 35.6 30.8 1.16
  • Relative risk Beta carotene vs. control

18
Beta carotene Clinical trial 2
  • The Beta-Carotene and Retinol Efficacy Trial
    (CARET)
  • RQ Do vitamin A and beta-carotene prevent
    lung cancer in smokers?
  • Design RCT, 4.0 years
  • Subjects 18,314 men, smokers or asbestos workers
  • Intervention Retinol (25,000 IU) and beta
    carotene (15 mg) vs. placebo
  • Outcome Lung cancer incidence

19
Beta-carotene Clinical Trial 2Results
  • Lung Cancer Death (all causes)
  • All Subjects 1.28 (1.04-1.57) 1.17 (1.03-1.33)
  • Asbestos-exposed 1.40 (0.95-2.07) 1.25
    (1.01-1.56)
  • Smokers 1.23 (0.96-1.56) 1.13 (0.96-1.32)

Relative Risk (95 CI), treatment vs. placebo
20
Beta Carotene RCTs
  • Beta carotene not recommended for cancer
    prevention
  • Similar story for beta carotenes and heart
    disease
  • RCTs very useful

21
Examples of major breakthroughs from RCTs
  • Protease inhibitors and AIDS
  • Aspirin and heart disease
  • Lipid lowering (statins) and heart disease

22
Steps in a Classical Randomized, Controlled
Trail (RCT)
  • 1. Select participants
  • 2. Measure baseline variables
  • 3. Randomize (to 1 or more treatments)
  • 4. Apply intervention
  • 5/6. Follow-up--measure outcomes
  • Most commonly one treatment vs. control
  • Can be used for various types of outcomes
    (binary, continuous)

23
Randomization
  • Key element of RCTs
  • Assure equal distribution of both...
  • measured/known confounders
  • unmeasured/unknown confounders
  • Important to do well
  • True random allocation
  • Tamper-proof (no peaking, altering order of
    participants, etc)
  • Simple randomization
  • Low tech
  • High tech

24
Other types of randomization
  • Blocking equal after each n assignments
  • e.g., block size of 4, treatments a and b
  • abab aabb bbaa baab
  • Assure relatively equal number of ppts. to each
    treatment
  • Disadvantages of blocking
  • Size of block 2 treatments--4 or 6
  • Very commonly used
  • Formally random, permuted blocks

25
Randomization to balance prognostic variables
  • Stratified permuted blocks
  • Blocks within strata of prognostic variable
  • e.g., HRT study of prevention of MI. High LDL at
    much higher risk--want to avoid more higher LDL
    in placebo.
  • Stratum
  • High LDL aabb baba
  • Normal LDL baab abab .
  • Limited number of risk factors
  • Very commonly used in multicenter studies to
    balance within clinical center
  • Fancier techniques for assuring balance
  • Adaptive randomization (not much used)

26
Implementation of randomization
  • Less challenging for blinded studies
  • Sealed envelopes in fixed order at clinical sites
  • Alternatively list of drug numbers
  • a b a b b b a a
  • 1 2 3 4 5 6 7 8
  • Clinic receives bottles labeled only by
    numbers--assign in order
  • Unblinded studies important to keep next
    assignment secret
  • Problem with blocks within strata

27
Who to Study Principles for Inclusion/exclusion
  • Widest possible generalizability
  • Sufficiently high event rate (for power to be
    adequate)
  • Population in whom intervention likely to be
    effective
  • Ease of recruitment
  • Likelihood of compliance with treatment and FU

28
Explicit criteria for inclusion in a trial
  • Typically written as inclusion/exclusion
    criteria in protocol
  • The more explicit the better
  • Want centers or investigators to be consistent
  • Examples of exclusion decisions
  • 1. Women with heart disease vs.
  • Women with CABG surgery or documented MI
    by ecg (criteria) or enzymes (criteria)
  • 2. Users of estrogen vs
  • Use of ERT for more than 3 months over
    last 24 mos.

29
Valid reasons to exclude participants (Table
10.1)
  • Treatment would be unsafe
  • Adverse experience from active treatment
  • Risk of placebo (SOC)
  • Active treatment cannot/unlikely to be effective
  • No risk of outcome
  • Disease type unlikely to respond
  • Competing/interfering treatment (history of?)
  • Unlikely to adhere or follow-up
  • Practical problems

30
Design-a-trial Inclusion criteria options for
HRT
  • Study HRT and prevention of heart disease, 4
    years (HERS-like)
  • Women over age 50 years
  • Women over 60 years
  • Women over 75 years
  • Women with existing heart disease
  • Generalizability?
  • Feasible sample size?
  • Population amenable to intervention?
  • Logistic difficulties (recruitment? cost?
    adherence)

31
HERS inclusion options
  • HERS trial options (event rate)
  • Women over age 50 years (0.1/year)
  • Women over 60 years (0.5/year)
  • Women over 75 years (1/year)
  • Women with existing heart disease (4/year)

32
HERS inclusion options
  • HERS trial options (event rate) n required
  • Women over age 50 years (0.1/year) 55,000
  • Women over 60 years (0.5/year) 45,000
  • Women over 75 years (1/year) 34,000
  • Women with existing heart disease (4/year)
    3,000
  • (Choose last option as most practical common to
    generalize from secondary to primary prevention)

33
Exclusions/inclusions examples
  • Important impact on generalizability of both
    efficacy and safety
  • Example Fracture Intervention Trial (FIT)
  • Study of alendronate (amino-bisphosphonate) vs.
    placebo in women with low bone mass
  • 6459 women randomized to alendronate or placebo
  • Fracture endpoint
  • Upper GI and esophagitis concerns with
    bisphosphonates, esp. aminos
  • Who to exclude?

34
FIT inclusion/exclusion example
  • Alendronate studies (pre-FIT) excluded
  • Any history of upper GI events
  • Any (remote) history of ulcer
  • Esophagial problems, etc.
  • Reports of upper GI problems in clinical
    practice 5 to 20 of patients stop alendronate.
    Due to
  • Use by real world patients?
  • Use in real world?
  • Psychological--due to warnings about potential
    problems

35
Inclusion may impact effect of treatment
  • FIT reduction in hip fractures only among those
    with more severe osteoporosis
  • BL BMD T-score RR for hip fracture
  • - 2.0 to -1.6 0.98
  • - 2.5 to -2.0 1.05
  • Similar findings in statin trials higher
    lipids, more benefit

36
Alternative RCT designs Factorial design
  • Test of more than one treatment (vs. placebo)
  • Each drug alone and in combination
  • Allows multiple hypotheses in single trial
  • Efficient (sort of)
  • e.g., Physicians Health Study
  • Test aspirin MI
  • beta caratene cancer

37
Factorial design Physicians Heath Study
Placebo
Beta-carotene
Aspirin vs. no aspirin (MI)
Aspirin plus Beta-carotene
Aspirin
Beta carotene vs. no beta carotene (cancer)
38
Factorial design assumptions/limitations
  • Treatments do not interact
  • Effect of aspirin on MI is same with and without
    beta-carotene
  • Difficult to prove, requires large sample
  • Womens Health Initiative (MOAS, 600M )
  • Estrogen vs. placebo (all outcomes)
  • Calcium/Vit D vs. placebo (fractures)
  • Effect of calcium is the same/additive with and
    without estrogen..very shaky
  • Best used for unrelated RQs (both treatments and
    outcomes)

39
Cross-over designs
  • Both treatments are administered sequentially to
    all subjects
  • Subject serves as own control, random order
  • Compare treatment period vs. control period
  • Diuretic vs. beta blocker for blood pressure
  • 1/2 get d followed by bb
  • 1/2 get bb followed by d

40
Cross-over assumptions/limitations
  • Continuous variables only
  • No order effects
  • No carry-over effects
  • Need quick response and quick resolution
  • Wash out period helpful
  • More commonly used in phase I/II

41
Other special designs
  • Matched pairs randomized
  • One of each pair to each treatment
  • e.g., two eyes within an individual (one to each
    treatment)
  • Diabetic Retinopathy study

42
Other special designs
  • Cluster or grouped randomization
  • Randomize groups to treatments
  • Often useful especially for public health-type
    interventions

43
Other special designs (clusters)
  • Cluster or grouped randomization examples
  • medical practices to stop-smoking interventions
  • cities to public health risk factor reduction (5
    Cities Project)
  • baseball teams to chewing-tobacco intervention
  • Analysis complex
  • Sample size complex true n is between n
    clusters and n individuals (closer to clusters)

44
Previews of coming attractions
  • Blinding, interventions, controls (placebo vs.
    active)
  • Follow-up, compliance, analysis
  • Outcomes (efficacy and adverse effects)
  • Ethical issues (many!!)
  • Nuts and bolts
  • Multiple hypothesis testing
  • Working with the evil empire (drug cos)
About PowerShow.com