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Randomized Trials

Randomized Trials. 9 Sessions Grady (course director), Black (lecturer), Cummings (lecturer) Mechanics Turn in homework to Olivia Romero prior to each session. NEW. Randomized Trials: the Evidence in “Evidence-Based”. Today Randomized trials: why bother? Randomization

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Randomized Trials

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  1. Randomized Trials • 9 Sessions • Grady (course director), Black (lecturer), Cummings (lecturer) • Mechanics • Turn in homework to Olivia Romero prior to each session NEW

  2. 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@psg.ucsf.edu • 597-9112

  3. Feedback from last year (observed)…. HERS • Great course but….. NEW

  4. Feedback from this year (predicted)…. WHI • Great course but….. NEW

  5. 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@psg.ucsf.edu • 597-9112

  6. 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

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

  8. 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”

  9. Disadvantages of RCTs • Expensive • Time Consuming • Can only answer a single question So, why bother?

  10. 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)

  11. 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

  12. 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

  13. Estrogen Replacement Therapy (ERT) Disease Effect on Risk* Coronary heart disease Decrease by 40 - 80%Osteoporosis (hip fx) Decrease by 30 - 60%Breast cancer Increase by 10 - 20%Endometrial cancer Increase by 700% Alzheimer’s Decrease by ? Pulmonary embolism & Increase by 200 - 300%deep vein thrombosis * From observational (case-control and cohort) studies

  14. 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

  15. Meta-analysis of ERT, Published ~4/10/97 “Benefits (for CHD, osteoporosis) outweigh risks (breast cancer) and side effects…All post-menopausal women should be taking ERT”* * CNN, 4/10/97

  16. 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

  17. 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, < 80 years, mean age 67 • 20 clinical centers in U.S./UCSF Coordinating center • Funding by Wyeth-Ayerst (post-NIH refusal) • Expected results???? • Real results: JAMA: 8/98

  18. 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!

  19. Women’s Health Initiative HRT study* (7/10/02) • Randomized trial (2) • 16,608 women with uterus (ERT + progestin vs. placebo) • ~11,000 women without uterus (ERT alone vs. placebo) • Ages 50-79, mean age 64 • Represent broad range of U.S. women • 40 clinical centers • Follow-up planned for 8.5 years, to end in 2005 * only one component of WHI..more later

  20. WHI HRT study: 7/10/02 • Combination therapy arm stopped early (3 years) • Mean 5.2 years of follow-up • Overall, health risks outweigh benefits • Significant increased risk for invasive breast cancer HRT users

  21. WHI: Invasive Breast Cancer 3% 2% 1% years1 2 3 4 5 6 7

  22. WHI: Coronary Heart Disease years1 2 3 4 5 6

  23. Other surprises:Beta 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

  24. 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

  25. Beta-carotene: Clinical Trial #1Results 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 Incidence per 10,000 person years

  26. 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

  27. 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

  28. Beta Carotene RCTs • Beta carotene not recommended for cancer prevention • Similar story for beta carotenes and heart disease • RCT’s very useful

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

  30. 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)

  31. Randomization • Key element of RCT’s • 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

  32. 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

  33. 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)

  34. 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

  35. 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

  36. 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.

  37. 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

  38. 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)

  39. 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)

  40. 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)

  41. 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?

  42. 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

  43. Inclusion may impact effect of treatment • FIT: Included women with baseline BMD T-score below -1.6 (only those below -2.5 officially osteoporotic) • Reduction in hip fractures only among those with more severe osteoporosis • Similar findings in statin trials: higher lipids, more benefit

  44. Effect of alendronate on hip fx depends on baseline hip BMD Baseline BMD T-score -1.6 – -2.5 1.84 (0.7, 5.4) 0.44 (0.18, 0.97) < - 2.5 Overall 0.79 (0.43, 1.44) 0.1 1 10 NEW Relative Hazard (± 95% CI)

  45. Effect of alendronate on non-spine fx depends on baseline hip BMD Baseline BMD T-score -1.6 – -2.0 1.14 (0.82, 1.60) 1.03 (0.77, 1.39) -2.0 – -2.5 < - 2.5 0.64 (0.50, 0.82) Overall 0.86 (0.73, 1.01) 0.1 1 10 NEW Relative Hazard (± 95% CI)

  46. Inclusion, exclusion, Conclusion • Many factors to balance in deciding who to include • Generally not a clear cut or single correct decision • Many academics have simplistic understanding of issues NEW

  47. 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., Physician’s Health Study • Test aspirin ==> MI • beta caratene ==> cancer

  48. Factorial design: Physician’s Heath Study Placebo Beta-carotene Aspirin vs. no aspirin (MI) Aspirin plus Beta-carotene Aspirin Beta carotene vs. no beta carotene (cancer)

  49. Factorial design assumptions/limitations • Treatments do not interact • Effect of aspirin on MI is same with and without beta-carotene • Must test for interaction of treatments • Difficult to prove, requires large sample

  50. Factorial design assumptions/limitations • Women’s Health Initiative (MOAS, $600M +) • Estrogen vs. placebo (all outcomes) • Calcium/Vit D vs. placebo (fractures) • Low fat vs. regular diet (breast cancer) • Effect of calcium on fractures is the same/additive with and without estrogen.. • very shaky NEW

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