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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 – Selection of participants (Inclusion/exclusion) – Design options for trials • Dennis Black, PhD – [email protected] – 597-9112 Feedback from last year (observed)…. • Great course but….. HERS NEW Feedback from this year (predicted)…. • Great course but….. WHI NEW 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 – [email protected] – 597-9112 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 Examples of interventions • Drug vs. placebo • Low fat diet vs. regular diet • Exercise vs. CPP 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” Disadvantages of RCTs • Expensive • Time Consuming • Can only answer a single question So, why bother? 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) 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 Example: Estrogen Replacement Therapy in 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 Estrogen Replacement Therapy (ERT) Disease Effect on Risk* Coronary heart disease Osteoporosis (hip fx) Breast cancer Endometrial cancer Decrease by 40 - 80% Decrease by 30 - 60% Increase by 10 - 20% Increase by 700% Alzheimer’s Decrease by ? Pulmonary embolism & deep vein thrombosis Increase by 200 - 300% * From observational (case-control and cohort) studies Nurses Health Study (NEJM, 9/12/91) • Prospective cohort study, n = 48,470 • 337,000 person years of follow-up Estrogen Use Never Used Current user Former user Risk of Major Coronary Disease* 1.4 0.6 1.3 * Events per 1000 women-years of follow-up ** Relative Risk (95% CI) compared to never users Relative Risk** 1.0 0.56 (0.40-0.80) 0.83 (0.65-1.05) 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 Virtually all estrogen results are based 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 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 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! 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 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 WHI: Invasive Breast Cancer 3% 2% 1% years 1 2 3 4 5 6 7 WHI: Coronary Heart Disease years 1 2 3 4 5 6 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 Beta carotene: Clinical trial #1 The Alpha-Tocopherol, Beta Carotene Cancer Prevention Study RQ: Do vitamin E and beta-carotene prevent lung cancer in smokers? Design: Subjects: Intervention: (factorial) RCT, factorial, 6.1 years 29,133 smokers, Finnish men aged 50-69 1. Alpha-tocopherol, 50 mg/day vs. placebo 2. Beta-carotene, 20 mg/day vs. placebo Outcome: Lung cancer incidence Beta-carotene: Clinical Trial #1 Results 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 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: Subjects: Intervention: RCT, 4.0 years 18,314 men, smokers or asbestos workers Retinol (25,000 IU) and beta carotene (15 mg) vs. placebo Outcome: Lung cancer incidence Beta-carotene: Clinical Trial #2 Results 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 Beta Carotene RCTs • Beta carotene not recommended for cancer prevention • Similar story for beta carotenes and heart disease • RCT’s very useful Examples of major breakthroughs from RCTs • Protease inhibitors and AIDS • Aspirin and heart disease • Lipid lowering (statins) and heart disease 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) 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 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 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) Implementation of randomization • Less challenging for blinded studies • Sealed envelopes in fixed order at clinical sites • Alternatively: list of drug numbers – abab bbaa – 1234 5678 – Clinic receives bottles labeled only by numbers--assign in order • Unblinded studies: important to keep next assignment secret – Problem with blocks within strata 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 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. 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 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) 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) 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) 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? 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 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 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 NEW 0.79 (0.43, 1.44) 0.1 1 Relative Hazard (± 95% CI) 10 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) -2.0 – -2.5 1.03 (0.77, 1.39) < - 2.5 0.64 (0.50, 0.82) Overall 0.86 (0.73, 1.01) NEW 0.1 1 Relative Hazard (± 95% CI) 10 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 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 Factorial design: Physician’s Heath Study Placebo Aspirin Betacarotene Aspirin plus Betacarotene Beta carotene vs. no beta carotene (cancer) Aspirin vs. no aspirin (MI) 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 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 3-way factorial design of WHI HRT vs. no HRT NEW Low fat vs. regular diet Factorial design assumptions/limitations • Factorial designs are seductive but problematic • Best used for unrelated RQ’s (both treatments and outcomes) NEW 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 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 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 Other special designs • Cluster or grouped randomization –Randomize groups to treatments –Often useful especially for public healthtype interventions 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) Previews of coming attractions • Blinding, interventions, controls (placebo vs. active) (1/16) • Follow-up, compliance, etc. (1/23) • Outcomes (efficacy and adverse effects) • Ethical issues (many!!) • Nuts and bolts • Interim monitoring • Multi-center trials and working with the evil empire (drug cos)