Controlled Clinical Trials

Controlled Clinical Trials • 9 Sessions • Grady (course director), Black (lecturer), Cummings (lecturer) • Logistics….

TICR Professional Conduct StatementClarifications for this class I will maintain the highest standards of academic honesty I will neither give nor receive aid in examinations or assignments unless such cooperation is expressly permitted by the instructor I will conduct research in an unbiased manner, reports results truthfully, and credit ideas developed and work done by others I will not use answer keys from prior years I will write answers in my own words, and, when collaboration is permitted, acknowledge collaborators when answers are jointly formulated

Randomized Trials: Design, Subjects, and Randomization Dennis Black, PhD Dept. of Epidemiology and Biostatistics dblack@psg.ucsf.edu

Randomized Trials: the Evidence in “Evidence-Based” • Outline for today • Randomized trials: why bother? • Randomization • Plain vanilla • Other flavors • Selection of participants (Inclusion/exclusion) • Design options for trials • Vanilla • Factorial designs • Cross-over designs • Matched pairs • Cluster or group randomization

Randomized Controlled Trial (RCT) An experiment in which subjects are randomly allocated into groups, usually called study and control groups, to receive or not to receive an experimental preventive or therapeutic procedure, maneuver, or intervention. The results are assessed by rigorous comparison of rates of disease, death, recovery, or other appropriate outcome in the study and control groups, respectively.

Number of randomized trials published* * Based on Medline search restricted to “Randomized clinical trials”

Reasons to NOT do RCTs • Expensive: total costs typically in $ millions (maybe be as high as $200-$500 million) • Time Consuming: typically years • Can only answer a single question • May not apply to most patients in practice • May not be practical • Generally very difficult to get funded • Time consuming, organizationally complex So, why bother?

Alternatives to RCTs(30 second Epi. Course) RQ: Does Vitamin E prevent prostrate cancer? 1. Case-control studies • Compare those with and without disease 2. Cross-sectional studies • Compare rates of risk factor among those with and without disease at a single time point. 3. Cohort studies (prospective) • Identify those with and without risk factor • Follow forward in time to see who gets disease • Case-control, cross-sectional, and cohort studies are observational (not experimental)

Reasons for doing RCTs • Only study design that can prove causation • Most influential to clinical practice • Strongest evidence in “evidence-based” • Required by FDA (and others) for new drugs and some devices • Required more and more by payers

Vitamin E, C and Selenium on Prostate Cancer in men (JAMA, 1/09) • 2 very large studies published together • SELECT study (Lippman) is largest cancer prevention trial ever performed (n=35,533) • Also Gaziano study of prostate cancer

Vitamin E, C and Selenium on Prostate Cancer in men (JAMA 1/09) • These studies have it all and are great examples: • Interesting/popular research questions: Vit C and E for cancer prevention • Surprising and impactful results • Large studies • Early stopping • Multiple endpoints • Subgroup analyses • Factorial design • To be used throughout course (D. Black)

Vitamin E, C and Selenium on Prostate Cancer: Background • 1994: ATBC (alpha-tocopherol/beta carotene) trial showed 35% reduction in P.Ca in men taking vitamin e (post-hoc analysis) • 1996: 65% reduction in prostate cancer with selenium (secondary analysis) • Positive results in observational studies of anti-oxidant use and cancer • Hope/belief: prostate cancer could be prevented by anti-oxidants • Many people taking anti-oxidants

SELECT study(Factorial design, 35,533 men) (JAMA, 1/7/09) Placebo Selenium Vitamin E vs. No Vitamin E Selenium + Vitamin E Vit. E Selenium vs. no selenium • Selection: • Men • PSA <4 ng/ml • No P.Ca from • DR exam

SELECT studyResults for Prostate Ca (Primary endpoint)

SELECT Trial: Factoids • Non-significant increased risk for prostate cancer in vitamin E vs. placebo • Planned for 7 years, stopped early (“no possibility of benefit to planned degree”) • No benefit for other cancer endpoints • Interesting discussion (see Comments) of potential explanations of discrepancy with earlier results • Lots of other examples of “popular” treatments proven not beneficial or harmful in RCT’s

SELECT Trial: Impact on patient care? Editorial in JAMA • Physicians should not recommend…vitamin e--or any other anti-oxidant supplements– to their patients”

Vitamin E, C and Selenium on Prostate Cancer in men (JAMA 1/09)

Example: Estrogen Replacement Therapyin post-menopausal women • Important therapeutic question • Applies to 30 -50 million women in US • Prempro (estrogen/progestin combo)may have been most prescribed drug in US in 1990’s • Potentially huge impact on public health • Complex: ERT effects multiple diseases

Estrogen Replacement Therapy (ERT):Results from Observational Studies ~ 1996 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 1996: 100’s of observational studies with consistent results…. But no randomized trials at that time

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

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

As of 1997, virtually all estrogen results werebased 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) • First major RCT of estrogen (started 1992) • 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 Coord center • Funding by Wyeth-Ayerst (post-NIH refusal) • Results: JAMA: 8/98

HERS major outcome: No effect of HRT on heart disease (among women with existing CHD) Endpoint Placebo HRT RR P New CHD 176 172 0.99 0.91 Conclusion: Randomized trials can lead to big surprises!

Women’s Health Initiative HRT study* (7/10/02) • Randomized trial (2) in wide range of women (w and w/o CHD) • 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 E + P (stopped early 7/02): CHD 29% increase with HRT years1 2 3 4 5 6

HERS/WHI Trials: Take Home message • RCT’s can give definitive answers to clinical questions • HRT use has dramatically declined • Observational studies can be wrong. • Meta-analysis of observational studies can be wrong. • What went wrong with observational studies of HRT? • Take home • Confounders (known + unknown) are impossible to fully identify and control for in non-randomized studies

HERS/WHI Trials: Take Home • RCT’s can give definitive answers to clinical questions • HRT use has dramatically declined • Observational studies can be wrong. • Meta-analysis of observational studies can be wrong. • What went wrong with observational studies of HRT? • Take home • Confounders (known + unknown) are impossible to fully identify and control for in non-randomized studies HRT * Sort of

“Epidemiology—Is It Time to Call It a Day? --Editors of The International Journal of Epi

Many non-drug trials… • Surgical techniques • Behavioral intervention • Diet

What to eat this morning? Vs. Vs. Want to make an evidence-based decision..

RCT of 4 Popular Weight Loss Programs • Compare 4 diets 1. Atkins (low carbohydrate) 2. Weight Watchers (low calorie/portion size) 3. Zone (high protein/low-glycemic load) 4. Ornish (very low fat) Vs. JAMA 1/5/05

Diet study: Design N =160 Randomize to 1 of 4 diets Follow for 12 months Endpoints: • Weight loss • Heart disease risk factors (cholesterol, BP, triglycerides) How different from selenium prostate CA? JAMA 1/5/05

Diet study: Results at 12 months Year Atkins Zone Weight Ornish watchers . Weight (kg) -3.9 -4.9 -4.6 -6.6 LDL (mg/dL) -13.5 -18.1 -14.2 -25.2 SBP (mm/Hg) 0.3 2.1 -4.1 0.9 Small study, continuous endpoints JAMA 1/5/05

Diet study: Summary • All diets led to modest reductions in weight and cardiac risk factors • Poor compliance for all diets, especially Atkins and Ornish • Those who adhered well had better results JAMA 1/5/05

Examples of major positive breakthroughs from RCTs • Protease inhibitors and AIDS • Aspirin and heart disease • Lipid lowering (statins) and heart disease • Bisphosphonates and fracture risk Many of examples of trials with huge impact on clinical practice and public health

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) *Hulley et al, Designing Clinical Research

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 peeking, altering order of participants, etc) • Simple randomization • Low tech • High tech

Randomization Want balance in “Table 1” Lippman et. al

Randomization:The Basics Cannot assure equal numbers per group or balance

Randomized Permuted Blocks • Blocking: equal after each 4 (or n) assignments • e.g., block size of 4, treatments a and b abab aabb abba baba bbaa baab • Randomly choose blocks • Assure relatively equal number of ppts. to each treatment • Disadvantages of blocking (in unblinded trials) • Size of block: 2 treatments--4 or 6 • Very commonly used

Randomized Blocks to Balance Prognostic Variables • Stratified permuted blocks • Blocks within strata of prognostic variable • e.g., Prostrate cancer (PSA < 5 vs. PSA > 5) • Stratum PSA < 5: aabb baba … PSA > 5: 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

Adaptive Randomization • Probability of assignment to each treatment depends on previous randomizations

Implementation of randomization #001 #002 #003 • Less challenging for blinded studies • 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 • Sealed envelopes in fixed order at clinical sites • Unblinded studies: important to keep next assignment secret • Problem with randomized blocks

Randomization: Summary • Key element of clinical trials (Rct’s) • Insure balance for all factors at baseline • Not really very complicated (usually)

Selection of Patients

Who to Study: Factors to Consider for Inclusion/exclusion • Widest possible generalizability • Sufficiently high event rate (for power to be adequate) • Population in whom intervention likely to be effective and safe • Ease of recruitment • Likelihood of compliance with treatment and F/U

Who to Study (eg. CHD study): Principles for Inclusion/exclusion Broad eligibility ------------------- Narrow elig. eg.men or women >50men > 70 Recruitment: easy difficult Generalizability: wide narrow Sample size: large small

Valid reasons to exclude participants (Table 10.1, Hulley et. al.) • Treatment would be unsafe • Adverse experience from active treatment • “Risk” of placebo • 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

Controlled Clinical Trials