2/27/03 Outline2/27/03 Outline

• Part I: Misc. Statistical IssuesPart I: Misc. Statistical Issues– Multiple comparisons in clinical trialsMultiple comparisons in clinical trials

– Multiple endpointsMultiple endpoints

– SubgroupsSubgroups

– Adverse experience categorizationAdverse experience categorization

– Multivariate adjustmentMultivariate adjustment

• Part II: Multi-center trials and working with industry Part II: Multi-center trials and working with industry (Cummings left over)(Cummings left over)

Multiple comparisonsMultiple comparisons

• The general problemThe general problem– Each statistical test has a 5% chance of Type I errorEach statistical test has a 5% chance of Type I error

– We are wrong 1 time out of 20We are wrong 1 time out of 20

– Easy to come up with spurious resultsEasy to come up with spurious results

• Take a worthless drug (placebo 2) compare to placebo 1Take a worthless drug (placebo 2) compare to placebo 1– 1 study: P(type I error)= 5%1 study: P(type I error)= 5%

– 2 studies: P(1 or 2 type I errors)= almost 10%2 studies: P(1 or 2 type I errors)= almost 10%

– 20 studies: P(at least one significant)=64%20 studies: P(at least one significant)=64%

• Publication biasPublication bias

Multiple comparisons: solutions?Multiple comparisons: solutions?

• BonferroniBonferroni– Divide overall p-value by number of testsDivide overall p-value by number of tests

– Unacceptable losses of powerUnacceptable losses of power

• Use common sense/BayesianUse common sense/Bayesian– Does result make sense?Does result make sense?

– Biologic plausibilityBiologic plausibility

– Is result supported by previous data?Is result supported by previous data?

– Was analysis defined Was analysis defined aprioriapriori??

• Examples of problem in clinical trialsExamples of problem in clinical trials

Multiple comparisons in RCT’s are pervasiveMultiple comparisons in RCT’s are pervasive

• Monitoring of trials: look at results as they accumulateMonitoring of trials: look at results as they accumulate– Lots of statistical machinery Lots of statistical machinery

• Multiple endpoints in a trialMultiple endpoints in a trial– Primary endpoint: “all fractures” but also found significant Primary endpoint: “all fractures” but also found significant

reductions in hip fracturesreductions in hip fractures

– Primary endpoint: fractures, significant reductions in breast Primary endpoint: fractures, significant reductions in breast cancercancer

– SafetySafety

• Subgroup analysesSubgroup analyses

• Multivariate analysis (adjustment) for BL covariatesMultivariate analysis (adjustment) for BL covariates

No Adjustment for Multiple Comparisons?No Adjustment for Multiple Comparisons?

• Rothman, 1990Rothman, 1990– Adjustments for multiple comparisons lead to type II Adjustments for multiple comparisons lead to type II

errorserrors

– A policy of not making adjustments is preferableA policy of not making adjustments is preferable

• “ “ Scientists should not be so reluctant to explore leads Scientists should not be so reluctant to explore leads that may turn out to be wrong that they penalize that may turn out to be wrong that they penalize themselves for missing possibly important findings”themselves for missing possibly important findings”

Multiple Endpoints: Multiple Endpoints: Making a Mountain Out of a MolehillMaking a Mountain Out of a Molehill

• Multiple Outcomes of Raloxifene Evaluation (MORE) trialMultiple Outcomes of Raloxifene Evaluation (MORE) trial

• Main outcome: vertebral fracturesMain outcome: vertebral fractures

• Secondary outcome: non-vertebral fracturesSecondary outcome: non-vertebral fractures– Main osteoporotic subtypes: hip, wristMain osteoporotic subtypes: hip, wrist

• Overall, no effect of raloxifene on NV fracturesOverall, no effect of raloxifene on NV fractures

• Looked at 14 subtypes of fracturesLooked at 14 subtypes of fractures

• One significant: ankle. Wanted to title paper: One significant: ankle. Wanted to title paper: “Raloxifene reduces ankle fractures”“Raloxifene reduces ankle fractures”

Multiple Endpoints in PEPI: Multiple Endpoints in PEPI: Strict Bonferonni RuleStrict Bonferonni Rule

• Post-menopausal Estrogen/Progesterone Intervention Post-menopausal Estrogen/Progesterone Intervention PEPI (website)PEPI (website)

• 4 treatment groups, several primary outcomes: all 4 treatment groups, several primary outcomes: all continuouscontinuous

• Adjust all p-values to account for multiple comparisonsAdjust all p-values to account for multiple comparisons– Multiple primary endpoints (4)Multiple primary endpoints (4)

– Within each endpoint, adjust for 4 treatmentsWithin each endpoint, adjust for 4 treatments

Multiple endpointsMultiple endpoints

• Often many ways to slice the outcome pieOften many ways to slice the outcome pie– Different subgroups of endpointsDifferent subgroups of endpoints

– Fractures: all, leg, arm, rib, etc. (MORE)Fractures: all, leg, arm, rib, etc. (MORE)

– Multiple comparisons problemsMultiple comparisons problems

• Some solutionsSome solutions– Very explicit predefinition of endpointsVery explicit predefinition of endpoints

– Limit number of endpointsLimit number of endpoints

– FDA: single endpoint onlyFDA: single endpoint only

SubgroupsSubgroups

• After primary analysis, want to look at subgroupsAfter primary analysis, want to look at subgroups

• Does effectiveness vary by subgroupDoes effectiveness vary by subgroup

• If drug effective, is it more effective in some If drug effective, is it more effective in some populations?populations?

• If results overall show no effect, does drug work in If results overall show no effect, does drug work in subgroup of participants?subgroup of participants?

• Are adverse effects concentrated in some subgroups?Are adverse effects concentrated in some subgroups?

Example: Efficacy of alendronateExample: Efficacy of alendronate

• FIT II: Women with BMD T-score < -1.6 FIT II: Women with BMD T-score < -1.6 (osteopenic--only 1/3 osteoporotic)(osteopenic--only 1/3 osteoporotic)

– Women without existing vertebral fractures (2)Women without existing vertebral fractures (2)

• Overall results: 14% reduction, p=.07Overall results: 14% reduction, p=.07

• WimpyWimpy

RR for clinical fracture of alendronateRR for clinical fracture of alendronate(FIT II, Cummings, JAMA 1999) (FIT II, Cummings, JAMA 1999)

00

11

1.51.5

OverallOverall

0.860.86(0.73 - 1.01)(0.73 - 1.01)

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isk P=0.07P=0.07P=0.07P=0.07

RR for clinical fracture of alendronate RR for clinical fracture of alendronate by baseline BMD groupsby baseline BMD groups

00

11

1.51.5

Baseline Femoral Neck BMD, by T-scoreBaseline Femoral Neck BMD, by T-score

OverallOverall T < -2.5T < -2.5 -2.5 < T < -2.0-2.5 < T < -2.0 T > -2.0T > -2.0

0.860.86(0.73 - 1.01)(0.73 - 1.01)

0.640.64(0.50 - 0.82)(0.50 - 0.82)

1.031.03

(0.77 - 1.39)(0.77 - 1.39)

1.141.14 (0.82 - 1.60)(0.82 - 1.60)

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What to Do With an What to Do With an Unexpected Subgroup FindingUnexpected Subgroup Finding

• Is this a real finding? (not really specified Is this a real finding? (not really specified apriori)apriori)

• Has this been previously observed?Has this been previously observed?– Increase prior probabilityIncrease prior probability

• Ways to verifyWays to verify– Examine for other similar subgrouping variables (BMD at hip, Examine for other similar subgrouping variables (BMD at hip,

spine, radius)spine, radius)

– Examine for other similar endpoints (hip fractures, etc.)Examine for other similar endpoints (hip fractures, etc.)

– Most important: look at other trials, if possible and availableMost important: look at other trials, if possible and available

– Examine biologic plausibilityExamine biologic plausibility

Effect of alendronate Effect of alendronate on hip fxon hip fx depends on baseline depends on baseline hip BMDhip BMD

Baseline BMD T-scoreBaseline BMD T-score

OverallOverall

< - 2.5< - 2.5

-1.6 – -2.5-1.6 – -2.5

0.10.1 11 1010Relative Hazard (± 95% CI)Relative Hazard (± 95% CI)

0.79 (0.43, 1.44)0.79 (0.43, 1.44)

0.44 (0.18, 0.97)0.44 (0.18, 0.97)

1.84 (0.7, 5.4)1.84 (0.7, 5.4)

Fosamax International Trial (FOSIT)Fosamax International Trial (FOSIT)

• 1908 women, 34 countries1908 women, 34 countries

• Lumbar spine BMD T-score < -2Lumbar spine BMD T-score < -2

• Alendronate (10 mg) vs. placeboAlendronate (10 mg) vs. placebo

• One year follow-upOne year follow-up

• BMD main endpointBMD main endpoint

• 47% reduction in all clinical fractures (p<.05)47% reduction in all clinical fractures (p<.05)

FOSIT: Relative risk alendronate vs. FOSIT: Relative risk alendronate vs. placebo within BMD subgroupsplacebo within BMD subgroups

Baseline hip BMD T N RR* 95% CI

Overall 1908 0.53 (0.3,0.9)

> -2 955 1.2 (0.5, 2.9)

-2 to –2..5 279 0.32 (0.07,1.5)

< -2.5 674 0.26 (0.1,0.7)

Subgroup analysis in HERSSubgroup analysis in HERS

• Overall no effect of HRT or perhaps harm in year 1Overall no effect of HRT or perhaps harm in year 1

• Is there a subgroup who benefit?Is there a subgroup who benefit?

• Is there subgroup with significant harm?Is there subgroup with significant harm?

• Look at relative hazard (RH) within subgroups defined by Look at relative hazard (RH) within subgroups defined by baseline variablesbaseline variables

– Medication use at baselineMedication use at baseline

– Prior diseasePrior disease

– Health habitsHealth habits

– Compare RH in those with and without risk factorCompare RH in those with and without risk factor• RH in those using beta blockers compared to those not usingRH in those using beta blockers compared to those not using

• RH > 1 ==> harmRH > 1 ==> harm

• Get p-value for significance of difference of RH in those w and withoutGet p-value for significance of difference of RH in those w and without

HERS: 4 years of HRT increased HERS: 4 years of HRT increased then decreased CHD Eventsthen decreased CHD Events

YearYear E + PE + P PlaceboPlacebo RHRH p-valuep-value

11 5757 3838 1.51.5 .04.04

22 4747 4848 1.01.0 1.01.0

33 3535 4141 0.90.9 .6.6

4 + 54 + 5 3333 4949 0.70.7 .07.07

> 5> 5 ??????

P for trend = 0.009P for trend = 0.009

Subgroups: the final frontier in HERSSubgroups: the final frontier in HERS

•

Relative hazard (E vs. placebo)Relative hazard (E vs. placebo)

Subgroup Within AmongSubgroup Within Among

Subgroup N (%) Subgroup Others p*Subgroup N (%) Subgroup Others p*

history of smoking 1712 (62) 1.01 3.39history of smoking 1712 (62) 1.01 3.39 .01 .01

current smoker 360 (13) 0.55 1.92 .03 current smoker 360 (13) 0.55 1.92 .03

digitalis use 275 (10) 4.98 1.26 .04 digitalis use 275 (10) 4.98 1.26 .04

>= 3 live births 1616 (58) 1.09 2.72 .04 >= 3 live births 1616 (58) 1.09 2.72 .04

lives alone 775 (28) 2.97 1.14 .05 lives alone 775 (28) 2.97 1.14 .05

prior mi by chart review 1409 (51) 2.14 0.93 .05 prior mi by chart review 1409 (51) 2.14 0.93 .05

beta-blocker use 899 (33) 2.89 1.15 .06 beta-blocker use 899 (33) 2.89 1.15 .06

age >= 70 at randomization 1019 (37) 2.65 1.14 .06age >= 70 at randomization 1019 (37) 2.65 1.14 .06

* Statistical significance of interaction* Statistical significance of interaction

Lots of subgroups were analyzed in HERSLots of subgroups were analyzed in HERS

• history of smoking (at rv) 1712 (62) 1.01 3.39 0.30 .01 history of smoking (at rv) 1712 (62) 1.01 3.39 0.30 .01 • current smoker (at rv) 360 (13) 0.55 1.92 0.29 .03 current smoker (at rv) 360 (13) 0.55 1.92 0.29 .03 • digitalis use (at rv) 275 (10) 4.98 1.26 3.96 .04 digitalis use (at rv) 275 (10) 4.98 1.26 3.96 .04 • >= 3 live births 1616 (58) 1.09 2.72 0.40 .04 >= 3 live births 1616 (58) 1.09 2.72 0.40 .04 • lives alone (at rv) 775 (28) 2.97 1.14 2.60 .05 lives alone (at rv) 775 (28) 2.97 1.14 2.60 .05 • prior mi by chart review (cr) 1409 (51) 2.14 0.93 2.30 .05 prior mi by chart review (cr) 1409 (51) 2.14 0.93 2.30 .05 • beta-blocker use (at rv) 899 (33) 2.89 1.15 2.51 .06 beta-blocker use (at rv) 899 (33) 2.89 1.15 2.51 .06 • age >= 70 at randomization 1019 (37) 2.65 1.14 2.32 .06 age >= 70 at randomization 1019 (37) 2.65 1.14 2.32 .06 • prior mi in most distant tertile 447 (16) 2.64 0.93 2.82 .07 prior mi in most distant tertile 447 (16) 2.64 0.93 2.82 .07 • walk 10m or in exercise program (at rv) 1770 (64) 2.35 1.11 2.12 .08 walk 10m or in exercise program (at rv) 1770 (64) 2.35 1.11 2.12 .08 • prior ptca by chart review (cr) 1189 (43) 0.92 1.98 0.46 .08 prior ptca by chart review (cr) 1189 (43) 0.92 1.98 0.46 .08 • prior mi within 2 years 420 (15) 3.20 1.28 2.50 .11 prior mi within 2 years 420 (15) 3.20 1.28 2.50 .11 • tg > median (at rv) 1377 (50) 2.02 1.05 1.93 .12 tg > median (at rv) 1377 (50) 2.02 1.05 1.93 .12 • rales in the lungs (at rv) 80 ( 3) 0.43 1.65 0.26 .13 rales in the lungs (at rv) 80 ( 3) 0.43 1.65 0.26 .13 • digitalis or ace-inhibitor use (at rv) 653 (24) 2.33 1.24 1.88 .16 digitalis or ace-inhibitor use (at rv) 653 (24) 2.33 1.24 1.88 .16 • previous ert for >= 12 months 302 (11) 4.19 1.41 2.98 .18 previous ert for >= 12 months 302 (11) 4.19 1.41 2.98 .18 • serious medical conditions 1028 (37) 1.05 1.81 0.58 .21 serious medical conditions 1028 (37) 1.05 1.81 0.58 .21 • age >= 53 at lmp 578 (21) 3.19 1.38 2.31 .23 age >= 53 at lmp 578 (21) 3.19 1.38 2.31 .23 • hdl > median (at rv) 1315 (48) 1.18 1.95 0.61 .24 hdl > median (at rv) 1315 (48) 1.18 1.95 0.61 .24 • lp(a) > median (at rv) 1378 (50) 1.26 2.08 0.60 .25 lp(a) > median (at rv) 1378 (50) 1.26 2.08 0.60 .25 • use of non-statin llm (at rv) 420 (15) 0.89 1.69 0.52 .25 use of non-statin llm (at rv) 420 (15) 0.89 1.69 0.52 .25 • married (at rv) 1588 (57) 1.26 1.98 0.64 .29 married (at rv) 1588 (57) 1.26 1.98 0.64 .29 • lvef <= 40% 178 ( 6) 2.16 1.01 2.13 .31 lvef <= 40% 178 ( 6) 2.16 1.01 2.13 .31 • prior mi within 4 years 765 (28) 2.07 1.32 1.57 .32 prior mi within 4 years 765 (28) 2.07 1.32 1.57 .32 • previous ert use for >= 1 year 327 (12) 2.86 1.41 2.03 .32 previous ert use for >= 1 year 327 (12) 2.86 1.41 2.03 .32 • prior mi within 1 year 194 ( 7) 2.88 1.43 2.02 .33 prior mi within 1 year 194 ( 7) 2.88 1.43 2.02 .33 • chest pain (at rv) 982 (36) 1.25 1.88 0.67 .33 chest pain (at rv) 982 (36) 1.25 1.88 0.67 .33 • dbp >= 90 mmhg (at rv) 149 ( 5) 0.91 1.62 0.56 .35 dbp >= 90 mmhg (at rv) 149 ( 5) 0.91 1.62 0.56 .35 • prior ptca within 1 year 206 ( 7) 3.94 1.46 2.71 .38 prior ptca within 1 year 206 ( 7) 3.94 1.46 2.71 .38 • prior mi within 3 years 612 (22) 2.05 1.37 1.50 .40 prior mi within 3 years 612 (22) 2.05 1.37 1.50 .40 • prior ptca within 4 years 838 (30) 1.15 1.70 0.68 .40 prior ptca within 4 years 838 (30) 1.15 1.70 0.68 .40 • use of any llm (at rv) 1296 (47) 1.23 1.76 0.70 .40 use of any llm (at rv) 1296 (47) 1.23 1.76 0.70 .40 • diuretic use (at rv) 775 (28) 1.89 1.33 1.42 .41 diuretic use (at rv) 775 (28) 1.89 1.33 1.42 .41 • signs and symptoms of chf (at rv) 118 ( 4) 0.94 1.60 0.58 .42 signs and symptoms of chf (at rv) 118 ( 4) 0.94 1.60 0.58 .42 • ace inhibitor use (at rv) 483 (17) 2.05 1.40 1.46 .44 ace inhibitor use (at rv) 483 (17) 2.05 1.40 1.46 .44 • total cholesterol > median (at rv) 1377 (50) 1.32 1.80 0.74 .47 total cholesterol > median (at rv) 1377 (50) 1.32 1.80 0.74 .47 • l-thyroxine use (at rv) 414 (15) 2.29 1.43 1.60 .47 l-thyroxine use (at rv) 414 (15) 2.29 1.43 1.60 .47 • poor/fair self-rated health (at rv) 665 (24) 1.30 1.72 0.76 .51 poor/fair self-rated health (at rv) 665 (24) 1.30 1.72 0.76 .51 • heart murmur (at rv) 540 (20) 1.89 1.42 1.34 .53 heart murmur (at rv) 540 (20) 1.89 1.42 1.34 .53 • sbp >= 140 mmhg (at rv) 1051 (38) 1.37 1.72 0.80 .59 sbp >= 140 mmhg (at rv) 1051 (38) 1.37 1.72 0.80 .59 • prior ptca within 3 years 695 (25) 1.27 1.61 0.78 .62 prior ptca within 3 years 695 (25) 1.27 1.61 0.78 .62 • s3 heart sounds (at rv) 19 ( 1) 2.74 1.50 1.82 .63 s3 heart sounds (at rv) 19 ( 1) 2.74 1.50 1.82 .63 • htn by physical exam (at rv) 557 (20) 1.32 1.62 0.81 .64 htn by physical exam (at rv) 557 (20) 1.32 1.62 0.81 .64 • >= 2 severely obstructed main vessels 1312 (47) 1.53 1.26 1.22 .69 >= 2 severely obstructed main vessels 1312 (47) 1.53 1.26 1.22 .69 • statin use (at rv) 1004 (36) 1.34 1.59 0.84 .71 statin use (at rv) 1004 (36) 1.34 1.59 0.84 .71 • have you ever been pregnant 2564 (93) 1.55 1.15 1.35 .72 have you ever been pregnant 2564 (93) 1.55 1.15 1.35 .72 • calcium-channel blocker (at rv) 1511 (55) 1.61 1.38 1.17 .73 calcium-channel blocker (at rv) 1511 (55) 1.61 1.38 1.17 .73 • previous hrt for >= least 12 months 132 ( 5) 1.24 1.60 0.78 .77 previous hrt for >= least 12 months 132 ( 5) 1.24 1.60 0.78 .77 • ldl > median (at rv) 1373 (50) 1.44 1.63 0.89 .77 ldl > median (at rv) 1373 (50) 1.44 1.63 0.89 .77 • prior ptca within 2 years 475 (17) 1.35 1.56 0.87 .81 prior ptca within 2 years 475 (17) 1.35 1.56 0.87 .81 • baseline left bundle branch block 212 ( 8) 1.31 1.55 0.85 .82 baseline left bundle branch block 212 ( 8) 1.31 1.55 0.85 .82 • white 2451 (89) 1.48 1.62 0.92 .88 white 2451 (89) 1.48 1.62 0.92 .88 • ever told you had diabetes 634 (23) 1.48 1.53 0.97 .94 ever told you had diabetes 634 (23) 1.48 1.53 0.97 .94 • aspirin use (at rv) 2183 (79) 1.51 1.56 0.97 .95 aspirin use (at rv) 2183 (79) 1.51 1.56 0.97 .95 • any alcohol consumption (at rv) 1081 (39) 1.54 1.57 0.98 .97 any alcohol consumption (at rv) 1081 (39) 1.54 1.57 0.98 .97 • gallstones or gallbladder dis. 633 (23) 1.55 1.52 1.02 .97 gallstones or gallbladder dis. 633 (23) 1.55 1.52 1.02 .97 •

baseline atrial fibrillation/flutter 33 ( 1) - 1.50baseline atrial fibrillation/flutter 33 ( 1) - 1.50 - - - -

Total subgroups examined: 102Total subgroups examined: 102

Total subgroups with p< .05: 6Total subgroups with p< .05: 6

Total subgroups examined: 102Total subgroups examined: 102

Total subgroups with p< .05: 6Total subgroups with p< .05: 6

Subgroups: conclusionsSubgroups: conclusions

• Subgroups are full of statistical problemsSubgroups are full of statistical problems– Multiple comparisons may lead to erroneous conclusionsMultiple comparisons may lead to erroneous conclusions

• Limited power in for subgroup analysesLimited power in for subgroup analyses

• Subgroups based on baseline variables are less badSubgroups based on baseline variables are less bad

• Subgroups based on post-randomization variables are Subgroups based on post-randomization variables are more problematicmore problematic

Safety assessmentSafety assessment

• Often many categories (FIT: 200 or more)Often many categories (FIT: 200 or more)

• Some are rareSome are rare

• Ex: Risedronate and lung cancerEx: Risedronate and lung cancer

• How to control for spurious findings?How to control for spurious findings?

• P-values almost meaninglessP-values almost meaningless

Categorization of Adverse ExperiencesCategorization of Adverse Experiences

• AE’s collected as “open text”AE’s collected as “open text”

• Need to categorize and compare by treatmentNeed to categorize and compare by treatment

• Options:Options:– Many categories: few events per treatment, low powerMany categories: few events per treatment, low power

– Few categories: heterogenuous, may miss important Few categories: heterogenuous, may miss important effectseffects

– No correct solutionNo correct solution

• MeDRA codingMeDRA coding– ~15,000 standard clinical terms (“specific terms”)~15,000 standard clinical terms (“specific terms”)

– Various levels of groupingVarious levels of grouping

– May be non-sensical in some situationsMay be non-sensical in some situations

Categorization of Adverse Experiences:Categorization of Adverse Experiences:Sellmeyer solutionSellmeyer solution

PATH StudyAECategories: AE Categories (Data as of: 02/26/2003)

UCSF General Term UCSF Group Term Adverse event specify

CONSTITUTIONAL ARTHRALGIA AM STIFFNESS

ANKLE PAIN

ANKLE PAIN BILATERAL

ANKLE PAIN LEFT

ANKLE SORENESS

ANKLE STIFFNESS

ARM AND LEG ACHES

ARTHRALGIA-RT EXTREM

ARTHRITIS KNEE

3 PAGES DELETED

TRIGGER RELEASE-RT-M-FGR

W0RSENING KNEE PAIN

WORSENING ARTHRALGIA,R

WORSENING ARTHRITIS

WORSENING ARTHRITIS PAIN

WORSENING OSTEOARTHRITIS

WORSENLNG LEFT KNEE PALN

CONSTITUTIONAL BACK PAIN BACK ACHE

BACK ACHE MORE NOTICEABL

BACK PAIN

BACK PAIN STIFFNESS

BACK PN-THRACIC/CERVICAL

BACK STRAIN LOWER

BACKACHE

Multivariable adjustmentMultivariable adjustment

• Sometimes adjust for baseline variablesSometimes adjust for baseline variables

• Especially those that are maldistributedEspecially those that are maldistributed

• If algorithm for adjustment not pre-defined, adds If algorithm for adjustment not pre-defined, adds subjective element to “objective” RCTsubjective element to “objective” RCT

• Given ineffective treatment, with enough fiddling with Given ineffective treatment, with enough fiddling with adjustments, can come up with significant effect (Paul adjustments, can come up with significant effect (Paul Meier)Meier)

• Conclusions: Many argue that should NEVER do Conclusions: Many argue that should NEVER do adjustments in RCT’sadjustments in RCT’s

• If do adjustment, severely limit plansIf do adjustment, severely limit plans

Statistical issues: SummaryStatistical issues: Summary

• ITT (from 1/30 lecture):ITT (from 1/30 lecture):– All participants remain on medicationAll participants remain on medication

– All participants are followed until end of studyAll participants are followed until end of study

– Pre-planned analysisPre-planned analysis

• Multiple comparisons are ubiquitousMultiple comparisons are ubiquitous– MonitoringMonitoring

– Subgroup analysesSubgroup analyses

– Safety analysesSafety analyses

• Where possible, minimize subjectivity and adhoc-nessWhere possible, minimize subjectivity and adhoc-ness

• Use judgementUse judgement