clinical trials potpourri: databases, trials and meta- analysis oh my! oh my!

Clinical Trials Potpourri:Clinical Trials Potpourri:Databases, Trials and Meta-Databases, Trials and Meta-

AnalysisAnalysis

Oh My!Oh My!

OutlineOutline• Why Trials and Not Databases?Why Trials and Not Databases?

• Trial DesignTrial Design– RandomizationRandomization– Proper ControlsProper Controls– Intention To TreatIntention To Treat– ExclusionsExclusions

• WithdrawalsWithdrawals

• Metanalyses vs. Big And Simple TrialsMetanalyses vs. Big And Simple Trials

LIMITATIONS OF DATABASES LIMITATIONS OF DATABASES

• Prospective approach not usedProspective approach not used

• Randomization not usedRandomization not used

• ““Selection Bias” Selection Bias” should be assumed regardless of should be assumed regardless of direction of treatment effect.direction of treatment effect.– Regimen depends on:Regimen depends on:

• patient presentationpatient presentation

• severity of disease severity of disease

• Treated and controls systematically differTreated and controls systematically differ

• Adjustment for covariates inadequateAdjustment for covariates inadequate

– Unknown covariates affect outcomeUnknown covariates affect outcome

– Relevant covariates unavailableRelevant covariates unavailable

– Incomplete collection covariate dataIncomplete collection covariate data

– Covariate errors compromise adjustmentCovariate errors compromise adjustment

– Mismodeling -- never really knownMismodeling -- never really known

• ““Time Zero” not identified.Time Zero” not identified.

• All patients or random sample?All patients or random sample?

• Inadequate test of new therapyInadequate test of new therapy

Databases serve as hypothesis Databases serve as hypothesis generation for clinical trialsgeneration for clinical trials

Trial DesignTrial Design

PREREQUISITES FOR PREREQUISITES FOR SUCCESSFUL CLINICAL TRIALSSUCCESSFUL CLINICAL TRIALS

• Trial Needs to be Done - Trial Needs to be Done - EquipoiseEquipoise

• Question is appropriate, unambiguousQuestion is appropriate, unambiguous

• Trial architecture is validTrial architecture is valid

• Inclusion/Exclusion criteria balance efficiency Inclusion/Exclusion criteria balance efficiency and generalizabilityand generalizability

• FeasibleFeasible

• Administration effectiveAdministration effective

Sacket 1983.

KEY POINT OF TRIALS:KEY POINT OF TRIALS:PROPER CONTROL PROPER CONTROL

““Group against which intervention group is Group against which intervention group is compared”compared”

• Placebo or “standard of care”Placebo or “standard of care”

– Modified slightly for Clinical TrialsModified slightly for Clinical Trials

– Identifying and maintaining control group?Identifying and maintaining control group?

– Can be an extremely difficult problemCan be an extremely difficult problem

– Serious consequences if not doneSerious consequences if not done

RANDOMIZATION PROCESSRANDOMIZATION PROCESS

• Produce comparable study groups Produce comparable study groups

• Known and unknown risk factorsKnown and unknown risk factors

• Removes bias in subject allocation Removes bias in subject allocation

• Guarantees statistical tests will have Guarantees statistical tests will have valid significance levelsvalid significance levels

• Trialist’s most powerful weapon against biasTrialist’s most powerful weapon against bias

EMPIRICAL EVIDENCE OF BIASEMPIRICAL EVIDENCE OF BIASCochrane CollaborationCochrane Collaboration

• Objective: Objective: DDetermine if inadequate randomized etermine if inadequate randomized control design and execution are associated bias control design and execution are associated bias in estimating treatment effectsin estimating treatment effects..

• Design:Design: 250 controlled trials from 33 meta-analyses 250 controlled trials from 33 meta-analyses

• Outcomes Tests: Outcomes Tests: – Inadequate allocationInadequate allocation– Inadequate sequence generationInadequate sequence generation– Exclusions after randomizationExclusions after randomization– Lack of double blind designLack of double blind design

KF Schulz, et al: JAMA 1995;273:408-412KF Schulz, et al: JAMA 1995;273:408-412

Inadequate Blinding and BiasInadequate Blinding and BiasMeasure of Methods QualityMeasure of Methods Quality Odds Ratio Odds Ratio

(95% CI)(95% CI) XX22(df)(df) pp

Allocation Concealment (Blinding)Allocation Concealment (Blinding)

AdequateAdequate 1.00 (ref)1.00 (ref)

InadequateInadequate 0.70 (0.62-0.70)0.70 (0.62-0.70) 32.9 (1)32.9 (1) <0.001<0.001

Sequence Generation Sequence Generation

AdequateAdequate 1.00 (ref)1.00 (ref)

InadequateInadequate 0.95 (0.81-1.12)0.95 (0.81-1.12) 0.31 (1)0.31 (1) 0.580.58

ExclusionsExclusions

NoNo 1.00 (ref)1.00 (ref)

YesYes 1.07 (0.94-1.21)1.07 (0.94-1.21) 0.99 (1)0.99 (1) 0.320.32

Double BlindedDouble Blinded

NoNo 1.00 (ref)1.00 (ref)

YesYes 0.83 (ref)0.83 (ref) 6.16 (1)6.16 (1) 0.010.01

Inadequate Blinding and BiasInadequate Blinding and Bias

Concealment Allocation

Odds Ratio(95% CI)

X2 (df) p

Adequate 1.00 (referent)

Unclear 0.67 (0.60-0.75) 57.9 (2) <.001

Inadequate 0.59 (0.48-0.73)

Inadequate concealing (bliniding) of data Inadequate concealing (bliniding) of data associated with bias that associated with bias that cannotcannot be controlled for be controlled for

APPROPRIATE CONTROLSAPPROPRIATE CONTROLS

• Difficult to obtain unbiased sampleDifficult to obtain unbiased sample

• What is the appropriate control group?What is the appropriate control group?

• Comparison groups similar as possibleComparison groups similar as possible

• Example: Example: Select a number 0 - 9.Select a number 0 - 9.

RESULTS OF SELECTION: RESULTS OF SELECTION: NUMBERS 0-9NUMBERS 0-9

• 0 and 9 usually under-represented0 and 9 usually under-represented

• The extremes are not as often selectedThe extremes are not as often selected

• Seeming preference for odd numbersSeeming preference for odd numbers

• 3, 5, 7 will be more often selected3, 5, 7 will be more often selected

INTENTION TO TREATINTENTION TO TREAT“ONCE IN, ALWAYS COUNTED” “ONCE IN, ALWAYS COUNTED” • Intention to treat analysis Intention to treat analysis avoids biasavoids bias

– Excluding randomized subjects on the basis Excluding randomized subjects on the basis of outcome or response variables is of outcome or response variables is worst worst kind of bias kind of bias

– Bias of unknown magnitude and directionBias of unknown magnitude and direction

• Intention to treat safeguards against Intention to treat safeguards against erroneous efficacy when excluding erroneous efficacy when excluding subjects who subjects who do not do not adhere to protocoladhere to protocol

INTENTION TO TREATINTENTION TO TREAT“ONCE IN, ALWAYS COUNTED” “ONCE IN, ALWAYS COUNTED”

Randomized controlled trials with Randomized controlled trials with outcome endpoints should all be outcome endpoints should all be

intention to treat designintention to treat design

EFFICACY (EFFICACY (ON TREATMENTON TREATMENT) ) ANALYSISANALYSIS

• Expected in pharmaceutical industry.Expected in pharmaceutical industry.

• Precisely described Precisely described

– Denominator in two analyses will not be the Denominator in two analyses will not be the samesame

• Estimated benefit between two analysesEstimated benefit between two analyses

• Should be reported Should be reported without p-valuewithout p-value

EXCLUSION FROM TRIALSEXCLUSION FROM TRIALS

ProPro

• Before RandomizationBefore Randomization

– Rationale: Eligibility Rationale: Eligibility criteria not metcriteria not met

• No bias in comparison No bias in comparison of group resultsof group results

• Follow-up those Follow-up those excluded?excluded?

– Commonly as a registryCommonly as a registry

ConCon

• Affects Affects generalizability of generalizability of resultsresults

• Investigators need to Investigators need to ensure group ensure group comparabilitycomparability

EXCLUSION OF SOME EVENTEXCLUSION OF SOME EVENT

• Prevention Trials - Immediate EventsPrevention Trials - Immediate Events

– Understand intervention?Understand intervention?

– Adverse effects may occur earlierAdverse effects may occur earlier

• Present both analysesPresent both analyses

• Really a withdrawal trial. Really a withdrawal trial.

Do Not Do This!Do Not Do This!

WITHDRAWALSWITHDRAWALS

• Similar to non-adherence, but more Similar to non-adherence, but more detrimentaldetrimental

• Loss of information on treatment tolerance, Loss of information on treatment tolerance, efficacyefficacy

• Can affect endpoints critically if no further Can affect endpoints critically if no further follow upfollow up

– Intention to treat will regard as censoredIntention to treat will regard as censored

STUDY POLICY ON STUDY POLICY ON WITHDRAWALSWITHDRAWALS

If done, should be done:If done, should be done:

•with methods stated with methods stated a-prioria-priori

•blindedblinded

•early in the study early in the study

•but minimizing the numberbut minimizing the number

May still be challenged!May still be challenged!

EXAMPLES OF DESIGN POLICIES EXAMPLES OF DESIGN POLICIES RELATED TO WITHDRAWALSRELATED TO WITHDRAWALS

1.1. Enroll only those with secure Enroll only those with secure diagnosis.diagnosis.

2.2. Enroll confirmed and unconfirmed, Enroll confirmed and unconfirmed, later withdraw those with diagnostic later withdraw those with diagnostic error.error.

3.3. Enroll confirmed and unconfirmed, Enroll confirmed and unconfirmed, allow allow nono withdrawals. withdrawals.

INELIGIBILITYINELIGIBILITY

•Clerical error - Canadian Cooperative TrialClerical error - Canadian Cooperative Trial

•Definition - Surgical vs Medical Therapy in Bilateral Definition - Surgical vs Medical Therapy in Bilateral Carotid StenosisCarotid Stenosis

•Laboratory error - BHATLaboratory error - BHAT

•Misinterpretation - MILISMisinterpretation - MILIS

•Mis-classificaiton - ANTURANEMis-classificaiton - ANTURANE

INELIGIBILITYINELIGIBILITY

•Clerical error - Canadian Cooperative TrialClerical error - Canadian Cooperative Trial

•Definition - Surgical vs Medical Therapy in Bilateral Definition - Surgical vs Medical Therapy in Bilateral Carotid StenosisCarotid Stenosis

•Laboratory error - BHATLaboratory error - BHAT

•Misinterpretation - MILISMisinterpretation - MILIS

•Misclassification - ANTURANEMisclassification - ANTURANE

WithdrawalsWithdrawals

SurgerySurgery MedicalMedicalTreatmentTreatment RRRR pp

AnalyzedAnalyzed

TIA, Stroke TIA, Stroke or Deathor Death 4343 5353 0.730.73 0.020.02

NN 8181 7272

SURGICAL VERSUS MEDICAL THERAPY BILATERAL SURGICAL VERSUS MEDICAL THERAPY BILATERAL CAROTID STENOSIS CAROTID STENOSIS

Definition: “alive and stroke free after hospitalization”Definition: “alive and stroke free after hospitalization”

WithdrawalsWithdrawals

SurgerySurgery MedicalMedicalTreatmentTreatment RRRR pp

AnalyzedAnalyzed

NN 8181 7272

All All AvailableAvailable

NN 9494 7373

SURGICAL VERSUS MEDICAL THERAPY BILATERAL SURGICAL VERSUS MEDICAL THERAPY BILATERAL CAROTID STENOSIS CAROTID STENOSIS

Definition: “alive and stroke free after hospitalization”Definition: “alive and stroke free after hospitalization”

WITHDRAWALSWITHDRAWALSEffects on Trial Outcomes Effects on Trial Outcomes

a-prioria-priori definition for withdrawal - interpreted differently definition for withdrawal - interpreted differently

• Reanalysis: 19 deaths found in ineligiblesReanalysis: 19 deaths found in ineligibles

– Original 10 vs. 4 death. Reanalysis 12 vs. 7 deathsOriginal 10 vs. 4 death. Reanalysis 12 vs. 7 deaths

– p using eligibles=0.07p using eligibles=0.07 p using all =0.20p using all =0.20

Mortality by study group and eligibility status: Mortality by study group and eligibility status: anturane (sulfinpyrazone) re-infarction trialanturane (sulfinpyrazone) re-infarction trial

RandomizedRandomized IneligibleIneligible EligiblesEligibles

AnturaneAnturane 813 (9.1)813 (9.1) 38 (26.3)38 (26.3) 775 (8.3)775 (8.3)

PlaceboPlacebo 816 (10.9) 816 (10.9) 33 (12.1)33 (12.1) 783 (10.9)783 (10.9)

POOR QUALITY OR MISSING DATAPOOR QUALITY OR MISSING DATA

• Lost to follow-up – No endpoint ascertainmentLost to follow-up – No endpoint ascertainment

• Complete or near complete ascertainment is Complete or near complete ascertainment is possible on clinical events possible on clinical events

TrialsTrials N Missing N Missing

CDP CDP 44

LRC LRC 00

PHS PHS 00

SHEP SHEP 66

POOR QUALITY OR MISSING DATAPOOR QUALITY OR MISSING DATA

• Other response variablesOther response variables

– Imputation of missing data Imputation of missing data

• 20% increase in efficacy20% increase in efficacy

– Survival analysis - time to eventSurvival analysis - time to event

– Removal of outliers - similar results?Removal of outliers - similar results?

– Worst case analysisWorst case analysis

Meta-AnalysisMeta-Analysis

Once upon a time, there were Once upon a time, there were many magnesium trials…many magnesium trials…

HOW DO WE USE META-ANALYSIS? HOW DO WE USE META-ANALYSIS? SMALL TO MODERATE SIZED TRIALS SMALL TO MODERATE SIZED TRIALS

AND LARGE SIMPLE TRIALSAND LARGE SIMPLE TRIALS

Studies: Studies: Effect of magnesium on mortality Effect of magnesium on mortality in immediate post-myocardial infarction in immediate post-myocardial infarction

Sequence of InvestigationsSequence of Investigations

Meta-analysis - 1991Meta-analysis - 1991Moderate Size Trial - 1992Moderate Size Trial - 1992

Mega Trial - 1995Mega Trial - 1995

Large Trial-2002Large Trial-2002

INITIAL META-ANALYSISINITIAL META-ANALYSIS MAGNESIUM AND DEATH POST MIMAGNESIUM AND DEATH POST MI

• 7 trials: 1301 participants7 trials: 1301 participants

• 657 (25) magnesium657 (25) magnesium

• 644 (53) controls644 (53) controls

• 55% relative reduction in mortality55% relative reduction in mortality– 95% CI 0.28-0.71, p<0.00195% CI 0.28-0.71, p<0.001

• Biologically plausible result:Biologically plausible result:– Ventricular arrhythmia reduced: 7 versus 109 Ventricular arrhythmia reduced: 7 versus 109

• Adverse effects rareAdverse effects rare

MAGNESIUM AND DEATH POST MIMAGNESIUM AND DEATH POST MI

Included Trial CharacteristicsIncluded Trial Characteristics• All randomized, 6 blindedAll randomized, 6 blinded

• Baseline characteristics balancedBaseline characteristics balanced

• 99.4% follow-up for mortality 99.4% follow-up for mortality (8 patients)(8 patients)

• Similar administration and doseSimilar administration and dose– Treatment usually started within 12 hoursTreatment usually started within 12 hours– Dosage varied from 30-90 mmolsDosage varied from 30-90 mmols– Infusion over 24-48 hours. Some bolusInfusion over 24-48 hours. Some bolus

• Baseline and follow-up Mg levels similarBaseline and follow-up Mg levels similar

• 11 year mortality: 20% vs 32% from 2 studiesyear mortality: 20% vs 32% from 2 studies

MAGNESIUM TRIAL META-ANALYSISMAGNESIUM TRIAL META-ANALYSIS

Leicester Intravenous Magnesium Leicester Intravenous Magnesium Intervention Trial (LIMIT-2)Intervention Trial (LIMIT-2)

• N= 2316 patients with suspected acute MIN= 2316 patients with suspected acute MI

– Blinded placebo controlledBlinded placebo controlled

– 65% confirmation of MI in both groups65% confirmation of MI in both groups

• 8 mmol over 5 minutes; 65 mmol over 24 hrs8 mmol over 5 minutes; 65 mmol over 24 hrs

• Primary outcome - total mortality @ 28 daysPrimary outcome - total mortality @ 28 days

– 99.3% ascertainment99.3% ascertainment

• 24% mortality reduction24% mortality reduction (95%CI: 0.57-0.99,p = 0.04)(95%CI: 0.57-0.99,p = 0.04)

• 25% reduction in left ventricular failure25% reduction in left ventricular failure (95% CI = 0.61 - 0.91, p = 0.009)(95% CI = 0.61 - 0.91, p = 0.009)

LIMIT- 2LIMIT- 2

MAGNESIUM TRIAL META-ANALYSISMAGNESIUM TRIAL META-ANALYSIS

ISIS 4: ISIS 4: INTERNATIONAL STUDY INTERNATIONAL STUDY OF INFARCT SURVIVALOF INFARCT SURVIVAL

• N= 58,050 ParticipantsN= 58,050 Participants

• Entry up to 24 hours after onset of chest pain.Entry up to 24 hours after onset of chest pain.

• 2x2x2 factorial design: Treatments vs. Placebo2x2x2 factorial design: Treatments vs. Placebo

– 1 month, up to 100 mg/d captopril1 month, up to 100 mg/d captopril

– 1 month, controlled-release nitrate 60 mg/d1 month, controlled-release nitrate 60 mg/d

– 24 hours magnesium.24 hours magnesium.

• 8 mmols bolus, 72 mmols infusion8 mmols bolus, 72 mmols infusion

• Primary End Point: All cause mortalityPrimary End Point: All cause mortality

MORTALITY IN DAYS 0-35 MORTALITY IN DAYS 0-35 SUBDIVIDED BY OTHER RANDOMLY SUBDIVIDED BY OTHER RANDOMLY ALLOCATED STUDY TREATMENTSALLOCATED STUDY TREATMENTS

SYSTEMATIC OVERVIEW OF EFFECTS ON SYSTEMATIC OVERVIEW OF EFFECTS ON SHORT-TERM MORTALITY OF STARTING SHORT-TERM MORTALITY OF STARTING

INTRAVENOUS MAGNESIUM EARLY IN INTRAVENOUS MAGNESIUM EARLY IN ACUTE MYOCARDIAL INFARCTIONACUTE MYOCARDIAL INFARCTION

Meta-AnalysesMeta-AnalysesWHAT WENT WRONG?WHAT WENT WRONG?

WHAT SHOULD WE BELIEVE?WHAT SHOULD WE BELIEVE?• Previous meta-analysis and clinical trial - small numbersPrevious meta-analysis and clinical trial - small numbers

– 99% CI in LIMIT-2 - no benefit99% CI in LIMIT-2 - no benefit

• Increase in deaths ISIS-4Increase in deaths ISIS-4– p 0.07, 95% CI = +12-0%p 0.07, 95% CI = +12-0%

• No convergence or divergence - 1 yearNo convergence or divergence - 1 year

• 23,000 given bolus within 6 hours23,000 given bolus within 6 hours7.9% magnesium, 7.6% control7.9% magnesium, 7.6% control

• 17,000 no fibrinolytic therapy - no change17,000 no fibrinolytic therapy - no change

• ISIS an open trial - no apparent problemsISIS an open trial - no apparent problems

LIMITATION OF META-ANALYSISLIMITATION OF META-ANALYSIS

• Numbers per study is smallNumbers per study is small

• Number of outcomes (deaths) smallNumber of outcomes (deaths) small

• Potentially biased patient selectionPotentially biased patient selection

• Publication biasPublication bias

• Selection of endpoints - problematicSelection of endpoints - problematic

• Duration of follow up:Duration of follow up:– Generally covered hospital stayGenerally covered hospital stay– Limited long-termLimited long-term

META-ANALYSISMETA-ANALYSIS A systematic way of combining data to get a more precise A systematic way of combining data to get a more precise

estimate of the effect of a therapy.estimate of the effect of a therapy. PositivesPositives

• Combine all available data.Combine all available data.• Larger numbers of events available.Larger numbers of events available.• Estimate of therapeutic benefits possibleEstimate of therapeutic benefits possible..

NegativesNegatives• Loss of equipoiseLoss of equipoise• Outcome numbers may be smallOutcome numbers may be small• Uncritical examinationUncritical examination

ImportanceImportance• Sample size estimatesSample size estimates• FDA submissionsFDA submissions• Medical policy formulationMedical policy formulation

Lau et al – NEJM 1992:327: 248-254Lau et al – NEJM 1992:327: 248-254

CUMULATIVE META-ANALYSISCUMULATIVE META-ANALYSIS

““The Performance Of Updating A Meta-The Performance Of Updating A Meta-Analysis Every Time A New Trial Appears”Analysis Every Time A New Trial Appears”•Goal – Evaluating the results as a continuum.Goal – Evaluating the results as a continuum.

•Outcome – Supply practitioners with up-to-date informationOutcome – Supply practitioners with up-to-date information

•Methods Methods – ““Fixed effects model” (Mantel-Haenszel Statistic)Fixed effects model” (Mantel-Haenszel Statistic)– ““Random effects model” (DerSimonian-Laird Statistic)Random effects model” (DerSimonian-Laird Statistic)

•Methods Evaluation – Little difference in resultsMethods Evaluation – Little difference in results

•Recommendation – Use both methodsRecommendation – Use both methods

THROMBOLYTIC TRIALSTHROMBOLYTIC TRIALS

Large, Simple TrialsLarge, Simple Trials

LARGE, SIMPLE TRIALSLARGE, SIMPLE TRIALS

YUSUF, COLLINS AND PETOYUSUF, COLLINS AND PETO

““Ask an important question, Ask an important question, answer it reliably”answer it reliably”

Statistics in Medicine 1984;3:409-420 Statistics in Medicine 1984;3:409-420

LARGE, SIMPLE TRIALSLARGE, SIMPLE TRIALS

• Identification of effective treatmentsIdentification of effective treatments

• Disease common, treatment practicalDisease common, treatment practical

• Concentrate on major outcomes (e.g., death)Concentrate on major outcomes (e.g., death)

• Stratification does not improveStratification does not improve

• No need to subcategorize participantsNo need to subcategorize participants

• If no reliable answer yet - effect moderateIf no reliable answer yet - effect moderate

Statistics in Medicine 1984;3:409-420 Statistics in Medicine 1984;3:409-420

PREREQUISITES FOR PREREQUISITES FOR SUCCESSFUL CLINICAL TRIALSSUCCESSFUL CLINICAL TRIALS

• Trial Needs to be Done - Trial Needs to be Done - EquipoiseEquipoise

• Question is appropriate, unambiguousQuestion is appropriate, unambiguous

• Trial architecture is validTrial architecture is valid

• Inclusion/Exclusion criteria balance efficiency Inclusion/Exclusion criteria balance efficiency and generalizabilityand generalizability

• FeasibleFeasible

• Administration effectiveAdministration effective

Sacket 1983.

EXPECTED EFFECTS OF TRIAL SIZEEXPECTED EFFECTS OF TRIAL SIZE ON TRIAL RESULTS ON TRIAL RESULTS

Total no. of deaths intrial

(treated + control)

(Approx. no. of patientsrandomized if risk

Approx. probability offailing to achieve 1

P<0.01 significance iftrue risk reduction is

Comments thatmight be made ofsize before trial

begins

0-50 (under 500) over 0.9 Utterly inadequate

50-150 (1000) 0.7-0.9 Probably inadequate

150-350 (3000) 0.3-0.7Possibly adequate,

possibly not

350-650 (6000) 0.1-0.3 Probably adequate

over 650 (10,000) under 0.1 Definitely adequate

Effects of trial size on trial results. Relationship between Effects of trial size on trial results. Relationship between the total number of deaths in the two treatment groups the total number of deaths in the two treatment groups and the result actually attainedand the result actually attained

No. of trials resulting in:

Total no. ofdeaths in trial(-bl. plac.)

(Mean no. ofpatients

randomized)

Statisticalpower

P<0.05against

Non-sigt.againts

Non-sigt.favorable

P<0.05favourable

0-50 (255)Utterly

inadequate0 5 5 0

50-150 (861)Probably

inadequate0 1 9 1

150-350 (2925)Possibly

adequate,possibly not

0 0 1 2

350-650 (No such -bl.trials exist)

Problablyadequate

- - - -

over 650 (No such -bl.trials exist)

Definitelyadequate

- - - -

TOTAL (866)

Inadequateseparately,

adequate onlyin aggregate

0 6 15 3

SummarySummary

• Bias is Achilles heel of clinical Bias is Achilles heel of clinical investigation – REDUCE BIAS!investigation – REDUCE BIAS!

• Databases limited by selection bias, Databases limited by selection bias, inadequate control for all covariatesinadequate control for all covariates– Good hypothesis generationGood hypothesis generation

• Good trials need Good trials need good and maintained good and maintained randomizationrandomization to reduce bias to reduce bias

SummarySummary

• Meta-analyses good for overview of all Meta-analyses good for overview of all datadata– Small numbers and events, publication Small numbers and events, publication

bias limit efficacybias limit efficacy

• Ensure good trial design and Ensure good trial design and adminstrationadminstration– That is why you are in the audience!That is why you are in the audience!

clinical trials potpourri: databases, trials and meta- analysis oh my! oh my!

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