bios 6648: design & conduct of clinical...

Date: 4 Sep 2013

1. Setting andObjectives1.0 Background

(a) Treatment indication

(b) Inference uponcompletion

1.1 The study population

1.2 The study question

(a) What is the treatment?

(b) Phase I-IV trials

(c) Nature of the clinicalquestion

(d) 1-sided vs 2-sidedquestions

1.3 Case study: Rocket-AF

Bios 6648- pg 1

Bios 6648: Design & conduct of clinical researchSection 1 - Specifying the study setting and objectives

1. Specifying the study setting and objectives

1.0 BackgroundI Where will we end up?:

(a) The treatment indication(b) Inference upon trial completion

I The scientific method

1.1 Defining the study population1.2 Defining the study question

(a) Defining the interventions: What is the treatment?(b) Phase I-IV clinical trials(c) Statistical structure of the outcome space(d) 1-sided versus 2-sided questions

1.3 Case study (Rocket-AF trial)

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Bios 6648- pg 2

1.0 Background

Where will we end up?(a) The treatment indication

I The FDA approves a new drug for a specific “indication."I The study setting/objectives must inform the intended

indication (or vice versa).I Components of an indication include:

I TreatmentI Disease or conditionI Patient populationI Therapeutic objective

I See my written notes for section 1 for further discussionI Example: Exercise 1.

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Bios 6648- pg 3

1.0 Background

(a) Specifying the treatment indication

Notes (See also Section 1 written notes):I Disease:

I Diseases can be defined by symptoms (COPD), causalagents (meningococcal meningitis), or treatment (MDRtuberculosis).

I The definition of a disease often changes with factorsunrelated to the disease (e.g., new treatments or a newcategorization of symptoms)

I Population of patients:I The target patient population is similarly dynamic.I Example: better diagnostic tools may detect cancer at

earlier stages or make it easier to detect later-stagedisease.

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Bios 6648- pg 4

1.0 Background

(a) Specifying the treatment indication (con’t)

I Treatment:I The way in which a treatment is delivered may change.I New formulations may allow oral instead of IV delivery,

which might extend the use to other populations or otherforms of the disease.

I Ancillary treatments (standard of care) is always changing.I Desired outcome

I Primary clinical outcomes versus surrogate outcomes(Vioxx; mammography; colon cancer screening)

I Unanticipated or anticipated beneficial (sildenafil citrate) orharmful (rosiglitazone) effects.

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Bios 6648- pg 5

1.0 Background

Where will we end up?(b) How will we summarize trial results?

I Inference upon trial completion(i) What is statistical inference?(ii) Four required elements(iii) Properties of estimators(iv) Interpretation of interval estimates

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Bios 6648- pg 6

1.0 Background

Inference upon trial completion(i) Why review statistical foundations?

I We are discussing the study setting and objectives.I As a scientific experiment, the results of a clinical trial are

used to rule out (or rule in) hypotheses about treatmenteffects. The standards for rejecting (or acceptinghypotheses) are based on statistical criteria.

I We need a basic understanding of statistical foundationsin order to discuss the scientific setting and the role ofuncertainty.

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Bios 6648- pg 7

1.0 Background

Inference upon trial completion(i) What is statistical inference?

Underlying Population

Sample

Statistics

Inference

θθ denotes unknown center

about θθ

Sample summary measure: θθ̂

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Bios 6648- pg 8

1.0 Background

Inference upon trial completion(ii) Four required elements of statistical inference

We use θ̂ (observed trial result) to estimate the true underlyingvalue θ

1. Point estimate: θ̂ is the “best" estimate of θ.2. Interval estimate: Values of θ that are consistent with the

trial results.3. Expression of uncertainty (p-value): To what degree is a

particular hypothesis (the “null" hypothesis) consistent withthe observed trial results?

4. Decision: Based on the above measures, what decisionshould be reached about the use of a new therapy?

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Bios 6648- pg 9

1.0 Background


I Example:CHEST trial: Ghofrani,et.al. NEJM (2013); 369: 319-29:Riociguat for the Treatment of Chronic ThromboembolicPulmonary Hypertension.

I Trial: Randomized double-blind placebo controlled trial inpatients with inoperable CTEPH.

I Results:“...By week 16, the 6-minute walk distance ( had increasedby a mean of 39 m in the riociguat group, as compared witha mean decrease of 6 m in the placebo group(least-squares mean difference, 46 m; 95% confidenceinterval [CI], 25 to 67; P

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Bios 6648- pg 10

1.0 Background


Example (con’t)I Setting:

I Primary endpoint: 16-week change in 6-minute walkdistance (6MWD)

I Summary of outcome: mean change denoted byθ1 (riociguat) and θ0 (placebo)

I Measure of treatment effect: difference in 6mwd:θ = θ1 − θ0.

I Observed effect:I Observed summary outcomes: θ̂1 = 39m; θ̂0 =-6mI Observed treatment effect: θ̂ = θ̂1 − θ̂0 = 46m

(by least-squares regression).I Inference:

I Point estimate: 46mI Interval estimate: 25m to 67mI Uncertainty: p < 0.001I Decision: to use or not to use?

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Bios 6648- pg 11

1.0 Background

Inference upon trial completion(iii) Properties of estimators

Desirable properties of:I Point estimate

I Unbiased and consistent: the long-run average of θ̂ is veryclose to θ

I Small variance (Uniform Minimum Variance UnbiasedEstimator)

I Interval estimateI Correct coverage probability (e.g., 95% of all 95%

confidence interval include θ).I As narrow as possible while maintaining the correct

coverage probability.I P-value

I Correct sizeI Decision

I Decision criteria maintain the appropriate type I statisticalerror rate.

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Bios 6648- pg 12

(iv) Interpretation of an interval estimator

What is the interpretation of a 95% confidence interval?

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Bios 6648- pg 13


What’s wrong with the following picture?

θθL θθ̂obs θθu

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Bios 6648- pg 14


Proper depiction of an interval estimator:


If θ < θL or if θ > θU then the observed result θ̂ = θ̂obs would beunusual.

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Bios 6648- pg 15


I The scientific objective is to identify the hypotheses thathave (or have not) been ruled out by the trial’s results.

I Let U(θref |θ̂obs) represent a statistical measure of theconsistency between the trial’s result θ̂ = θ̂obs and thehypothesis θ = θref .

I By usual frequentist criteria this measure is equal to thesmaller of:

P(θ̂ ≥ θ̂obs|θ = θref )P(θ̂ ≤ θ̂obs|θ = θref )

I Reject the hypothesis θ = θref when U(θref |θ̂obs) is small;specifically when:

U(θref |θ̂obs) <α

2

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Bios 6648- pg 16


We seek the values of θ that cannot be rejected; specifically:I Find the set of θref such that U(θref |θ̂obs) ≥ α/2 usingα = 0.05.

I If θ̂ ∼ N (θ,V ) then the non-rejection region is given by[θL, θU ] where

θL = θ̂obs − 1.96√

VθU = θ̂obs + 1.96

√V

I (See graph above)

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Bios 6648- pg 17


What assumptions are necessary to assure that the aboveinterval has the correct properties?

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Bios 6648- pg 18


What assumptions are necessary to assure that the aboveinterval has the correct properties?

I No assumption about the distribution of the individual dataelements is necessary.

I The estimated effect θ̂ must follow a Normal distribution:I Central limit theorem assures θ is Normally distributed as

long as the sample size is not too small.I For interpretation as a non-rejection region, we must know

the mean-variance relationship.

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Bios 6648- pg 19

I A note on mean-variance relationships:


I With a mean-variance relationship the confidence intervalcan have the correct coverage probability, but may not be anon-rejection region.

I Interventions often change both the mean and the variance.I We will return to this issue in chapter 7.

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Bios 6648- pg 20


In summary...I Scientific decisions must consider the magnitude of the

effect (point estimate) and the hypotheses that remainviable based on the trial’s results (the interval estimate).

I I will appeal to these considerations as I describe thescientific setting.

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Bios 6648- pg 21


Example (CHEST trial CI: 25m to 67m):I 16-week improvement in 6MWD with riociguat was 46m

better than the improvement with placebo. The variabilityin the results allows us to rule out (with 95% confidence)improvements that are more than 67 meters greater withriociguat or less than 25 meters greater with riociguat.

I Note: the following is incorrect:I There is a 95% chance (or probability) that the true

underlying difference is between 25 meters and 67 meters.I Note: the following is sometimes accepted, but

misleading:I We are 95% confident that the true underlying difference is

between 25 meters and 67 meters.

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Bios 6648- pg 22

1.0 Background

The scientific method

I The scientific method is an iterative process of posing andevaluating hypotheses using carefully designedexperiments.

I A clinical trial is an experiment and should be built oncarefully-framed hypotheses:

I What is the treatment?I What is θ (the measure of treatment effect)?I What are important differences?I What differences support recommending use of a new

treatment?I The trial must be designed to be informative relative to the

hypotheses (the scientist game)I Upon completion the range of viable hypotheses that

remain is determined by the experimental results

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Bios 6648- pg 23

1.0 Background

The scientific method: The scientist game

Assignment: Try the scientist game:htpp://www.emersonstatistics.com/ScientistGame

I Careful consideration of what you want to know upon trialcompletion is essential. The ‘obvious’ choice is often notthe best choice.

I The scientist game is illustrative of the scientificimportance of all aspects of the design including:

I Specification of the treatmentI Selection and definition of the outcome(s)I Choice of control groupI Definition of design hypothesesI Statistical standard for evidenceI Choice of sample size

What was your choice?

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Bios 6648- pg 24

1.0 Background

The scientific method: The scientist game

The scientist game illustrates how it is possible to select an entirelyuninformative experiment to test a hypothesis. An explanation of game and itsapplication to experimental design and clinical trials is given on the abovewebsite. The possible choices for your experiment and whether or not they areinformative (indicated by a +) are:

Possible ExperimentsHypotheses A b b B a B a Aletter, size, script + - - - - - - -letter, size + - - - - - - +letter, script + - - - - - + -size, script + - - - - + - -letter + - - - + - + +size + - - + - + - +script + - + - - + + -all coincidence + + + + + + + +

The best choices are B, a, or A because they will reduce the number ofpotential hypotheses from 8 to 4.

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Bios 6648- pg 25

1.1 Defining the study population

Defining the study population

I Study population:I Subjects in the study are representative of the study

population.I Study results are intended to estimate effects in the study

populationI Study population is defined by:

I Eligibility criteria: Characteristics of individuals who will beinvited to participate in the trial

I Exclusion criteria: Individuals who will be excluded even ifthey meet the eligibility criteria (usually for safety reasons).

I “Target" population:I The population in which the treatment/intervention will be

used.I The treatment indication is for the target population.

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Bios 6648- pg 26



Reasons why the study population might differ from target:(a) Ethical:

I Cannot force participationI Sometimes you must exclude “vulnerable populations"; e.g.:

I PrisonersI Pregnant womenI ChildrenI These populations might be studied after efficacy is

established in the study population.

(b) PracticalI E.g., restriction to major regional centers** Beware of excessive restriction

(c) Scientific:I Compliant (exclude subjects who are likely to be

non-compliant).I Restrict to subjects who will be able to complete follow-up

visits.I Exclude co-morbid conditionsI Require basic level of health(?)

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Bios 6648- pg 27



Reasons why the study population might differ from target:(d) Special considerations in placebo-controlled trials:

I Restrict to patients who can (ethically) receive placeboI (Sometimes this restriction is used even if the new drug

would be offered to the patients who are excluded.)

But remember:“If it is ethical to conduct a placebo controlled trial, then it isunethical not to... (Lloyd Fisher)"

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Bios 6648- pg 28



Selected examples for illustrationI OCEANS trial (Carol AghajanianC., et.al. J Clin Oncol

(2012); 30:2039-2045:A Randomized, Double-Blind, Placebo-Controlled Phase IIITrial of Chemotherapy With or Without Bevacizumab inPatients With Platinum-Sensitive Recurrent EpithelialOvarian, Primary Peritoneal, or Fallopian Tube Cancer

I Problems with gastro-intestinal perforation in early trialsI Restricting eligibility to platinum-sensitive recurrent cancers

appears to have eliminated those problems.I See Eligibility Criteria in paper (bottom of first column page

2040).

I CHEST trial (see first exercise)I Review JK notes on chapter 12.

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Bios 6648- pg 29

End:Section 1.1

Date: 4 Sep 20131. Setting and Objectives1.0 Background1.1 The study population1.2 The study question1.3 Case study: Rocket-AF

bios 6648: design & conduct of clinical...

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