Increasing Complexity of Clinical Trials

Increasing Complexity of Clinical Trials

Definitions:
Procedures: include lab & blood work, routine exams, x-rays & imaging, questionnaire & subjective assessments, invasive procedures, heart assessment, etc.

Protocol: the clinical-trial design plan
Enrollment rate: the percentage of volunteers meeting the increasing number of protocol eligibility criteria (percentage screened who were then enrolled)

Retention rates: the percentage of volunteers enrolled who then completed the study; declining retention rates mean that firms must enroll more patients initially and/or recruit more patients during the trial.

Increasing Complexity of Clinical Trials
During the last decade clinical trial designs and procedures have become much more complex, demanding more staff time and effort, and discouraging patient-enrollment and retention

Unique Procedures per Trial Protocol (Median)
Total Procedures per Trial Protocol (Median)
Clinical-Trial Staff Work Burden (Measured in Work-effort Units)
Length of Clinical Trial (Days)
Clinical-Trial-Participant Enrollment Rate
Clinical-Trial-Participant Retention Rate

Increasing Complexity of Clinical Trials.ppt

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Clinical Protocol Development

CLINICAL PROTOCOL DEVELOPMENT

What’s The Question?
What is the study hypothesis?

What’s The Question?
* What’s the outcome?
* What’s the intervention?
* When and for how long?
* For whom?
* How many participants are needed?
* How can we optimize potential benefit (and what we learn) while minimizing potential harm?

Answering the Question
* Response variable selection and measurement
* Defining the intervention
* Study design
* Eligibility criteria
* Sample size estimate
* Patient management procedures
* Monitoring for safety and benefit
* Data analysis approaches
Response Variable Selection
* “Dose ranging”
* Biologic activity
* Biomarker
o Understand mechanism
o Surrogate outcome
* Toxicity
* Condition/vector/gene interaction
* Feasibility for larger study
* Clinical outcome

Response Variable Criteria
* Well defined
* Stable
* Reproducible
* Unbiased
* Ascertainable in all participants
* Adequately address study hypothesis

Defining the Intervention
* Dose/dosing schedule
* Vector
* Route of delivery
* Method of preparation

Study Design
* Uncontrolled
* Controlled
o Before/after
o Historical
o Concurrent, not randomized
o Randomized

Comparing Treatments
* Fundamental principle
o Groups must be alike in all important aspects and only differ in the intervention each group receives
o In practical terms, “comparable treatment groups” means
“alike on the average”
* Randomization
o Each participant has the same chance of receiving any of the
interventions under study
o Allocation is carried out using a chance mechanism so that neither the participant nor the investigator will know in advance which will be assigned
* Blinding
o Avoidance of conscious or subconscious influence
o Fair evaluation of outcomes

Non-randomized Trials May Be Appropriate
* Early studies of new and untried therapies
* Uncontrolled early phase studies where the standard is relatively ineffective
* Investigations which cannot be done within the current climate of controversy (no “clinical equipoise”)
* Truly dramatic response

Advantages of Randomized Control Clinical Trial
1. Randomization "tends" to produce comparable groups
2. Randomization produces valid statistical tests

Disadvantages of Randomized Control Clinical Trial

1. Generalizable Results?
o Participants studied may not represent general study population.
2. Recruitment
o Hard
3. Acceptability of Randomization Process
o Some physicians will refuse
o Some participants will refuse
4. Administrative Complexity
Study Population
Subset of the general population determined by the eligibility criteria
General population
Eligibility criteria
Enrollment
Study sample
Eligibility Criteria
* State in advance
* Consider
o Potential for effect of intervention
o Ability to detect that effect
o Safety
o Ability for true informed consent

Sample Size (1)
* The study is an experiment in people
* Need enough participants to answer the question
* Should not enroll more than needed to answer the question
* Sample size is an estimate, using guidelines and assumptions

Sample Size (2)
* Approaches for early phase studies
o Dose escalation schemes
o Decision that intervention is unlikely to be effective in ?x% of participants
o Decision that intervention could be effective in ?x% of participants
* Standard ways of estimating for phase III
Sample Size (3)
* Assumptions depend on
o Nature of condition
o Desired precision of answer
o Availability of alternative treatments
o Knowledge of intervention being studied
o Availability of participants

Regular Follow-up
* Routine Procedures (report forms)
o Interviews
o Examinations
o Laboratory Tests
* Adverse Event Detection/Reporting
* Quality Assurance
Contingency Plans
* Patient management
* Evaluation and reporting to all relevant persons and groups
* Data monitoring plans
* Protocol amendment or study termination
Data Analysis (1)
* Occurrence of event
* Time to event
* Mean level of response
* Duration of response
Data Analysis (2)
* Intention-to-treat
* Explanatory
* Subgroups
* Adjusted vs. Unadjusted

Data Analysis (3)
* Specify in advance
o Primary
o Secondary
o Other
o Statistical approach
* Exploratory

Clinical Protocol (1)
* Background/Justification
--Where we are in the field
--What the study will add that is important
* Objectives
--Primary hypothesis
--Secondary hypotheses
--Other
Clinical Protocol (2)
* Study Design and Methods
--Type of study, comparison
--Inclusion and exclusion criteria
--Description of intervention (what, how)
--Concomitant therapy
--Examination procedures (baseline, follow-up, outcome assessment)
--Intervention assignment procedure

Clinical Protocol (3)
* Monitoring and Management
--Data and safety monitoring
--Adverse event assessment, reporting
--Contingency procedures
--Withdrawal criteria

Clinical Protocol (4)
* Statistics
--Sample size
--Stopping guidelines
--Analysis plans
* Participant protection issues
Summary
* Protocol lays out who, what, why, when, where, how
* Safeguards participants
* Safeguards study integrity
* Midcourse changes are often appropriate (even necessary)

Clinical Protocol Development.ppt

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Introduction to Clinical Trials

Introduction to Clinical Trials

Issues in Analysis of Randomized Clinical Trials
Sources of Bias
1. Patient selection
2. Treatment assignment
3. Patient Evaluation
4. Data Analysis

Minimize Bias
1. Randomized Controls
2. Double blind (masked)
3. Analyze what is randomized

What Data Should Be Analyzed?
* Basic Intention-to-Treat (ITT) Procedure
o Analyze what is randomized!
* Randomized control trial “gold” standard
o Beware of lookalikes
* Definitions
Exclusions
o Screened but not randomized
o Affects generalizability
o Validity OK
Withdrawals from Analysis
o Randomized, but not included in data analysis
o Possible to introduce bias!

Patient Closeout
* ICH E9 Glossary
o “Intention-to-treat principle - …It has the consequence that subjects allocated to a treatment group should be followed up, assessed, and analyzed as members of that group irrespective of their compliance with the planned course of treatment.”

Patient Withdrawn in Analysis
* Common Practice - 1980s
o Over 3 years, 37/109 trials in New England Journal of Medicine

* Typical Reasons Given
a. Patient ineligible (in retrospect)
b. Noncompliance
c. Competing events
d. Missing data

I. Patient Withdrawn in Analysis
A. Patient INELIGIBLE
o After randomization, discover some patients did not in fact meet entry criteria
o Concern ineligible patients may dilute treatment effect
o Temptation to withdraw ineligibles
o Withdrawl of ineligible patients, post hoc, may introduce bias

Betablocker Heart Attack Trial
* 3837 post MI patients randomized
* 341 patients found by Central Review to be ineligible
* Results

Anturane Reinfarction Trial (1980) NEJM
* Randomized, double blind, placebo controlled
Anturane Reinfarction Trial (1980)
* 1629 patients randomized
o 1631 entered, but two patients randomized twice
o Need to delete 03013, 17008
o Use first randomization!

* Declared post hoc 71 “ineligible” patients

Analyzable Deaths - Within 7 days of being off drug

1980 Anturane Mortality Results
Total Mortality
Anturane Reinfarction Trial (1980)
Total Mortality
Anturane Sudden Death (SD)
for Total Follow-up
Anturane Analysis
Acceptable Policies For Ineligible Subjects

1. Delay randomization, confirm eligibility and allow no withdrawals (e.g. AMIS) (Chronic Studies)
2. Accept ineligibles, allow no withdrawals
(e.g. BHAT, MILIS) (Acute Studies)
3. Allow withdrawals if:
a. Procedures defined in advance
b. Decision made early (before event)
c. Decision independent and blinded
d. Use baseline covariates only (two subgroups)
e. Analysis done with and without

B. WITHDRAWL FOR NON-COMPLIANCE
References: Sackett & Gent (1979) NEJM, p. 1410

Coronary Drug Project (1980) NEJM, p. 1038
* Two Types of Trials
1. Management
- "Intent to Treat" Principle
- Compare all subjects, regardless of compliance

2. Explanatory
- Estimate optimum effect, understand mechanism
- Analyze subjects who fully comply
WITHDRAWALS FOR NON-COMPLIANCE MAY LEAD TO BIAS!

Breast Cancer Adjuvant Therapy Probability of Disease Free Survival for Years Post Mastectomy (Method I)
Breast Cancer Adjuvant Therapy
Probability of Disease Free Survival for
Years Post Mastectomy (Method II)
Redmond et al (1983) Cancer Treatment Report
Example: Coronary Drug Project 5-Year Mortality
Comments

* Higher % of estrogens patients did not comply
* Beneficial to be randomized to estrogen & not take it
* (6.1% vs. 9.9%)
* Best to be randomized to placebo & comply (4.8%)
Aspirin Myocardial Infarction Study (AMIS)
Summary of Compliance
* No consistent pattern
Example Non-compliance Did Worse
CDP Clofibrate, AMIS Both Treatment & Control
CDP Estrogen Control Only
Beta-blocker, Wilcox Two Treatments, Not Control
* Compliance an outcome, not always independent of treatment
* Withdrawal of non-compliers can lead to bias
* Non-compliers dilute treatment
* Try hard not to randomize non-compliers

II. Competing Events
* Subject may be censored from primary event by some other event (e.g. cancer vs. heart disease)
* Must assume independence
* If cause specific mortality used, should also look at total death
* If non-fatal event is primary, should also look at total death and non-fatal event
* Problem for some response measures

Problem of Definitions
Classification Anturane Placebo P-value
Anturane Reinfarction Trial Sudden Death
Category Source Placebo Anturane P-value

III. "Wrong", Inconsistent, Outlying Data
* "Wrong" or "outlying" data may in fact be real
* Decisions must be made blind of group assignment
* All modifications or withdrawals must be documented
IV. Missing Outcome Data
* Design with zero
o missingness may be associated with treatment
+ for analysis, data are not missing at random
+ even if same number missing, missing may be for different reason in each treatment group
* Implement with minimum possible
* Analyze exploring different approaches
o if all, or most, agree, then more persuasive

“Best” and “Worst” Case Analyses
VI. Poor Clinic Performance in a Multicenter Study

* If randomization was stratified by clinic, then withdrawal of a clinic is theoretically valid
* Withdrawal must be done independent of the outcome at that clinic
VIII. Fishing or Dichotomizing Outcomes
* Common practice to define a response (S,F) from a non-dichotomous variable
* By changing our definition, we can alter results
* Thus, definitions stated in advance
* Definitions should be based on external data

Dichotomizing Outcomes
Example
IX. Time Dependent Covariate Adjustment
* Classic covariate adjustment uses baseline prognostic factors only
o Adjust for Imbalance
o Gain Efficiency

* Adjustment by time dependent variates not recommended in clinical trials (despite Cox time dependent regression model)

* Habit from epidemiology studies
Intent To Treat (ITT) Principle

* Analyze all patients randomized, regardless of compliance to assigned intervention
* Analyze all events in the follow-up, regardless of compliance


Introduction to Clinical Trials.ppt

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