542-06-#1 STATISTICS 542 Introduction to Clinical Trials Protocols and Manual of Procedures.

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STATISTICS 542STATISTICS 542Introduction to Clinical TrialsIntroduction to Clinical Trials

Protocols andProtocols andManual of ProceduresManual of Procedures

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Protocol vs Manual of Operations Protocol vs Manual of Operations AnalogyAnalogy

• Protocol is general “blueprint” for– investigators + institutional review boards– sponsor– regulatory agencies

• Manual of Procedures is detailed “construction document”– clinic staff– data management staff

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Desirable Protocol Desirable Protocol CharacteristicsCharacteristics

• Clear

• Consistent

• Complete

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Scale ImplicationsScale Implications

• “Simple”– One investigator, one patient, one encounter

• “Harder”– Multiple investigators, multiple patients,

multiple visits, multiple cultures, multiple languages

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Considerations Considerations DuringDuring Protocol DevelopmentProtocol Development

For example• Randomization assignment and outcome

ascertainment– how is potential bias minimized?

• Treatment implementation– maximize compliance while minimizing

variation• within and between investigators and clinic staff• patient and their support system• over study follow-up and calendar time

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Protocol (1)Protocol (1)Should include:

1. Literature Review (Brief)Describe the "state of the art" and motivate rationale for this clinical trial

2. Statement of Objectives• What is the hypothesis that is being tested, and what endpoints or measurements

& observations will be made to evaluate this therapy• e.g. BHAT

To determine whether chronic administration of proprandol to pts with at least one MI will reduce mortality due to all causes significantly over a 2 yr. follow up period.

• There may be more than one objective, some primary and some secondary.

3. Sample Size

Assumptions used, sources of data used & methods used to make the calculations

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Protocol (2)Protocol (2)4. Study Design

a. Recruitment• Entry Criteria - who are eligible• Exclusion Criteria - among those who are eligible, who should not be further

considered for various reasons• Statement of Informed Consent - patient must agree to all aspects of trial,

particularly to those things which will directly involve himb. Randomization Process

Description of the mechanics of how the patient is to be randomized and when (preferably as late as possible to avoid problems)

c. Baseline Evaluation• Clinical evaluation, history, & physical• Laboratory evaluation (e.g. EKG, X-ray, etc.)

Should describe what measurements are to be maded. Treatment Description

• Describe exactly how the two treatments are to be administered to the assigned patients, how often, dosage, etc.

e. Follow Up Schedule & EvaluationHow often are patients to be seen, by whom & what measurements are to be taken at each visit.

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Protocol (3)Protocol (3)

5. Data Monitoring

a. Toxicity: look for possible harmful effects; what variables will

be considered

b. Early Stopping: what mechanism, what endpoint will be

watched to assess whether a large early benefit has been detected, what statistical procedures

c. Quality Control: statement of procedures to insure data

obtained is of highest quality, usually involves laboratory

results mainly

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Protocol (4)Protocol (4)

6. Analysis Plans

State at least in rough terms what hypotheses will be tested and how in principle statistical methods will be used to answer these questions.

Avoids criticism of "data dredging”

Useful in pointing out potential problems in the analysis

problems; some may be avoided!

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Protocol (5)Protocol (5)7. Organizational Structure

Useful because it is then clear to everyone who is in charge of what, lines of authority and what are the governing rules

8. List of Participating Centers and Principle Investigators

"good public relations"

9. Data Monitoring & Committee Membership

10.Publication Policy who is acknowledged

who does the work what is editorial process what is study material and what belongs to each PI time schedule of publications

"Area most sensitive to young PI's"

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Protocol Example OutlineProtocol Example OutlineDiabetes Control & ComplicationsDiabetes Control & Complications

Trial (DCCT)Trial (DCCT)

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SUMMARY ii

SECTION page

1. INTRODUCTION 1.1

Scope and Impact of Diabetes 1.1

Background 1.3

Historical Perspective 1.4

Future Directions 1.7

2. OBJECTIVES AND DESIGN 2.1

Objectives 2.1

Design 2.2

3. SAMPLE SIZE 3.1

Introduction 3.1

Basis of Sample Size Calculations 3.2

Contents (DCCT) [1]Contents (DCCT) [1]

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4. PATIENT SELECTION AND RECRUITMENT 4.1

Introduction 4.1

Eligibility Criteria 4.1

Eligibility Criteria Applicable to Both Categories of Subject 4.1

For Patients Without Retinopathy 4.2

For Patients With Minimal Background Retinopathy 4.3

Exclusion Criteria 4.4

Exclusion Criteria Applicable to Both Categories of Subject 4.4

Exclusion Criteria for Patients Without Retinopathy 4.10

Additional Exclusion Criteria for Patients With Minimal

Background Retinopathy 4.10

Recruitment

5. INFORMED CONSENT 5.1

General Principles 5.1

Sequence of Procedures 5.3


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6.0 PRE-RANDOMIZATION EVALUATION 6.1


Laboratory 6.1

Ophthalmologic 6.2

Renal 6.2

Neurologic 6.3

Cardiovascular 6.3

Psychological 6.4

Compliance/Adherence 6.5

Dietary 6.6

Examination Results 6.6

Quality Control 6.6

7.0 RANDOMIZATION 7.1

Phase II Randomization 7.1

Considerations for Phase III 7.3

Ineligible Patients Who Are Randomized 7.4


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8.0 METABOLIC CONTROLIntervention Strategy in the Standard Group 8.1

Intervention Strategy 8.1Insulin 8.3Diet 8.4Exercise 8.5Urine Tests 8.5Self Blood Glucose Monitoring 8.5Clinic Visits 8.6Educational Program 8.6Protection of Subjects 8.6

Intervention Strategy in the Experimental Group 8.7General Guidelines 8.7Diet 8.10Exercise 8.10Urine Tests 8.10Self Blood Glucose Monitoring 8.11Clinic Visits 8.11

General Procedures to Maximize Adherence to Protocol 8.12


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9. FOLLOW-UP PROCEDURES FOR ENDPOINT VISITS 9.1


Blood Glucose Control 9.1

Ophthalmologic 9.2

Renal 9.3

Neurologic 9.3

Cardiovascular 9.4

Psychological 9.4

Compliance/Adherence 9.5

Dietary 9.6

Examination Results 9.6

Missed Visits 9.6

Transfer 9.6


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10. MONITORING PERFORMACE 10.1


Central Biochemistry Laboratory & Hemoglobin Alc Laboratory 10.1

Central Ophthalmologic Reading Unit 10.2

Other Central Units 10.3

Local Procedures 10.3

Clinical Centers 10.3

Coordinating Center 10.3

Correction of Deficiencies 10.4

11. MANAGEMENT OF INTERCURENT EVENTS 11.1


Guidelines 11.2


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12. DEVIATIONS FROM ASSIGNED TREATMENT 12.1

Introduction 12.1

Deviations for Experimental Treatment 12.1

Mandatory Situations 12.1

Allowable Situations 12.2

Treatment Policy 12.3

Deviations from the Standard Treatment 12.4

Mandatory Situations 12.4

Allowable Situations 12.4

Treatment Policy 12.4

Transfer to Inactive Status (both treatment groups) 12.5

Procedures for Deviation or Transfer to Inactive Status 12.6

13. RESULTS AND STATISTICAL ANALYSIS 13.1


Baseline Results and Analyses 13.1

Outcome Variables 13.2

Analysis Plan 13.3

Interim Analyses 13.5


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14. PUBLICATIONS AND PRESENTATIONS 14.1

Introduction 14.1

Duties of the Publications and Presentations Committee 14.1

Implementation 14.3

15. ANCIALLARY STUDIES 15.1

Introduction 15.1

Definition of an Ancillary Study 15.1

Reason for Requirement Approval 15.2

Levels of Approval Required for Ancillary Studies 15.2

Funding of Ancillary Study Results 15.3

Publication of Ancillary Study Results 15.3

Implementation 15.4

16. PROTOCOL CHANGES 16.1

Introduction 16.1

Policy 16.1

Procedures 16.1


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17. ADMINISTRATIVE STRUCTURE 17.1

Introduction 17.1

Structure 17.1

18. DISPOSITION OF DOCUMENTS, DATA, AND MATERIALS 18.1

Documents 18.1

Data Forms 18.1

Tapes of Data and Analysis Files 18.2

Laboratory Specimens 18.2

Photographs and Other Materials 18.3

Appendix page

A. …………………………………………………………………………… A.1

B. …………………………………………………………………………… B.1


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Trial OrganizationTrial Organization

• Components– sponsor– clinical centers– central resource units

• Administration– Steering Committee– Independent Data Monitoring Committee

• responsibilities• composition and independence

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Central Units (Labs, …)

Clinical Centers

NIH

Institutional Review Board

Policy Board

Data Monitoring Committee

Steering Committee

Coordinating Center

NIH Model

Patients

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Central Units (Labs, …)

Clinical Centers

Patients

Data Management Center (Sponsor or Contract Research

Organization)

Pharmaceutical Industry Sponsor

Institutional Review Board

Independent Data Monitoring

Committee (IDMC)

Steering Committee

Statistical Analysis Center (SAC)

Regulatory Agencies

Industry-Modified NIH Model

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Manual of Operations/ProceduresManual of Operations/Procedures

• Multiple may be needed– investigators– central resource units

• laboratory• Events Classification Committee ...

• Purpose - standardization of procedures– laboratory - quality of reagent, equipment

replacement, temporal drift, ...

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Trial Data CollectionTrial Data Collection

• Data collection forms or Case Report Forms (CRFs)

• Data Completeness• Data Integrity

• Important Note: Off Treatment does not mean Off Study

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Database Size (1)Database Size (1)

• Number of subjects– screened– enrolled

• Length of follow-up/ number of subject visits

• Number central resource items– Central blood measurements– Central pathology

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Database Size (2)Database Size (2)• Number of forms/patient

• Amount of coding of free text– adverse events– concomitant medications– logs, journals, recalls, ….

• Central adjudication– clinical events

• cause of death• severity of bleeding, ...

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Database RequirementsDatabase Requirements

• Integration of multiple data sources– clinic based– central resources– process

• Unique identification of patient

• Audit trails

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Data Collection Data Collection Also See Meinert Reference!

• Data collection must cover key questions or aspects1. Recruitment Process/Eligibility Screen2. Baseline Covariates

– Who was studied? (Eligibility)– Trt Balance? (Comparability)

3. Compliance– How did design get implemented?

4. Toxicity5. Primary and Secondary Outcomes6. Ancillary

• Two points in time- At or before randomization- Sometime after randomization

• Most trials collect too much data!

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Data CollectionData CollectionRecruitmentRecruitment

• Over optimism– Investigators usually overestimate number of patients they can recruit

• Recruitment Goals– Need to establish recruitment goals and have contingency plans– Good planning and interim monitoring

• Review Patient Admissions– Ask investigators to show patient admissions which meet entry

criteria, if possible

• Poor Recruitment Center– Usual reason is not enough patients screened– If a center can't recruit effectively, it may have to be dropped from

further efforts BUT don't throw out enrolled patients

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Data CollectionData CollectionEligibilityEligibility

• Modify Criteria– Changing entry criteria doesn't usually improve

recruitment that dramatically!

• Big Net– Need to screen "10 to 20" patients for every one

randomized | Big net required

• Can't "catch up”– Patient exposure to treatment lost due to lagging

recruitment

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Baseline Variables Baseline Variables (On Study Information)(On Study Information)

• All baseline data should be measured prior to randomization and start of therapy.

• Uses1. Eligibility (Based on a subset)2. Group comparability3. Stratified randomization4. Subgroup analysis5. Establish prognostic variables6. Evaluate changes from baseline for outcome or toxicity7. Comparing centers & different studies

• TimingShould be measured as close to start of therapy as possibleMay not be able to ascertain some variables

e.g. MILIS "infarct size" not possible at baseline

• May need 2 visits to confirm eligibility

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Data CollectionData CollectionPrimary-Secondary OutcomePrimary-Secondary Outcome

• Clear definitions

• Complete Ascertainment

• Possible Adjudication

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Data CollectionData CollectionAdverse EffectsAdverse Effects

• Many possible adverse effects may be monitored.A Multiple Comparisons Problem

• Not always as well defined (too many perhaps)• Anticipated + Unexpected• Natural history effects

BHAT 66% placebo patients shortness of breathonly 6% at baseline had history

Need control group

• Ascertainment– Eliciting vs. volunteer response– Length of follow-up– Frequency of patient contact

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Data CollectionData CollectionSubject ComplianceSubject Compliance

Perfect Compliance Unusual

1. Patients will not absolutely adhere to planned protocolRecruit "good" compliers

2. Try not to enter patients who would not be able to comply (Hard to predict!)

3. Once entered, try to minimize compliance problems

4. Patients can't be dropped from analysis because of non-compliance

5. Patient adherence must be carefully monitoreda. visitsb. pill count, amount of therapy consumedc. physiologic measurementsd. tracers

6. Off treatment does not mean off study!

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Data Collection-Data Collection-Quality Control (1)Quality Control (1)

No study is better than quality of its data

Focus energy on selected key variables

Strategies• Proper data collection forms• Data editing

a. Missing datab. Range checksc. Visual inspectiond. Consistency

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Data Collection-Data Collection-Quality Control (2)Quality Control (2)

• Training/Certification

a. Sites b. Items- Clinics - Protocol- Central labs - Data forms- Data center - Procedures

- Information flow

• Manual of operations-Clear definitions & instructions

• QC Procedures- Correct problems ASAP

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Data Form ConstructionData Form Construction

1. Need standard forms

2. Safeguards in construction

• Allow time for developing & testing• Solicit content advice• Review other RCT forms in similar trials• Pre-test before using

• Research record medical record

• Link each item with stated objective• Require adequate review before adding new items

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Data Item Construction (1)Data Item Construction (1)1. Every item should force a response

2. Terminology

• Keep it simple• Provide key definitions on form• If answer requires judgement or rating, provide basis• Use "yes" to indicate "presence of" (No double negative)• Indicate time frame

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Data Item Construction (2)Data Item Construction (2)3. Use of Existing Forms

• Don't reinvent the wheel if already used elsewhere• Don't use an entire form just because it exists• Get permission

4. Avoid open form - Use closed form• Use response checklist• Specify units of measurement (lbs. or kg.)• Enough boxes to specify adequate precision __._• Minimize calculations - obtain raw data

5. Use STOP & SKIP instructions

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Quality AssuranceQuality Assurance

• Timely Review

– Until recently, S.O.P. for industry was to collect data until trial was finished, then try to clean it up or do it in batches as CRAs visited sites

– Now QC can be an ongoing process

• QC Procedures

1. Visual check at clinic 6. Periodic QA reports v feedback

2. Visual check at data center 7. Submission of duplicate records

3. Double data entry 8. Comparison of clinics

4. Computer edit for admissible values 9. Re-certification of clinic personnel

5. Data edit queries back to clinic 10. Minimize lag time patient visit data entry

11. Audits

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Data EditingData Editing

1. Patient Identification & Record Linkage- Need internal check

2. Legibility

3. Form admissibility- Correct form, correct time window

4. Missing Information

5. Consistency- Consistent answers from form to form- Within one form/section to section

6. Ranges and Code Check- Codes legal- Responses within "acceptable" or "reasonable" range

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Audits/Data Integrity CheckAudits/Data Integrity Check

1. Comparison of data on computer file to data form (within data center)

2. Comparison of computer file to original medical record(at clinical center)

3. Often 10% random sample used (military audit)

-Do not disclose which 10% ahead of time

4. Data center integrity

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QC ReportQC Report

• Patient visits on schedule

• Procedures completed

• Timeliness of forms

– Clinic v data center

– Data center v data file

• Edit messages (by form)

– Completeness

– Legibility

– Errors

• Split/duplicate sample

• Audits

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Quality Assurance ActivitiesQuality Assurance Activities

• Monthly Reports– Clinical studies– Patient accrual information

• Data Corrections– Data monitoring and management– Database management

• Monthly Clinical Activity Summary Reports– Program area– Clinical Disease Group– Treating Physician

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Typical Case Report FormTypical Case Report Form

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Web

E-Mail

DataFax

Data Collectionand Management

OracleStudy Specific

Database

US Mail

Fax

Clinical Sites Coordinating Center

Data CollectionData CollectionData submitted on paper case report forms

Alternatives

Primary Method

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ONCORE: A Web Based SystemONCORE: A Web Based System

• Secure, fast web based system• Manages portfolio of cancer oriented protocols• Many functionalities

– Review & approval– Subject registration– Data collection– Analysis

• Started at UWCCC, now in 15 Centers• Local software company, Percipenz• www.oncore.org

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ConclusionConclusion

• Data collection personnel -- no matter how well-trained, careful, and proficient -- should not be expected to resolve all errors before their data are transmitted to a central database management site

• Centrally, someone must have big picture and also the little details

• Not paying attention to this can be the downfall of any trial

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Informed Consent ProcessInformed Consent Process

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Informed Consent ProcessInformed Consent Process

• A required process

• Failure to comply can result in serious consequences– Closure of trial– Closure of institution

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Informed ConsentInformed ConsentBasic ElementsBasic Elements

• Basic description of study• Description of risks• Description of benefits• Alternative therapies• Patient confidentiality• Compensation for injury• Contact Person• Voluntary participation

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Informed ConsentInformed ConsentAdditional ElementsAdditional Elements

• Any risk to fetus• Circumstances of termination of treatment• Additional costs• Consequences of patient withdrawal• Patient update of new relevant results• Number of subjects in trial

542-06-#1 STATISTICS 542 Introduction to Clinical Trials Protocols and Manual of Procedures.

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