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Chapter 7 Protocols and Manual of Procedures

Chapter 7 Protocols and Manual of Procedures. Protocol vs Manual of Operations Analogy. Protocol is general “blueprint” ( 藍圖 ) for investigators + institutional review boards(IRB) sponsor regulatory agencies Manual of Procedures is detailed “construction document” clinic staff

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Chapter 7 Protocols and Manual of Procedures

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  1. Chapter 7Protocols andManual of Procedures 1

  2. Protocol vs Manual of Operations Analogy • Protocol is general “blueprint” (藍圖) for • investigators + institutional review boards(IRB) • sponsor • regulatory agencies • Manual of Procedures is detailed “construction document” • clinic staff • data management staff 2

  3. Desirable Protocol Characteristics • Clear • Consistent • Complete 3

  4. Scale Implications • “Simple” • One investigator, one patient, one encounter • “Harder” • Multiple investigators, multiple patients, multiple visits, multiple cultures, multiple languages 4

  5. Considerations During Protocol 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 5

  6. 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 6

  7. 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 him b. 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 made d. Treatment Description • Describe exactly how the two treatments are to be administered to the assigned patients, how often, dosage, etc. e. Follow Up Schedule & Evaluation How often are patients to be seen, by whom & what measurements are to be taken at each visit. 7

  8. 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 8

  9. 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. C Avoids criticism of “data dredging” (清淤) C Useful in pointing out potential problems in the analysis problems; some may be avoided! 9

  10. 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 C who is acknowledged C who does the work C what is editorial process C what is study material and what belongs to each PI C time schedule of publications "Area most sensitive to young PI's" 10

  11. Protocol Example OutlineDiabetes Control & ComplicationsTrial (DCCT) 11

  12. Contents (DCCT) [1] 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 12

  13. Contents (DCCT) [2] 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 13

  14. Contents (DCCT) [3] 6.0 PRE-RANDOMIZATION EVALUATION 6.1 General Principles 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 14

  15. Contents (DCCT) [4] 8.0 METABOLIC CONTROL Intervention Strategy in the Standard Group 8.1 Intervention Strategy 8.1 Insulin 8.3 Diet 8.4 Exercise 8.5 Urine Tests 8.5 Self Blood Glucose Monitoring 8.5 Clinic Visits 8.6 Educational Program 8.6 Protection of Subjects 8.6 Intervention Strategy in the Experimental Group 8.7 General Guidelines 8.7 Diet 8.10 Exercise 8.10 Urine Tests 8.10 Self Blood Glucose Monitoring 8.11 Clinic Visits 8.11 General Procedures to Maximize Adherence to Protocol 8.12 15

  16. Contents (DCCT) [5] 9. FOLLOW-UP PROCEDURES FOR ENDPOINT VISITS 9.1 General Principles 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 16

  17. Contents (DCCT) [6] 10. MONITORING PERFORMACE 10.1 General Principles 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 General Principles 11.1 Guidelines 11.2 17

  18. Contents (DCCT) [7] 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 General Principles 13.1 Baseline Results and Analyses 13.1 Outcome Variables 13.2 Analysis Plan 13.3 Interim Analyses 13.5 18

  19. Contents (DCCT) [8] 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 19

  20. Contents (DCCT) [9] 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 20

  21. T1303 第四期鼻咽癌誘導式化療加上同步化學放射治療 與單獨同步化學放射治療的比較 計畫主持人： 台大醫院腫瘤部 洪瑞隆 醫師 長庚醫院內科部血液腫瘤科 王正旭 醫師 台大醫院耳鼻喉部 徐茂銘 教授 Study Bio-Statistician： Chin-FYu HsiaoLin, Ph.D. 蕭金福博士 21

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  30. Trial Organization • Components • sponsor • clinical centers • central resource units • Administration • Steering Committee • Independent Data Monitoring Committee • responsibilities • composition and independence • physician, statistician, … 30

  31. NIH Model Steering Committee NIH Policy Board Data Monitoring Committee Coordinating Center Central Units (Labs, …) Clinical Centers Institutional Review Board Patients 31

  32. Industry-Modified NIH Model Steering Committee Pharmaceutical Industry Sponsor Regulatory Agencies Independent Data Monitoring Committee (IDMC) Statistical Analysis Center (SAC) Data Management Center (Sponsor or Contract Research Organization) Central Units (Labs, …) Clinical Centers Institutional Review Board Patients 32

  33. Manual 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, ... 33

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  35. Trial Data Collection • Data collection forms or Case Report Forms (CRFs) • Data Completeness • Data Integrity (完整性) • Important Note: Off Treatment does not mean Off Study 35

  36. 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 (病理學) 36

  37. Database Size (2) • Number of forms/patient • Amount of coding of free text • adverse events (MEDRA?) • concomitant medications (WHO?) • logs, journals, recalls, …. • Central adjudication (裁定) • clinical events • cause of death • severity of bleeding, ... 37

  38. Database Requirements • Integration of multiple data sources • clinic based • central resources • process • Unique identification of patient • Audit trails 38

  39. Data Collection Also See Meinert Reference! • Data collection must cover key questions or aspects 1. Recruitment Process/Eligibility Screen 2. Baseline Covariates • Who was studied? (Eligibility) • Trt Balance? (Comparability) 3. Compliance • How did design get implemented? 4. Toxicity 5. Primary and Secondary Outcomes 6. Ancillary • Two points in time - At or before randomization - Sometime after randomization • Most trials collect too much data! 39

  40. Data CollectionRecruitment • 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 40

  41. Data CollectionEligibility • 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 (落後) recruitment 41

  42. Baseline Variables (On Study Information) • All baseline data should be measured prior to randomization and start of therapy. • Uses 1. Eligibility (Based on a subset) 2. Group comparability 3. Stratified randomization 4. Subgroup analysis 5. Establish prognostic variables 6. Evaluate changes from baseline for outcome or toxicity 7. Comparing centers & different studies • Timing Should be measured as close to start of therapy as possible May not be able to ascertain some variables e.g. MILIS "infarct size" not possible at baseline • May need 2 visits to confirm eligibility 42

  43. Data CollectionPrimary-Secondary Outcome • Clear definitions • Complete Ascertainment • Possible Adjudication 43

  44. Data CollectionAdverse 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 breath only 6% at baseline had history  Need control group • Ascertainment • Eliciting (誘引)vs. volunteer response • Length of follow-up • Frequency of patient contact 44

  45. Data CollectionSubject Compliance Perfect Compliance Unusual 1. Patients will not absolutely adhere to planned protocol Recruit "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 monitored a. visits b. pill count, amount of therapy consumed c. physiologic (生理)measurements d. tracers 6. Off treatment does not mean off study! 45

  46. Data Collection-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 data b. Range checks c. Visual inspection d. Consistency 46

  47. Data Collection-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 47

  48. Data Form Construction 1. Need standard forms 2. Safeguards in construction • Allow time for developing & testing • Solicit (徵求) 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 48

  49. Data Item Construction (1) 1. Every item should force a response 2. Terminology (術語) • 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 49

  50. 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 50

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