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Experimental Studies


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Prepared forHSCI 330, SFU

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Experimental Studies

  1. 1. UPCOMING COURSE EVENTS • Group projects are due next Tuesday night (November 6th) by 11:59pm • Physical copies are due in class November 14th. • Be sure to include a copy of the rubric stapled to the front and the names and student numbers of each student in your group. • Group Peer Evaluations are also due in-class on November 14th. • Rashed will teach class on November 14th.
  2. 2. from the latin experiri – to try or test. Experiment (n)
  3. 3. INTRODUCTION TO EXPERIMENTAL RESEARCH • Clinical trials – Laboratory Experiments that occur in a clinical setting at the individual level. • Community trials – Field experiments that occur in the “natural” environment a the group level (e.g., school, classroom, or city). • Quasi-experimental studies – Studies that are similar to clinical trials, but lack some important element of control or experimentation.
  4. 4. INTRODUCTION TO EXPERIMENTAL RESEARCH Treated Observed Outcome Data Analysis No Outcome Untreated Recruitment Treatment Observation
  5. 5. INTRODUCTION TO EXPERIMENTAL RESEARCH • The Five Characteristics of a “True Experiment” are: • Has both an experimental group and a control group. • One groups gets the intervention, the other group does not. • Random assignment of individuals to the groups. • The degree to which random assignment ensures equivalence of the groups is dependent upon the size of the groups • The groups are measured on one or more dependent variables. • This is called the pretest. • The intervention (independent variable) is introduced. • The dependent variables are measured again. • This is the post test.
  6. 6. INTRODUCTION TO EXPERIMENTAL RESEARCH • Independent and dependent variables • IV is manipulated • DV is observed for change • Pre-testing and post-testing • To compare variation in DV before and after treatment • Experimental and control groups • Experimental group receives “treatment” and is compared to control group (no treatment).
  7. 7. • Clinical trials and experimentation date back thousands of years. • Modern clinical trials emerged in the 18th Century. • By the early 20th Century clinical trials had emerged as the gold standard of public health and medical research.
  8. 8. HISTORY OF EXPERIMENTS – 2ND CENTURY BCE • The first documented experiment resembling a clinical trial was conducted by King Nebuchadnezzar, a ruler of Babylon. • According to the “Book of Daniel” (200 BCE) Nebuchadnezzar (605 BC – c. 562 BC) ordered his people to eat only meat and drink only wine. • Some youth insisted that why be allowed to eat a diet of legumes and water, which he allowed. • After 10 days, he compared the health of the bean eaters to the meat eaters. Collier (2009) “Legumes, Lemons, and Streptomycin: A short history of the clinical trial.”
  9. 9. HISTORY OF EXPERIMENTS – 16TH CENTURY CE • In 1567, Ambroise Paré described an experiment to test the properties of bezoar stones. • At the time, the stones were commonly believed to be able to cure the effects of any poison, but Paré believed this to be impossible. • It happened that a cook at Paré's court was caught stealing fine silver cutlery, and was condemned to be hanged. • The cook agreed to be poisoned, on the conditions that he would be given a bezoar straight after the poison and go free in case he survived.
  10. 10. HISTORY OF EXPERIMENTS – 18TH CENTURY CE • James Lind was hired as a surgeon by the British East India Company • It was popularly believed that citrus fruit was a cure for scurvy. • When his ship was hit with a bout of scurvy, He divided twelve scorbutic sailors into six groups of two. • They all received the same diet but, in addition, • group one was given a quart of cider daily, • group two twenty-five drops of elixir of vitriol (sulfuric acid), • group three six spoonful's of vinegar, • group four half a pint of seawater, • group five received two oranges and one lemon, • and the last group a spicy paste plus a drink of barley water.
  11. 11. ETHICAL GUIDELINES IN EXPERIMENTAL RESEARCH • Nuremburg Code – 10 Principles • Required is the voluntary, well-informed, understanding consent of the human subject in a full legal capacity. • The experiment should aim at positive results for society that cannot be procured in some other way. • It should be based on previous knowledge (e.g., an expectation derived from animal experiments) that justifies the experiment. • The experiment should be set up in a way that avoids unnecessary physical and mental suffering and injuries, except, in experiments where the experimental physicians also serve as subjects. • It should not be conducted when there is any reason to believe that it implies a risk of death or disabling injury. • The risks of the experiment should be in proportion to (that is, not exceed) the expected humanitarian benefits. • Preparations and facilities must be provided that adequately protect the subjects against the experiment's risks. • The staff who conduct or take part in the experiment must be fully trained and scientifically qualified. • The human subjects must be free to immediately quit the experiment at any point when they feel physically or mentally unable to go on. • Likewise, the medical staff must stop the experiment at any point when they observe that continuation would be dangerous.
  12. 12. ETHICAL GUIDELINES IN EXPERIMENTAL RESEARCH • Declaration of Helsinki • The fundamental principle is • respect for the individual (Article 8), • their right to self-determination and the right to make informed decisions (Articles 20, 21 and 22) regarding participation in research, both initially and during the course of the research. • The investigator's duty is solely to the patient (Articles 2, 3 and 10) or volunteer (Articles 16, 18), and • while there is always a need for research (Article 6), • the subject's welfare must always take precedence over the interests of science and society (Article 5), • and ethical considerations must always take precedence over laws and regulations (Article 9).
  13. 13. ETHICAL GUIDELINES IN EXPERIMENTAL RESEARCH • Council for International Organizations and Medical Sciences (CIOMS) produced detailed guidelines (originally published in 1993 and updated in 2002). • Address complex issues including • HIV/AIDS research, • availability of study treatments after a study ends, • women as research subjects, • safeguarding confidentiality, • compensation for adverse events, • guidelines on consent.
  14. 14. ETHICAL GUIDELINES IN EXPERIMENTAL RESEARCH • To provide unified standard for European Union (EU), Japan and United States in facilitating mutual acceptance of clinical data-International Conference on Harmonisation (ICH). • Good Clinical Practice (GCP) guidelines was developed with consideration of Australia, Canada, Nordic countries and WHO. • GCP guidelines are like north star in the sky; we may never reach there but aim to reach (way to go).
  15. 15. • Clinical trials are probably the most famous type of experimental study. • Research studies involving people • Try to answer scientific questions and find better ways to prevent, diagnose, or treat disease • Translate results of basic scientific research into better ways to prevent, diagnose, or treat disease
  16. 16. DIFFERENT TYPES OF CLINICAL TRIALS • Therapeutic/Treatment trials – test new treatment, new combinations of drugs, or new approaches to surgery or radiation therapy (for people with a particular disease). • Prophylactic/Prevention trials – look for better ways to prevent disease in people who have never had the disease or to prevent a disease from returning. These approaches may include medicines, vitamins, vaccines, minerals or lifestyle changes. • Screening trials – test the best way to detect certain diseases or health conditions. • Quality of life trials ( or supportive care trials) – explore ways to improve comfort and the quality of life for individuals with a chronic illness 18
  17. 17. Drug development process • Investigational New drug (IND) • Pre clinical testing • Is the drug safe? • Affects other body systems? • Effective dose range? • Pharmacodynamics (effects of drugs and mechanism of action)? • Pharmacokinetics (movement of drugs within body)? • Is the drug a carcinogen (can cause cancer)? • Is the drug a teratogen (effects development of embryo)? • Long term animal studies confirms cancer or birth defects. • Regulators will want to know… • Description of drug • Chemistry • Preclinical information • Any previous human study • Investigators Brochure • Clinical development plan • Protocol and Investigator submission for first Phase-1 19
  18. 18. CLINICAL TRIALS Slide 20 0 I II III IV Effect on Body Safety + Dosing + Efficacy and Side effects Effectiveness, & Side Effects Usually <30 Patients 50 or so Participants 1,000’s of Participants Populations Biological Specimens / < 10 Participants 64% 75% 48% 40% 8% Success Rate ≃10 Years
  19. 19. CLINICAL TRIALS | PHASE I TRIALS • Unblinded, uncontrolled study with typically fewer than 30 patients • The purpose of phase I trials is to determine the safety of a test in humans • Patients in phase I trials often have advanced disease and have already tried other options • They often undergo intense monitoring
  20. 20. CLINICAL TRIALS | PHASE II TRIALS • Relatively small (up to 50 people) randomized blinded trials that test • Tolerability • Safe dosage • Side effects • How the body copes with the drug • Also evaluate which types of disease a treatment is effective against, further assess side effects and how they can be managed, and reveal the most effective dosage level
  21. 21. CLINICAL TRIALS | PHASE III TRIALS • Typically much larger and may involve thousands of patients • These trials typically involve random assignment and are used to evaluate the efficacy of a new treatment • Different dosages or methods of administration of the treatment are often part of the evaluation
  22. 22. CLINICAL TRIALS | PHASE IV TRIALS • A large study conducted after the therapy has been approved by the FDA to assess the rate of serious side effects, and explore further therapeutic uses
  23. 23. • Experimental design is a blueprint of the procedure that enables the researcher to test his hypothesis by reaching valid conclusions about relationships between independent and dependent variables. • Ethical considerations • Assembling study cohort • Measuring baseline variables • Choosing comparison group • Assuring Fidelity • Selecting treatment • Selecting patient population • Selecting outcome (endpoint)
  24. 24. ASSEMBLING STUDY COHORT • Inclusion criteria • Broad vs. specific – related to the extent of generalization • Is the outcome rare (e.g., CHD incidence)? Then recruit from populations at high risk such as males. • Exclusion criteria • Define exclusion criteria that will help control error. • Example: An advanced cancer that may be fatal before the end of the follow-up period in a subject entering a CHD-prevention study • Exclude those with difficulty in complying • Examples: Alcoholics, psychotic patients, individuals planning to move out of state • Sample size
  25. 25. MEASURING BASELINE VARIABLES • Characterize the study cohort • Identifying information (name, address, ID#) • Demographics (age, race, gender, etc.) • Clinical factors • The first table of a final report of any randomized blinded trial typically compares the level of baseline characteristics in the two study groups • Consider measuring the outcome variable • Change (appropriate for within-group design) • To assure disease is or is not present at baseline (appropriate for between-group design) • Measure various predictors of outcomes (e.g., smoking habits) to allow for statistical adjustment • Be parsimonious (i.e., keep simple)
  26. 26. CHOOSING COMPARISON GROUP • Not contaminated by treatment • Ideal – possible to blind, usually meaning placebo used • Status quo vs. new treatment
  27. 27. BETWEEN & WITHIN-GROUP DESIGN • Within-Group Designs – Outcome of a single group is compared before and after an assigned intervention. • Prone to time-related confounding factors (e.g., participants do better on follow-up cognitive tests because they learned from the baseline test). • Between-Group Designs – Outcomes between two or more groups of people receiving different levels of an intervention. • Prone to individual-related confounding factors (e.g., gender, race, genetic susceptibility).
  28. 28. ASSURING FIDELITY • Calling the day before clinical visit • Providing reimbursement • Adhering to the intervention protocol • Drug or behavioral intervention should be well tolerated • Taking once a day vs. complex schedule • Measuring compliance (self-report, pill counts, urinary metabolite levels)
  29. 29. SELECTING TREATMENT • What is the research objective? • Are the therapies safe and active against the disease? • Is there evidence that one therapy is better than another? • Is the intervention likely to be implemented in a clinical practice? • Is the intervention “strong” enough to have a chance of producing a detectable effect?
  30. 30. SELECTING PATIENT POPULATION • Often a compromise between • The population most efficient for answering the clinical question • The population best for generalizing the study findings • For example, many CHD-prevention trials do not include subjects over age 60 because such elderly subjects might already have extensive atheriosclerosis of their coronary arteries that would no longer be responsive to preventive efforts.
  31. 31. SELECTING OUTCOMES (ENDPOINTS) • Primary endpoint • For example, the primary endpoint for most phase III clinical trials in HIV disease is an AIDS-defining event or death • Major AIDS-defining events are: parasitic infections; fungal infections; bacterial infections; viral infections; neoplastic disease; HIV dementia; HIV wasting syndrome • Selection of the “best” endpoint is often complicated • Surrogate endpoint
  32. 32. RANDOMIZED CONTROLLED TRIALS Strengths Limitations Establishes temporal sequencing of events and thus provides strong evidence for causality. Removes confounding and selection bias by randomizing participants into experimental and control groups. Addresses error and bias through blinding and placebos. Can be replicated. Ethical limitations often prevent these studies from moving forward. Differential loss to follow up, due to declining interest, illness, or death may occur due to relative efficacy or inefficacy of intervention. Often recruit from optimally healthy populations. Study conditions often do not represent real world conditions. A successful clinical research process requires a lot of money, time, human and other resources and careful planning.
  33. 33. There are a number of factors to consider when thinking about the internal validity of an experiment. • History • Maturation • Pre-testing • Measuring instruments • Statistical regression • Differential selection • Experimental mortality • Interaction of factors
  34. 34. HISTORY • The events occurring between the first and second measurements in addition to the experimental variable which might affect the measurement.
  35. 35. MATURATION • The process of maturing which takes place in the individual during the duration of the experiment which is not a result of specific events but of simply growing older, growing tired or similar changes.
  36. 36. PRE-TESTING • The effect created on the second measurement by having a measurement before the experiment.
  37. 37. INSTRUMENTS • Changes in instruments, calibration of instruments, observers or scorers may cause changes in the measurements.
  38. 38. STATISTICAL REGRESSION • Where groups are chosen because of extreme scores of measurements, those scores tend to move toward the mean with repeated measurements even without an experimental variable.
  39. 39. DIFFERENTIAL SELECTION • Different individuals or groups have different previous knowledge or ability which would affect the final measurement if not taken into account.
  40. 40. EXPERIMENTAL MORTALITY • The loss of subjects from comparison groups could greatly affect the comparisons because of unique characteristics of those subjects. Groups to be compared need to be the same as before the experiment.
  41. 41. INTERACTION EFFECTS • Combinations of many of these factors may interact especially in multiple group comparisons to produce erroneous measurements.
  42. 42. There are a number of factors to consider when thinking about the internal validity of an experiment. • Pre-testing • Differential selection • Experimental procedures • Multiple treatment interference
  43. 43. PRE-TESTING • Individuals who were pre-tested might be less or more sensitive to the experimental variable or might have learned from the pre-test making them unrepresentative of the population who had not been pre-tested.
  44. 44. DIFFERENTIAL SELECTION • The selection of the subjects determines how the findings may be generalized. Subjects selected from a small group or one with particular characteristics would limit generalizability.
  45. 45. EXPERIMENTAL PROCEDURED • The experimental procedures and arrangements have a certain amount of effect on the subjects in the experimental settings.
  46. 46. MULTIPLE TREATMENT INTERFERENCE • If the subjects are exposed to more than one treatment, then the findings could only be generalized to individuals exposed to the same treatments in the same order of presentation.
  47. 47. • Experimental Control • Randomization • Blinding
  48. 48. • Random assignment makes intervention and control groups look as similar as possible • Chance is the only factor that determines group assignment • Neither the patient or the physician know in advance which prevention program or therapy will be assigned • Confounding and sample size
  49. 49. NON-RANDOMIZED STUDY • Also called convenience sample • Concurrent comparison group is allocated by a non-random process • Assignment • Problems • Not effective at controlling unmeasured confounding variables • Measured confounding variables; however, may be adjusted through analytic methods
  50. 50. ADVANTAGES AND DISADVANTAGES • Advantages of randomization • Eliminates conscious bias due to physician or patient selection • Averages out unconscious bias due to unknown factors • Groups are “alike on average” • Disadvantages of randomization • Ethical issues • Interferes with the doctor-patient relationship
  51. 51. • Experimental research is an attempt by the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. • All variables except the dependent variable are held constant (control). • Experimental control attempts to predict events that will occur in the experimental setting by neutralizing the effects of other factors.
  52. 52. CONTROL METHODS • If randomization on a variable is not possible, then controls are used: • Physical control • Gives all subjects equal exposure to the independent variable. • Controls non-experimental variables that effect the dependent variable. • Selective control • Indirectly manipulate by selecting in or out variables that cannot be controlled. • Statistical control • Variables not conducive to physical or selective manipulation may be controlled by statistical techniques.
  53. 53. Exposed Observation Outcome No Outcome Unexpose d Random AssignmentRecruitment Blinded Follow-up over Time Data Analysis
  54. 54. BLINDING • To blind patients, use a placebo; for example, • Pill of same size, color, shape as treatment • Sham operation (anesthesia and incision) for angina relief (unethical) • Three levels of blinding • Single blind – Subjects • In a single-blinded placebo-controlled study, the subjects are blinded but investigators are aware of who is receiving the active treatment • Double blind – Investigators • In a double-blind study, neither the subjects nor the investigators know who is receiving the active treatment • Triple blind – Analyses • In a triple-blind study, not only are the treatment and research approaches kept a secret from the subjects and investigators, but the analyses are completed in a manner that is removed from the investigators
  55. 55. BLINDING • Why blind patients? • Patients try to get well/please physicians • Minimize potential bias from a placebo effect • A placebo effect is defined as the effect on patient outcomes (improved or worsened) that may occur due to the expectation by a patient (or provider) that a particular intervention will have an effect • More subjective outcomes call for more serious consideration of placebo • For example, time to death vs. pain relief • Placebos improve comparability of treatment groups in terms of compliance and follow-up • For example, if patient perceives improvement because of medication, more likely to remain in study
  56. 56. BLINDING • Blinding physician or outcome assessing investigator • Best way to avoid unconscious bias is to blind • Physicians – don’t know which patient is taking the placebo and which patient is taking the drug • Assessors – of the outcome; are not the treating doctors, and are not told which treatment was used • Difficulties with Blinding • For non-drug studies, such as those involving behavior changes or surgery, it may be impossible or unethical to blind • It may also be problematic to blind in drug studies where a treatment has characteristic side effects • What if physician blinding is not possible (e.g., surgery or radiation trial)?
  57. 57. BLINDING • Strengths • Demonstrate cause-effect relationships • May produce a faster and cheaper answer than observational studies • Only appropriate approach for some research questions • Allow investigators to control the exposure levels as needed • Weaknesses • Often more costly in time and money • Many research questions are not suitable for experimental designs because of ethical barriers and because of rare outcomes • Many research questions are not suitable for blinding • Standardized interventions may be different from common practice • May have limited generalizability due to the use of volunteers, eligibility criteria, and loss to follow-up
  58. 58. Quasi experimental studies lack some characteristic of an experimental study. Many quasi-experimental designs exist (too many to cover in this class), but below are some common alterations: • Natural Experiments • Naturalistic Experiments • Run-in Design • 2x2 Factorial Design • Time-Series Design • Crossover Design • Non-Equivalent Group Designs • Randomized Matched Pair Design
  59. 59. VALIDITY OF QUASI EXPERIMENTAL STUDIES Internal Validity • Internal validity is reduced due to the presence of controlled/confounded variables • But not necessarily invalid • It’s important for the researcher to evaluate the likelihood that there are alternative hypotheses for observed differences • Need to convince self and audience of the validity External Validity • If the experimental setting more closely replicates the setting of interest, external validity can be higher than a true experiment run in a controlled lab setting • Often comes down to what is most important for the research question • Control or ecological validity?
  60. 60. NATURAL EXPERIMENTS • In some rare situations in nature, unplanned events produce a natural experiment • In naturalistic experiments, one contrives to collect experimental data under natural conditions. You make the data happen out in the natural world (not in the lab), and you evaluate the results. • Levels of exposure to a presumed cause differ among a population in a way that is relatively unaffected by extraneous factors so that the situation resembles a planned experiment • Natural experiments are happening around us all the time. • They are not conducted by researchers, but simply evaluated by researchers. • In other words, the researcher does not have control over the application of the treatment. • This also means that there is no control over what groups receive the treatment and the composition of those groups.
  61. 61. NATURALISTIC EXPERIMENTS • The difference between a natural experiment and a naturalistic experiment is that the first just happens, the second must be contrived to happen. • Naturalistic experiments deviate from true experiments because group membership is not randomly assigned, and exogenous factors (confounding variables) are not controlled.
  62. 62. RUN-IN DESIGN • All eligible participants are placed on placebo (or treatment). Those who remain in the study after some short period of time (e.g., days or weeks) are then randomly assigned to the different arms of the study. • The design is useful for minimizing bias due to loss of follow-up. • As some people are eliminated from the study, generalization of the results to a population of interest become limited. PRO CONTRA
  63. 63. 2x2 FACTORIAL DESIGN • Eligible participants are randomly assigned to one of four groups. The groups represent the different combinations of the two interventions. • This is an efficient design that allows to test two hypotheses for the price of one. • Interactions between the effects of the interaction on the outcomes can produced misleading results. PRO CONTRA
  64. 64. TIME SERIES DESIGN • Among the eligible participants, the outcome variables are measured, the intervention is applied to the whole cohort, the cohort is followed, and the outcome variables are again measured. • A single, non-randomized group minimizes the potential for confounding because each participant serves as his or her own control. • There is not a concurrent control group such that it is impossible to determine whether the intervention effect is attributed to a learning effect. PRO CONTRA
  65. 65. CROSSOVER STUDY DESIGN • A crossover design (also called a crossover trial) is a longitudinal study in which subjects receive a sequence of different treatments (or exposures). • This combines randomized and time- series design to improve control over confounding, and fewer participants are required to obtain a given level of power. • A doubling of time for the study is required and there is an added level of complexity required in the analysis and interpretation. PRO CONTRA
  66. 66. NON-EQUIVALENT GROUPS DESIGN • The intervention is randomly assigned to naturally forming clusters (e.g., schools, hospitals, communities) • Helps control for confounding factors. • Sample size estimation and data analysis are more complicated than for individual-level randomization. In addition, the sample size required to maintain adequate statistical power is larger than with individual level randomization. PRO CONTRA
  67. 67. RANDOMIZED MATCHED PAIRED DESIGN • Eligible participants are matched in pairs according to some potential confounding founder (e.g., age sex, ethnicity). • Improves balance among groups on potential confounding variables. • Matching complicates the study at the design and analysis level and is unnecessary to control for confounding when the sample size is sufficiently large. PRO CONTRA
  68. 68. • An adaptive design is a design that allows modification (adaptation) to some aspects (e.g., trial and/or statistical procedures) of on-going trials after initiation without undermining the validity and integrity of the trials. • Adaptations are made based on pre-determined criteria.
  69. 69. ADAPTATION • An adaptation is defined as a change or modification made to a clinical trial before and during the conduct of the study. • Relax inclusion/exclusion criteria • Change study endpoints • Stopping trial early due to safety, futility, or efficacy • Modify dose and treatment duration
  70. 70. TYPES OF ADAPTIVE DESIGNS • Adaptive randomization design • Group sequential design • Flexible sample size re-estimation design • Drop-the-losers (pick-the-winner) design • Adaptive dose-finding design • Biomarker-adaptive design • Adaptive treatment-switching design • Adaptive-hypotheses design • Adaptive seamless design • Two-stage phase I/II (or II/III) adaptive design • Multiple adaptive design (any combinations of the above designs)
  71. 71. ADAPTIVE RANDOMIZATION DESIGN • A design that allows modification of randomization schedules (during the conduct of the trial) • Increase the probability of success • Type of adaptive randomization • Treatment-adaptive • Covariate-adaptive • Response-adaptive
  72. 72. GROUP SEQUENTIAL DESIGN • An adaptive design that allows for (i) prematurely stopping a trial due to • safety, • futility/efficacy, or • both • based on interim analysis results, and (ii) sample size re-estimation either in a blinded fashion or a unblinded fashion, which often conducted by an independent data monitoring committee (IDMC)
  73. 73. FLEXIBLE SAMPLE SIZE RE-ESTIMATION DESIGN • An adaptive design that allows for sample size adjustment or re-estimation based on the observed data at interim • Sample size adjustment or re-estimation is usually performed based on the following criteria • Controlling variability • Maintaining treatment effect • Achieving conditional power • Reaching desired reproducibility probability • Other criteria such as probability statement
  74. 74. DROP-THE-LOSERS DESIGN • Drop-the-losers design is a multiple stage adaptive design that allows dropping the inferior treatment groups • drop the inferior arms • retain the control arm • may modify current treatment arms • may add additional arms • It is useful where there are uncertainties regarding the dose levels.
  75. 75. ADAPTIVE DOSE FINDING DESIGN • Often used in early phase clinical development to identify the maximum tolerable dose (MTD), which is usually considered the optimal dose for later phase clinical trials • Adaptive dose finding designs often used in cancer clinical trials • Dose escalation designs • Bayesian sequential designs
  76. 76. BIOMARKER- ADAPTIVE DESIGN • A design that allows for adaptation based on the responses of biomarkers such as pharmacokinetic (PK) and pharmacodynamics (PD) markers and genomic markers • Types of biomarker • Classifier marker • Prognostic marker • Predictive marker
  77. 77. ADAPTIVE TREATMENT-SWITCHING DESIGN • A design that allows the investigator to switch a patient’s treatment from an initial assignment to an alternative treatment if there is evidence of lack of efficacy or safety of the initial treatment • commonly employed in cancer trials
  78. 78. ADAPTIVE-HYPOTHESES DESIGN • A design that allows change in hypotheses based on interim analysis results • often considered before database lock and/or prior to data unblinding • Examples • switch from a superiority hypothesis to a non-inferiority hypothesis • change in study endpoints (e.g., switch primary and secondary endpoints)
  79. 79. ADAPTIVE SEAMLESS DESIGN • An adaptive seamless design is a trial design that combines two separate independent trials into one single study • The single study would be able to address study objectives of individual studies • This design usually consists of two phases (stages) • Learning (exploratory) phase • Confirmatory phase • This design is known as a two-stage adaptive seamless design
  80. 80. MULTIPLE ADAPTIVE DESIGN • A multiple adaptive design is any combinations of the above adaptive designs • very flexible • very attractive • very complicated • statistical inference is often difficult, if not impossible to obtain