1、Basics of Study DesignJanice Weinberg ScDAssistant Professor of BiostatisticsBoston University School of Public HealthBasics of Study Design Bias and variability Randomization:why and how?Blinding:why and how?General study designsBias and Variability The clinical trial is considered to be the“gold s
2、tandard”in clinical research Clinical trials provide the ability to reduce bias and variability that can obscure the true effects of treatment Bias affects accuracy Variability affects precision Bias:any influence which acts to make the observed results non-representative of the true effect of thera
3、py Examples:healthier patients given treatment A,sicker patients given treatment B treatment A is“new and exciting”so both the physician and the patient expect better results on A Many potential sources of bias Variability:high variability makes it more difficult to discern treatment differences Som
4、e sources of variability Measurement instrument observer Biologic within individuals between individuals Can not always control for all sources(and may not want to)Fundamental principle in comparing treatment groups:Groups must be alike in all important aspects and only differ in the treatment each
5、group receives In practical terms,“comparable treatment groups”means“alike on the average”Why is this important?If there is a group imbalance for an important factor then an observed treatment difference may be due to the imbalance rather than the effect of treatment Example:Drug X versus placebo fo
6、r osteoporosis Age is a risk factor for osteoporosis Older subjects are enrolled in Drug X group Treatment group comparison will be biased due to imbalance on ageHow can we ensure comparability of treatment groups?We can not ensure comparability but randomization helps to balance all factors between
7、 treatment groups If randomization“works”then groups will be similar in all aspects except for the treatment receivedRandomization Allocation of treatments to participants is carried out using a chance mechanism so that neither the patient nor the physician know in advance which therapy will be assi
8、gned Simplest Case:each patient has the same chance of receiving any of the treatments under studySimple Randomization Think of tossing a coin each time a subject is eligible to be randomized HEADS:Treatment A TAILS:Treatment B Approximately will be assigned to treatments A and B Randomization usual
9、ly done using a randomization schedule or a computerized random number generatorProblem with Simple Randomization:May result in substantial imbalance in either an important baseline factor and/or the number of subjects assigned to each group Solution:Use blocking and/or stratified randomizationBlock
10、ing Example:If we have two treatment groups (A and B)equal allocation,and a block size of 4,random assignments would be chosen from the blocks 1)AABB 4)BABA 2)ABAB 5)BAAB 3)ABBA 6)BABA Blocking ensures balance after every 4th assignmentStratification Example To ensure balance on an important baselin
11、e factor,create strata and set up separate randomization schedules within each stratum Example:if we want prevent an imbalance on age in an osteoporosis study,first create the strata“75 years”and“75 years”then randomize within each stratum separately Blocking should be also be used within each strat
12、um Alternatives to Randomization Randomization is not always possible due to ethical or practical considerations Some alternatives:Historical controls Non-randomized concurrent controls Different treatment per physician Systematic alternation of treatments Sources of bias for these alternatives need
13、 to be consideredBlinding Masking the identity of the assigned interventions Main goal:avoid potential bias caused by conscious or subconscious factors Single blind:patient is blinded Double blind:patient and assessing investigator are blinded Triple blind:committee monitoring response variables(e.g
14、.statistician)is also blindedHow to Blind To“blind”patients,can use a placebo Examples pill of same size,color,shape as treatment sham operation(anesthesia and incision)for angina relief sham device such as sham acupuncture Why Should Patients be Blinded?Patients who know they are receiving a new or
15、 experimental intervention may report more(or less)side effects Patients not on new or experimental treatment may be more(or less)likely to drop out of the study Patient may have preconceived notions about the benefits of therapy Patients try to get well/please physicians Placebo effect response to
16、medical intervention which results from the intervention itself,not from the specific mechanism of action of the intervention Example:Fisher R.W.JAMA 1968;203:418-419 46 patients with chronic severe itching randomly given one of four treatments High itching score=more itching TreatmentItching Score
17、cyproheptadine HCI27.6 trimeprazine tartrate34.6 placebo30.4 nothing49.6Why Should Investigators be Blinded?Treating physicians and outcome assessing investigators are often the same people Possibility of unconscious bias in assessing outcome is difficult to rule out Decisions about concomitant/comp
18、ensatory treatment are often made by someone who knows the treatment assignment “Compensatory”treatment may be given more often to patients on the protocol arm perceived to be less effectiveCan Blinding Always be Done?In some studies it may be impossible(or unethical)to blind a treatment may have ch
19、aracteristic side effects it may be difficult to blind the physician in a surgery or device study Sources of bias in an un-blinded study must be consideredGeneral Study Designs Many clinical trial study designs fall into the categories of parallel group,dose-ranging,cross-over and factorial designs
20、There are many other possible designs and variations on these designs We will consider the general casesGeneral Study Designs Parallel group designsR A N D A B C control General Study Designs Dose-Ranging StudiesR A N D high dose medium dose low dose control General Study Designs Cross-Over DesignsR
21、 A N D A B B A WASH-OUT General Study Designs Factorial DesignsR A N D A+B A+control B+control control+control Cross-Over Designs Subjects are randomized to sequences of treatments(A then B or B then A)Uses the patient as his/her own control Often a“wash-out”period(time between treatment periods)is
22、used to avoid a“carry over”effect(the effect of treatment in the first period affecting outcomes in the second period)Can have a cross-over design with more than 2 periodsCross-Over Designs Advantage:treatment comparison is only subject to within-subject variability not between-subject variability r
23、educed sample sizes Disadvantages:strict assumption about carry-over effects inappropriate for certain acute diseases(where a condition may be cured during the first period)drop outs before second periodCross-Over Designs Appropriate for conditions that are expected to return to baseline levels at t
24、he beginning of the second period Examples:Treatment of chronic pain Comparison of hearing aids for hearing loss Mouth wash treatment for gingivitisFactorial Designs Attempts to evaluate two interventions compared to a control in a single experiment(simplest case)An important concept for these desig
25、ns is interaction(sometimes called effect modification)Interaction:The effect of treatment A differs depending upon the presence or absence of intervention B and vice-versa.Factorial Designs Advantages:If no interaction,can perform two experiments with less patients than performing two separate expe
26、riments Can examine interactions if this is of interest Disadvantages:Added complexity potential for adverse effects due to“poly-pharmacy”Factorial Designs Example:Physicians Health Study Physicians randomized to:aspirin(to prevent cardiovascular disease)beta-carotene(to prevent cancer)aspirin and beta-carotene neither(placebo)Stampfer,Buring,Willett,Rosner,Eberlein and Hennekens(1985)The 2x2 factorial design:its application to a randomized trial of aspirin and carotene in U.S.physicians.Stat.in Med.9:111-116.
