版權(quán)說明:本文檔由用戶提供并上傳,收益歸屬內(nèi)容提供方,若內(nèi)容存在侵權(quán),請進(jìn)行舉報(bào)或認(rèn)領(lǐng)
文檔簡介
BasicsofStudyDesignJaniceWeinbergScDAssistantProfessorofBiostatisticsBostonUniversitySchoolofPublicHealthBasicsofStudyDesignJaniceW1BasicsofStudyDesignBiasandvariabilityRandomization:whyandhow?Blinding:whyandhow?GeneralstudydesignsBasicsofStudyDesignBiasand2BiasandVariabilityTheclinicaltrialisconsideredtobethe“goldstandard”inclinicalresearchClinicaltrialsprovidetheabilitytoreducebiasandvariabilitythatcanobscurethetrueeffectsoftreatmentBiasaffectsaccuracyVariabilityaffectsprecisionBiasandVariabilityTheclinic3Bias:anyinfluencewhichactstomaketheobservedresultsnon-representativeofthetrueeffectoftherapy
Examples:healthierpatientsgiventreatmentA,sickerpatientsgiventreatmentBtreatmentAis“newandexciting”soboththephysicianandthepatientexpectbetterresultsonAManypotentialsourcesofbiasBias:anyinfluencewhichacts4Variability:highvariabilitymakesitmoredifficulttodiscerntreatmentdifferencesSomesourcesofvariabilityMeasurementinstrumentobserverBiologicwithinindividualsbetweenindividualsCannotalwayscontrolforallsources(andmaynotwantto)Variability:highvariability5Fundamentalprinciple
incomparingtreatmentgroups:GroupsmustbealikeinallimportantaspectsandonlydifferinthetreatmenteachgroupreceivesInpracticalterms,“comparabletreatmentgroups”means“alikeontheaverage”Fundamentalprinciple
incomp6Whyisthisimportant?IfthereisagroupimbalanceforanimportantfactorthenanobservedtreatmentdifferencemaybeduetotheimbalanceratherthantheeffectoftreatmentExample:DrugXversusplaceboforosteoporosisAgeisariskfactorforosteoporosisOldersubjectsareenrolledinDrugXgroupTreatmentgroupcomparisonwillbebiasedduetoimbalanceonageWhyisthisimportant?Ifthere7Howcanweensurecomparabilityoftreatmentgroups?WecannotensurecomparabilitybutrandomizationhelpstobalanceallfactorsbetweentreatmentgroupsIfrandomization“works”thengroupswillbesimilarinallaspectsexceptforthetreatmentreceivedHowcanweensurecomparabilit8RandomizationAllocationoftreatmentstoparticipantsiscarriedoutusingachancemechanismsothatneitherthepatientnorthephysicianknowinadvancewhichtherapywillbeassignedSimplestCase:eachpatienthasthesamechanceofreceivinganyofthetreatmentsunderstudyRandomizationAllocationoftre9SimpleRandomizationThinkoftossingacoineachtimeasubjectiseligibletoberandomizedHEADS: TreatmentATAILS: TreatmentBApproximately?willbeassignedtotreatmentsAandBRandomizationusuallydoneusingarandomizationscheduleoracomputerizedrandomnumbergeneratorSimpleRandomizationThinkoft10ProblemwithSimpleRandomization:Mayresultinsubstantialimbalanceineitheranimportantbaselinefactorand/orthenumberofsubjectsassignedtoeachgroupSolution:Useblockingand/orstratifiedrandomizationProblemwithSimpleRandomizat11BlockingExample:Ifwehavetwotreatmentgroups(AandB)equalallocation,andablocksizeof4,randomassignmentswouldbechosenfromtheblocks1)AABB 4)BABA2)ABAB 5)BAAB3)ABBA 6)BABABlockingensuresbalanceafterevery4thassignmentBlockingExample:Ifwehavetw12StratificationExampleToensurebalanceonanimportantbaselinefactor,createstrataandsetupseparaterandomizationscheduleswithineachstratumExample:ifwewantpreventanimbalanceonageinanosteoporosisstudy,firstcreatethestrata“<75years”and“75years”thenrandomizewithineachstratumseparatelyBlockingshouldbealsobeusedwithineachstratumStratificationExampleToensur13AlternativestoRandomizationRandomizationisnotalwayspossibleduetoethicalorpracticalconsiderationsSomealternatives:HistoricalcontrolsNon-randomizedconcurrentcontrolsDifferenttreatmentperphysicianSystematicalternationoftreatmentsSourcesofbiasforthesealternativesneedtobeconsideredAlternativestoRandomizationR14BlindingMaskingtheidentityoftheassignedinterventionsMaingoal:avoidpotentialbiascausedbyconsciousorsubconsciousfactorsSingleblind: patientisblindedDouble
blind: patientandassessing investigatorareblindedTriple
blind: committeemonitoring responsevariables(e.g. statistician)isalsoblindedBlindingMaskingtheidentityo15HowtoBlindTo“blind”patients,canuseaplaceboExamplespillofsamesize,color,shapeastreatmentshamoperation(anesthesiaandincision)foranginareliefshamdevicesuchasshamacupuncture
HowtoBlindTo“blind”patient16WhyShouldPatientsbeBlinded?Patientswhoknowtheyarereceivinganeworexperimentalinterventionmayreportmore(orless)sideeffectsPatientsnotonneworexperimentaltreatmentmaybemore(orless)likelytodropoutofthestudyPatientmayhavepreconceivednotionsaboutthebenefitsoftherapyPatientstrytogetwell/pleasephysiciansWhyShouldPatientsbeBlinded17Placeboeffect–responsetomedicalinterventionwhichresultsfromtheinterventionitself,notfromthespecificmechanismofactionoftheinterventionExample:FisherR.W.JAMA1968;203:418-419
46patientswithchronicsevereitchingrandomlygivenoneoffourtreatmentsHighitchingscore=moreitchingTreatment ItchingScore cyproheptadineHCI 27.6 trimeprazinetartrate 34.6 placebo 30.4 nothing 49.6Placeboeffect–responsetom18WhyShouldInvestigatorsbeBlinded?TreatingphysiciansandoutcomeassessinginvestigatorsareoftenthesamepeoplePossibilityofunconsciousbiasinassessingoutcomeisdifficulttoruleoutDecisionsaboutconcomitant/compensatorytreatmentareoftenmadebysomeonewhoknowsthetreatmentassignment“Compensatory”treatmentmaybegivenmoreoftentopatientsontheprotocolarmperceivedtobelesseffectiveWhyShouldInvestigatorsbeBl19CanBlindingAlwaysbeDone?Insomestudiesitmaybeimpossible(orunethical)toblindatreatmentmayhavecharacteristicsideeffectsitmaybedifficulttoblindthephysicianinasurgeryordevicestudySourcesofbiasinanun-blindedstudymustbeconsideredCanBlindingAlwaysbeDone?In20GeneralStudyDesignsManyclinicaltrialstudydesignsfallintothecategoriesofparallelgroup,dose-ranging,cross-overandfactorialdesignsTherearemanyotherpossibledesignsandvariationsonthesedesignsWewillconsiderthegeneralcasesGeneralStudyDesignsManyclin21GeneralStudyDesignsParallelgroupdesignsGeneralStudyDesignsParallel22GeneralStudyDesignsDose-RangingStudiesGeneralStudyDesignsDose-Rang23GeneralStudyDesignsCross-OverDesignsGeneralStudyDesignsCross-Ove24GeneralStudyDesignsFactorialDesignsGeneralStudyDesignsFactorial25Cross-OverDesignsSubjectsarerandomizedtosequencesoftreatments(AthenBorBthenA)Usesthepatientashis/herowncontrolOftena“wash-out”period(timebetweentreatmentperiods)isusedtoavoida“carryover”effect(theeffectoftreatmentinthefirstperiodaffectingoutcomesinthesecondperiod)Canhaveacross-overdesignwithmorethan2periodsCross-OverDesignsSubjectsare26Cross-OverDesignsAdvantage:treatmentcomparisonisonlysubjecttowithin-subjectvariabilitynotbetween-subjectvariabilityreducedsamplesizesDisadvantages:strictassumptionaboutcarry-overeffectsinappropriateforcertainacutediseases(whereaconditionmaybecuredduringthefirstperiod)dropoutsbeforesecondperiodCross-OverDesignsAdvantage:t27Cross-OverDesignsAppropriateforconditionsthatareexpectedtoreturntobaselinelevelsatthebeginningofthesecondperiodExamples:TreatmentofchronicpainComparisonofhearingaidsforhearinglossMouthwashtreatmentforgingivitisCross-OverDesignsAppropriate28FactorialDesignsAttemptstoevaluatetwointerventionscomparedtoacontrolinasingleexperiment(simplestcase)Animportantconceptforthesedesignsisinteraction(sometimescalledeffectmodification)Interaction:TheeffectoftreatmentAdiffersdependinguponthepresenceorabsenceofinterventionBandvice-versa.FactorialDesignsAttemptstoe29FactorialDesignsAdvantages:Ifnointeraction,canperformtwoexperimentswithlesspatientsthanperformingtwoseparateexperimentsCanexamineinteractionsifthisisofinterestDisadvantages:Addedcomplexitypotentialforadverseeffectsdueto“poly-pharmacy”FactorialDesignsAdvantages:30FactorialDesignsExample:Physician’sHealthStudyPhysiciansrandomizedto:aspirin(topreventcardiovasculardisease)beta-carotene(topreventcancer)aspirinandbeta-caroteneneither(placebo)Stampfer,Buring,Willett,Rosner,EberleinandHennekens(1985)The2x2factorialdesign:it’sapplicationtoarandomizedtrialofaspirinandcaroteneinU.S.physicians.Stat.inMed.9:111-116.FactorialDesignsExample:Phy31BasicsofStudyDesignJaniceWeinbergScDAssistantProfessorofBiostatisticsBostonUniversitySchoolofPublicHealthBasicsofStudyDesignJaniceW32BasicsofStudyDesignBiasandvariabilityRandomization:whyandhow?Blinding:whyandhow?GeneralstudydesignsBasicsofStudyDesignBiasand33BiasandVariabilityTheclinicaltrialisconsideredtobethe“goldstandard”inclinicalresearchClinicaltrialsprovidetheabilitytoreducebiasandvariabilitythatcanobscurethetrueeffectsoftreatmentBiasaffectsaccuracyVariabilityaffectsprecisionBiasandVariabilityTheclinic34Bias:anyinfluencewhichactstomaketheobservedresultsnon-representativeofthetrueeffectoftherapy
Examples:healthierpatientsgiventreatmentA,sickerpatientsgiventreatmentBtreatmentAis“newandexciting”soboththephysicianandthepatientexpectbetterresultsonAManypotentialsourcesofbiasBias:anyinfluencewhichacts35Variability:highvariabilitymakesitmoredifficulttodiscerntreatmentdifferencesSomesourcesofvariabilityMeasurementinstrumentobserverBiologicwithinindividualsbetweenindividualsCannotalwayscontrolforallsources(andmaynotwantto)Variability:highvariability36Fundamentalprinciple
incomparingtreatmentgroups:GroupsmustbealikeinallimportantaspectsandonlydifferinthetreatmenteachgroupreceivesInpracticalterms,“comparabletreatmentgroups”means“alikeontheaverage”Fundamentalprinciple
incomp37Whyisthisimportant?IfthereisagroupimbalanceforanimportantfactorthenanobservedtreatmentdifferencemaybeduetotheimbalanceratherthantheeffectoftreatmentExample:DrugXversusplaceboforosteoporosisAgeisariskfactorforosteoporosisOldersubjectsareenrolledinDrugXgroupTreatmentgroupcomparisonwillbebiasedduetoimbalanceonageWhyisthisimportant?Ifthere38Howcanweensurecomparabilityoftreatmentgroups?WecannotensurecomparabilitybutrandomizationhelpstobalanceallfactorsbetweentreatmentgroupsIfrandomization“works”thengroupswillbesimilarinallaspectsexceptforthetreatmentreceivedHowcanweensurecomparabilit39RandomizationAllocationoftreatmentstoparticipantsiscarriedoutusingachancemechanismsothatneitherthepatientnorthephysicianknowinadvancewhichtherapywillbeassignedSimplestCase:eachpatienthasthesamechanceofreceivinganyofthetreatmentsunderstudyRandomizationAllocationoftre40SimpleRandomizationThinkoftossingacoineachtimeasubjectiseligibletoberandomizedHEADS: TreatmentATAILS: TreatmentBApproximately?willbeassignedtotreatmentsAandBRandomizationusuallydoneusingarandomizationscheduleoracomputerizedrandomnumbergeneratorSimpleRandomizationThinkoft41ProblemwithSimpleRandomization:Mayresultinsubstantialimbalanceineitheranimportantbaselinefactorand/orthenumberofsubjectsassignedtoeachgroupSolution:Useblockingand/orstratifiedrandomizationProblemwithSimpleRandomizat42BlockingExample:Ifwehavetwotreatmentgroups(AandB)equalallocation,andablocksizeof4,randomassignmentswouldbechosenfromtheblocks1)AABB 4)BABA2)ABAB 5)BAAB3)ABBA 6)BABABlockingensuresbalanceafterevery4thassignmentBlockingExample:Ifwehavetw43StratificationExampleToensurebalanceonanimportantbaselinefactor,createstrataandsetupseparaterandomizationscheduleswithineachstratumExample:ifwewantpreventanimbalanceonageinanosteoporosisstudy,firstcreatethestrata“<75years”and“75years”thenrandomizewithineachstratumseparatelyBlockingshouldbealsobeusedwithineachstratumStratificationExampleToensur44AlternativestoRandomizationRandomizationisnotalwayspossibleduetoethicalorpracticalconsiderationsSomealternatives:HistoricalcontrolsNon-randomizedconcurrentcontrolsDifferenttreatmentperphysicianSystematicalternationoftreatmentsSourcesofbiasforthesealternativesneedtobeconsideredAlternativestoRandomizationR45BlindingMaskingtheidentityoftheassignedinterventionsMaingoal:avoidpotentialbiascausedbyconsciousorsubconsciousfactorsSingleblind: patientisblindedDouble
blind: patientandassessing investigatorareblindedTriple
blind: committeemonitoring responsevariables(e.g. statistician)isalsoblindedBlindingMaskingtheidentityo46HowtoBlindTo“blind”patients,canuseaplaceboExamplespillofsamesize,color,shapeastreatmentshamoperation(anesthesiaandincision)foranginareliefshamdevicesuchasshamacupuncture
HowtoBlindTo“blind”patient47WhyShouldPatientsbeBlinded?Patientswhoknowtheyarereceivinganeworexperimentalinterventionmayreportmore(orless)sideeffectsPatientsnotonneworexperimentaltreatmentmaybemore(orless)likelytodropoutofthestudyPatientmayhavepreconceivednotionsaboutthebenefitsoftherapyPatientstrytogetwell/pleasephysiciansWhyShouldPatientsbeBlinded48Placeboeffect–responsetomedicalinterventionwhichresultsfromtheinterventionitself,notfromthespecificmechanismofactionoftheinterventionExample:FisherR.W.JAMA1968;203:418-419
46patientswithchronicsevereitchingrandomlygivenoneoffourtreatmentsHighitchingscore=moreitchingTreatment ItchingScore cyproheptadineHCI 27.6 trimeprazinetartrate 34.6 placebo 30.4 nothing 49.6Placeboeffect–responsetom49WhyShouldInvestigatorsbeBlinded?TreatingphysiciansandoutcomeassessinginvestigatorsareoftenthesamepeoplePossibilityofunconsciousbiasinassessingoutcomeisdifficulttoruleoutDecisionsaboutconcomitant/compensatorytreatmentareoftenmadebysomeonewhoknowsthetreatmentassignment“Compensatory”treatmentmaybegivenmoreoftentopatientsontheprotocolarmperceivedtobelesseffectiveWhyShouldInvestigatorsbeBl50CanBlindingAlwaysbeDone?Insomestudiesitmaybeimpossible(orunethical)toblindatreatmentmayhavecharacteristicsideeffectsitmaybedifficulttoblindthephysicianinasurgeryordevicestudySourcesofbiasinanun-blindedstudymustbeconsideredCanBlindingAlwaysbeDone?In51GeneralStudyDesignsManyclinicaltrialstudydesignsfallintothecategoriesofparallelgroup,dose-ranging,cross-overandfactorialdesignsTherearemanyotherpossibledesignsandvariationsonthesedesignsWewillconsiderthegeneralcasesGeneralStudyDesignsManyclin52GeneralStudyDesignsParallelgroupdesignsGeneralStudyDesignsParallel53GeneralStudyDesignsDose-RangingStudiesGeneralStudyDesignsDose-Rang54GeneralStudyDesignsCross-OverDesignsGeneralStudyDesignsCross-Ove55GeneralStudyDesignsFactorialDesignsGeneralStudyDesignsFactorial56Cross-OverDesignsSubjectsarerandomizedtosequencesoftreatments(AthenBorBthenA)Usesthepatientashis/herowncontrolOftena“wash-out”period(timebetweentreatmentperiods)isusedtoavoida“carryover”effect(theeffectoftreatmentinthefirstperiodaffectingoutcomesinthesecondperiod)Canhave
溫馨提示
- 1. 本站所有資源如無特殊說明,都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請下載最新的WinRAR軟件解壓。
- 2. 本站的文檔不包含任何第三方提供的附件圖紙等,如果需要附件,請聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。
- 3. 本站RAR壓縮包中若帶圖紙,網(wǎng)頁內(nèi)容里面會(huì)有圖紙預(yù)覽,若沒有圖紙預(yù)覽就沒有圖紙。
- 4. 未經(jīng)權(quán)益所有人同意不得將文件中的內(nèi)容挪作商業(yè)或盈利用途。
- 5. 人人文庫網(wǎng)僅提供信息存儲(chǔ)空間,僅對用戶上傳內(nèi)容的表現(xiàn)方式做保護(hù)處理,對用戶上傳分享的文檔內(nèi)容本身不做任何修改或編輯,并不能對任何下載內(nèi)容負(fù)責(zé)。
- 6. 下載文件中如有侵權(quán)或不適當(dāng)內(nèi)容,請與我們聯(lián)系,我們立即糾正。
- 7. 本站不保證下載資源的準(zhǔn)確性、安全性和完整性, 同時(shí)也不承擔(dān)用戶因使用這些下載資源對自己和他人造成任何形式的傷害或損失。
最新文檔
- 二零二五版人工智能技術(shù)研發(fā)與應(yīng)用合同15篇
- 常州2025版二手房過戶稅費(fèi)處理與過戶手續(xù)辦理合同2篇
- 二零二五版智慧城市建設(shè)合作合同范本2篇
- 二零二五版在線教育管理系統(tǒng)定制開發(fā)合同3篇
- 二零二五版ISO9001質(zhì)量管理體系認(rèn)證與質(zhì)量管理體系審核與監(jiān)督合同3篇
- 水電工程2025年度施工安全評估合同2篇
- 二零二五版LED顯示屏戶外廣告位租賃合同協(xié)議3篇
- 二零二五年海鮮餐飲業(yè)特色菜品開發(fā)與銷售合同3篇
- 二零二五年度虛擬現(xiàn)實(shí)游戲開發(fā)電子合同承諾3篇
- 二零二五版智能零售企業(yè)兼職銷售員勞動(dòng)合同3篇
- 2025新北師大版英語七年級下單詞表
- 2024公路瀝青路面結(jié)構(gòu)內(nèi)部狀況三維探地雷達(dá)快速檢測規(guī)程
- 《智慧城市概述》課件
- 2024年北京市家庭教育需求及發(fā)展趨勢白皮書
- GB/T 45089-20240~3歲嬰幼兒居家照護(hù)服務(wù)規(guī)范
- 中建道路排水工程施工方案
- 拆機(jī)移機(jī)合同范例
- 智能停車充電一體化解決方案
- 化學(xué)驗(yàn)室安全培訓(xùn)
- 天書奇譚美術(shù)課件
- GB/T 18916.15-2024工業(yè)用水定額第15部分:白酒
評論
0/150
提交評論