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目次
1.1CaseAnalysis
1.3MethodologyofClinicalEpidemiology
1.4RolesandSignificanceofClinicalEpidemiology
Chapter2EvaluationofDiagnosticTests
2.2DesignofaDiagnosticTest
2.4ImportantIssuesinStudyDesignofDiagnosticTests
2.5PossibleBiasinDiagnosticTests
2.6StandardsfortheReportingofDiagnosticAccuracyStudies
2.7CaseStudyonEvaluationofaDiagnosticTest
Chapter3EvaluationofEtiologicalStudies
3.1CaseAnalysis
3.2ConceptofEtiologyinEpidemiology
3.3CausalInference
3.4MajorEpidemiologicalResearchMethodsinEtiologicalEvaluation
Chapter4ClinicalTrials
4.2IntroductiontoRandomizedControlledTrials
4.3EssentialElementsofaRTCStudy
4.4LimitationsofRCTs
4.5ReportingofTrialsandCONSORT
Chapter5Prognosis
5.1ClinicalScenario
5.2ClinicalQuestions
5.4SomeConcepts
5.5ResearchMethodsforPrognosticStudies
5.6DescribingPrognosisasaRate
5.7SurvivalAnalysis
5.8BiasinPrognosticStudiesandControllingMethods
5.9GuidelinesforAssessingEvidenceaboutPrognosticStudies
Chapter6Prevention
6.1ClinicalScenario
6.2WhatisPrevention?WhyPrevent?
6.3LevelsofPrevention
6.4ScreeningTest
Chapter7ClinicalResearch,ClinicalGuidelinesandClinicalPractice
7.1ClinicalScenario
7.2RandomizedClinicalTrials
7.3DiagnosticTests
7.4ResearchaboutPrognosis
7.7ApplyingtheEvidencetoIndividualPatients
7.8ResolutiontotheClinicalScenario
Chapter8MethodologicalToolsinClinicalEpidemiology
8.2SampleSizeRequiredforStudy
8.3ResourcesforEvidence-basedMedicine
8.40therBMJResources.
書摘/試閱
3.3.1 Time Sequence
The cause should be considered prior to the effect(outcome), which is the primary basis for the determination of the causal relationship. In clinical praetice, when a cause is not prior to an effect, the causalrelationship can be ruled out. However, time sequence is not sufficient to demonstrate the existenceof causality. In most cross-sectional and case controlstudies, time sequence of the cause and effect is unable to be determined because both the cause and effectare measured at the same time point.
3. 3. 2 Strength of Association
When a strong association is found between the causeand effect, it means that causality between them ishighly possible. For instance, it has been found inmany prospective cohort studies that the risk forsmokers to develop lung cancer is 4 to 16 times of thatfor non-smokers; meanwhile, the strength of association between the two is far higher than that betweensmoking and kidney cancer. Therefore, smoking ismore likely to have a causal relationship with lungcancer. Similarly, there is strong evidence that thehepatitis B virus is the cause of liver cancer, becausethe risk ratio of hepatitis B for hepatocellular carcinoma approaches 300. Sometimes, however, bias can also result in strong relative risk, which should he eomprehensively analyzed in combination with other judgment criteria.
3. 3. 3 Dose-response Relationship
If the suspected cause changes quantitatively, the corresponding result will also generate quantitativechange. The quantitative changes between the twocorrelate with each other, suggesting the existence ofa dose-response relationship. If a dose-response relationship is confirmed, speculations on causal inferencecan he strengthened. A study on the relationship between the frequency of snoring and carotid atherosclerosis found that the prevalence rate of carotid bifurcation plaques for non-snorers was 38.9%, for snoringone day per week was 46.2%, for snoring 2 to 4 daysper week was 53.8%, and for snoring more than 5days per week was 70.1%. The prevalence rate of carotid plaques gradually increases as the frequency ofsnoring increases. There is an obvious dose responserelationship between the frequency of snoring and thenumber of patients with carotid plaques. The dose-response relationship is the evidence of causality, although it still cannot rule out the possibility of confounding factors.
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