Apr-12-Ch-14-15

Apr-12-Ch-14-15 - Welcome to BSCI425 Apr 12 2010...

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Unformatted text preview: Welcome to BSCI425 Apr. 12, 2010 Announcements Gordis: Chapters 14 and 15 Announcements This Week: Chapters 14, 15 (Today) Chapter 20 Ethical Issues on Wed Thursday Project Time Questions? Causation Association Causation Often determine on the strength of the association Natural experiments Human studies Animal studies Design Types Case control start with cases (incidence) Cohort start with exposure Look at relative risk, attributed risk and odds ratio Gold Standard is RCT Often not possible, why ? What are some alternatives? Ecologic Study Done on existing data Looks at trends and relationships Provides guidance Based on population data, often general population data Can result in ecologic fallacy Prone to confounding factors Fig. 14-4 Breast Cancer Data Real vs. Spurious How does one determine if an observed association is real? Evidence Statistical evidence http://www.sciencenews.org/view/feature/id/ 57091/title/Odds_Are%2C_Its_Wrong Types of causal relationships Four Types Criteria for Judgment 1. Temporal relationship 2. Strength of the association 3. Dose-response relationship 4. Replication of the findings 5. Biologic plausibility 6. Consideration of alternate explanations 7. Cessation of exposure 8. Consistency with other knowledge 9. Specificity of the association What is show in this figure? USPSTF U.S. Preventive Services Task Force(USPSTF) An independent panel of experts in primary care and prevention that systematically reviews the evidence of effectiveness and develops recommendations for clinical preventive services. Part of Agency for Healthcare Research and Quality (AHRQ), Part of HHS http://www.ahrq.gov/ Mission: improving the quality, safety, efficiency, and effectiveness of health care for all Americans Quality of Evidence GOOD Evidence includes consistent results from welldesigned, well-conducted studies of representative populations that directly assess effects on health outcomes. FAIR Evidence is sufficient to determine effects on health outcomes, but the strength of the evidence is limited by the number, quality, or consistency of the individual studies, generalizability to routine practice, or indirect nature of the evidence on health outcomes. POOR Evidence is insufficient to assess the effects on health outcomes because of limited number or power of studies, important flaws in their design or conduct, gaps in the chain of evidence, or lack of information on important health outcomes. Recommendation Based on Evidence plus Impact A. The USPSTF strongly recommends that clinicians provide [the service] to eligible patients. B. The USPSTF recommends that clinicians provide [the service] to eligible patients. C. The USPSTF makes no recommendation for or against routine provision of [the service] D. The USPSTF recommends against routinely providing [the service] to asymptomatic patients I. The USPSTF concludes that the evidence is insufficient to recommend for or against routinely providing [the service] What is shown in this table Chapter 15 Bias Confounding Interactions -- When more than one thing is in play. Selection vs. selection bias Bias Confounding Associations resulting from unseen or unaccounted for factors What are some confounding factors Age Associated behaviors Smoking and birth weight Why we double blind in RCT studies Why the randomization processes needs to be documented and reproducible Selection bias Remember non-responders and withdrawals can NOT be assumed to be representative of the included subjects Exclusion bias Bias introduced because of exclusion criteria Information bias Classification of data Differential misclassifications Non-differential misclassifications Bias can be reduced by a more correct study design Addressing Confounding In designing and carrying out the study: Individual matching Group matching Interactions Many outcomes are the result of >1 possible pathway Not confounding Additive Synergistic In the analysis of data: Stratification Adjustment Relative Risk Adjustments Go through tables 15-11 to 15-22 Pay attention to Attributed risk table 15-13 Relative risk table 15-16 Attributed and Relative Risk Attributed risk Subtract box a Additive or multiplicative Relative risk Divide by box a Additive or multiplicative Additive or Multiplicative? Does data show relative of attributed risk? Box A Box B Construct and explanation Next Time Clicker quiz on chapters 14-15-20 Chapter Chapter 20 Ethical Considerations. ...
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