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EBCP

EBCP. Random vs Systemic error. Random error : errors  in measurement that lead to measured values being inconsistent when repeated measures are taken. Ie : innacurate Systematic erros : predictable errors that happen all the time. Eg : forgeting to zero a scale. Ie : low accuracy.

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EBCP

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  1. EBCP

  2. Random vs Systemic error • Random error: errors in measurement that lead to measured values being inconsistent when repeated measures are taken. Ie: innacurate • Systematic erros: predictable errors that happen all the time. Eg: forgeting to zero a scale. Ie: low accuracy

  3. Bias: systemic error due to flawed methodology

  4. Types 1 vs 2 error • Type 1 error: False +ve, generally due to bias • Type 2 error: False –ve, insufficient statistical power (ie: CI is too wide because the sample size is too small) or bias

  5. Confidence intervals Statistical significance Clinical significance

  6. Causation • Exposure must precede outcome • Dose dependant gradient • Dechallence-rechallege- take away the exposure and the outcome decreases/disappears, then reappears when the exposure is returned • Also: Is the association consistent with other studies and does it make biological sense?

  7. Measuring Outcomes • Relative risk (RR): the probability of an event in the active treatment group divided by the probability of an event in the control group. RR = Y/X. A relative risk of 1 is the null value or no difference. • Absolute risk reduction (ARR) : The risk in the control group minus that in the invervention group: ARR = X-Y. • Relative risk reduction (RRR)= 1-RR

  8. Measuring Outcomes • Odds ratios: used for case control trials as risk of developing the disease has no meaning since they already have it or don’t. • Odds ratio = odds of exposure in the cases/odds of exposure in the controls OR= a/c ÷ b/d

  9. Measuring Outcomes • Number needed to treat (NNT): the number of patients you need to treat to prevent one additional bad outcome. The number needed to treat is the reciprocal of the absolute risk reduction (NNT= 1/ARR). • Number needed to harm (NNH): the number of people who need to be subjected to the exposure for one person to develop a negative outcome (NNH= 1/ARR in a study measuring harm)

  10. Diagnostic Tests • A Sensitve test helps rule out a diagnosis: SeNsitiveNegative rule OUT: SNOUT • A Specific test helps confirm the diagnosis: SPecificPositive rule IN: SPIN • Sensitivity: probability of true positives • Specificity: probability of true negatives

  11. Diagnostic Tests • Pre test probability: The chance your pt has the diagnosis. Basically the incidence in similar people presenting with the same symptoms. • Likelihood Ratios (+/-ve) : how much a positive or negative result modifies the probability of the disease. • Ratio of 1 doesn’t change the probability • Ratios greater than one increase the probability • Ratios less than one decrease the probability LR+ = sensitivity/(1-specificity) OR true+ve rate /false+ve rate LR- = (1-sensitivity)/specificity OR false-ve rate /true-ve rate

  12. Nomograms

  13. Prognostic Studies • Usually done via observational studies like Case-control or more commonly Cohort studies. • The cohort should all be at a similar point in the course of the disease. • Results can be shown as a “x” year survival rate or survival curve.

  14. Systematic Reviews • Sometimes the method of selecting articles for the systematic review is biased. If the selection process is unbiased the funnel plot should look like an inverted funnel.

  15. Systematic Reviews • Forest plots: Combine the results of the studies into one graph.

  16. Systematic Reviews • Forest Plots: • Heterogeneity: Assess if any of the studies are significantly different from the others. If heterogeneity is too high then the results of the studies are too different to pool together in a meta-analysis.

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