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Statistics

Statistics. Statistics = everything you need to know, but continually want to forget!!!!. DISEASE. TEST. Sensitivity . TP/TP + FN % of truly diseased patients who test positive PID = positive in disease. Specificity. TN/TN + FP % of truly non-diseased patients who test negative

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Statistics

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  1. Statistics

  2. Statistics = everything you need to know, but continually want to forget!!!!

  3. DISEASE TEST

  4. Sensitivity TP/TP + FN % of truly diseased patients who test positive PID = positive in disease

  5. Specificity TN/TN + FP % of truly non-diseased patients who test negative NIH = negative in health

  6. Positive Predictive Value TP/TP + FP % of patients having disease when test result is positive

  7. Negative Predictive Value TN/TN +FN % of patients with negative test and no disease

  8. PPV and NPV and prevalence • PPV and NPV greatly influenced by the prevalence of the disease • Increase the prevalence, increase the PPV, decrease the NPV • More common a disease is in the population, the more likely it is that a positive test will be a true positive

  9. How prevalence affects NPV & PPVAssume 80% sensitivity; 60% specificity

  10. Type I (alpha) error • Trial concludes treatment is effective when there is no effect = false positive • Standard 5% probability that difference seen in a trial due to chance alone • Causes of type I error are chance and unmeasured difference in treatment groups

  11. Type II (beta) error • Trial concludes treatment ineffective when an effect exists = false negative • Accepted level is 20% • Causes of type II error are small sample size

  12. Actual Treatment Effect

  13. Problem #1 • 400 patients studies for prostate CA • 200 pts identified by biopsy as having ca • All patients underwent PSA testing • 160 pts correctly identified as having prostate CA • 120 patients correctly identified as not having prostate CA

  14. Calculate • Sensitivity • Specificity • PPV • NPV

  15. Problem #2 • Assume the prevalence of colon CA in SD county is 3% of all pts >50 yrs • Hemmocult testing is 20% sensitive, 80% specific • Calculate the predictive value of a positive test for detecting colon CA

  16. Improved version of hemmocult testing is 50% sensitive and 90% specific • Calculate the predictive value of a positive test for detecting colon cancer

  17. Risk • Relative Risk = The risk of an event after therapy as a percentage of risk without therapy • RR= Exp event rate/control event rate • Relative Risk Reduction=The proportional reduction in rates of bad events between exp and control groups • RRR= 1-RR

  18. Absolute Risk Reduction: The absolute arithmetic difference in rates between the exp and control groups • ARR= Exp event rate – control event rate • Number needed to treat: The # of patients who need to be treated to achieve one favorable outcome • NNN= 1/ARR

  19. Problem #3 • If patients presenting with an evolving CVA are treated with ASA, their one month morbidity rate is 22% whereas the morbidity rate in ASA + plavix is 7%. Calculate: • RR • RRR • ARR • NNT

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