Statistics

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

DISEASE PresentAbsent Positive TPFP Negative FNTN 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 NIH = negative in health

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

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

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

How prevalence affects NPV & PPV Assume 80% sensitivity; 60% specificity PrevalencePPVNPV

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

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

Actual Treatment Effect RX worksRX doesn’t work Trial Result PositiveTrue positiveType I error NegativeType II errorTrue negative

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

Calculate Sensitivity Specificity PPV NPV

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

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

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

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

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