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To understand these terms consider the following hypothetical example

1000 patients are randomized to receive either heparin or placebo. In the heparin group, adverse events (death, or MI ) occurred in  10% (50 of 500). For those treated with placebo, the adverse event rate was 20% (100 of 500). 

It is convenient to set up a contingency table to assist data analysis
 
 

Assignment group    Adverse even occurs Adverse even does not occur  Totals
experimental (heparin) 50      a 450    b 500
control (no heparin) 100    c 400    d 500
Totals 1000

In other terms, 
the Experimental Event Rate (EER) is a/(a + b)
and the Control Event Rate (CER)  is  c /(c + d)
 

  • The Absolute Risk Reduction (ARR) is the difference


            ARR=CER-EER      AAR= 0.2 - 0.1 = 0.1
 

  • The Relative Risk (RR) is the proportional reduction in risk


            RR= EER/CER        RR= 0.1/0.2 = 0.5

       "the relative risk of an adverse event in heparin treated patients is 50%"
 

  • Commonly Relative Risk Reductions (RRR) are reported in the literature
                RRR= 1-RR           RRR=1 - 0.5 = 0.5

                     "the risk of an adverse event was reduced by 50%"
 

  • Pundits of Evidence Based Medicine (evidencists?) favor the Number Needed to Treat (NNT) as a "bottom line" measure of effect size.  NNT can be determined in two ways
              1)  NNT =  1/ARR      NNT= 1/0.1 = 10
              2)  NNT= 1/ (RRR X CER)     NNT= 1/(0.5X 0.2)= 10

                  "You need to treat 10 patients to avoid one adverse event" 

NNT is in some ways more intuitive and informative than RR or RRR.  However, a full appreciation of NNT's requires a little more reading