A randomized comparison of patients' understanding of number needed to treat and other common risk reduction formats.
BACKGROUND
Commentators have suggested that patients may understand quantitative information about treatment benefits better when they are presented as numbers needed to treat (NNT) rather than as absolute or relative risk reductions.


OBJECTIVE
To determine whether NNT helps patients interpret treatment benefits better than absolute risk reduction (ARR), relative risk reduction (RRR), or a combination of all three of these risk reduction presentations (COMBO).


METHODS
Randomized cross-sectional survey.


METHODS
University internal medicine clinic.


METHODS
Three hundred fifty-seven men and women, ages 50 to 80, who presented for health care.


METHODS
Subjects were given written information about the baseline risk of a hypothetical "disease Y" and were asked (1) to compare the benefits of two drug treatments for disease Y, stating which provided more benefit; and (2) to calculate the effect of one of those drug treatments on a given baseline risk of disease. Risk information was presented to each subject in one of four randomly allocated risk formats: NNT, ARR, RRR, or COMBO.


RESULTS
When asked to state which of two treatments provided more benefit, subjects who received the RRR format responded correctly most often (60% correct vs 43% for COMBO, 42% for ARR, and 30% for NNT, P =.001). Most subjects were unable to calculate the effect of drug treatment on the given baseline risk of disease, although subjects receiving the RRR and ARR formats responded correctly more often (21% and 17% compared to 7% for COMBO and 6% for NNT, P =.004).


CONCLUSIONS
Patients are best able to interpret the benefits of treatment when they are presented in an RRR format with a given baseline risk of disease. ARR also is easily interpreted. NNT is often misinterpreted by patients and should not be used alone to communicate risk to patients.
Sheridan
Stacey L
SL
Division of General Medicine and Epidemiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. ssherida@e-mail.unc.edu
Pignone
Michael P
MP
Lewis
Carmen L
CL
D000368:Aged; D000369:Aged, 80 and over; D032882:Comprehension; D003430:Cross-Sectional Studies; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012306:Risk; D016896:Treatment Outcome