The effect of a treatment versus controls may be expressed in relative or absolute terms. For rational decision-making, absolute measures are more meaningful. The number needed to treat, the reciprocal of the absolute risk reduction, is a powerful estimate of the effect of a treatment. It is particularly useful because it takes into account the underlying risk (what would happen without the intervention?). The number needed to treat tells us not only whether a treatment works but how well it works. Thus, it informs health care professionals about the effort needed to achieve a particular outcome. A number needed to treat should be accompanied by information about the experimental intervention, the control intervention against which the experimental intervention has been tested, the length of the observation period, the underlying risk of the study population, and an exact definition of the endpoint. A 95% confidence interval around the point estimate should be calculated. An isolated number needed to treat is rarely appropriate to summarize the usefulness of an intervention; multiple numbers needed to treat for benefit and harm are more helpful. Absolute risk reduction and number needed to treat should become standard summary estimates in randomized controlled trials.
机构:
St Barts & Royal London Sch Med & Dent, Wolfson Inst Prevent Med, Dept Environm & Prevent Med, London EC1M 6BQ, EnglandSt Barts & Royal London Sch Med & Dent, Wolfson Inst Prevent Med, Dept Environm & Prevent Med, London EC1M 6BQ, England
机构:
Mem Sloan Kettering Canc Ctr, New York, NY USA
Mem Sloan Kettering Canc Ctr, 1101 Hempstead Turnpike, Uniondale, NY 11553 USAMem Sloan Kettering Canc Ctr, New York, NY USA
Sugarman, Ryan
Betts, Keith A.
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Anal Grp Inc, Los Angeles, CA USAMem Sloan Kettering Canc Ctr, New York, NY USA
Betts, Keith A.
Nie, Xiaoyu
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Anal Grp Inc, Los Angeles, CA USAMem Sloan Kettering Canc Ctr, New York, NY USA
Nie, Xiaoyu
Hartman, John
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Bristol Myers Squibb, Lawrenceville, NJ USAMem Sloan Kettering Canc Ctr, New York, NY USA
Hartman, John
Nguyen, Hiep
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Bristol Myers Squibb, Lawrenceville, NJ USAMem Sloan Kettering Canc Ctr, New York, NY USA
机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Pokfulam Rd, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Pokfulam Rd, Hong Kong, Peoples R China
Zhang, Chenyang
Yin, Guosheng
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Univ Hong Kong, Dept Stat & Actuarial Sci, Pokfulam Rd, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Pokfulam Rd, Hong Kong, Peoples R China