Disease impact number and population impact number: population perspectives to measures of risk and benefitCommentary: DINS, PINS, and things—(2);clinical and population perspectives on treatment effectsBMJ 2000; 321 doi: https://doi.org/10.1136/bmj.321.7266.950 (Published 14 October 2000) Cite this as: BMJ 2000;321:950
Disease impact number and population impact number: population perspectives to measures of risk and benefit
- Richard F Heller, professor of community medicine and biostatistics (firstname.lastname@example.org)a,
- Annette J Dobson, professor of biostatisticsb
- a Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, New South Wales 2308, Australia
- b Department of Social and Preventive Medicine, University of Queensland, Queensland 4006, Australia
- a Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT
- b MRC Health Services Research Collaboration, Department of Social Medicine, University of Bristol, Bristol BS8 2PR
- Correspondence to: R F Heller, Centre for Clinical Epidemiology and Biostatistics, David Maddison Clinical Sciences Building, Royal Newcastle Hospital, Newcastle, New South Wales 2308, Australia
- Accepted 5 July 2000
The number needed to treat statistic is a clinically useful measure of treatment effect, conveying both statistical and clinical importance to the treating doctor. 1 2 This information, however, is limited to clinical decision making and lacks a public health perspective. We propose two new statistics, which should allow the impact of an intervention to be seen in the context of the broader population.
The number needed to treat is defined as the number of patients who must be treated to prevent one patient from experiencing the adverse effects of the disease being studied.3 For example, treating five diabetic patients with intensive therapy may result in one fewer patient who dies or has a macrovascular event.4 This gives an immediate and simple understanding of the impact of the intervention. The number needed to treat statistic, however, relates only to those people actually treated and does not give an appreciation of how many people with the disease in question, or of the total population, will benefit from applying the intervention. Our proposed new statistics offer this population perspective to the number needed to treat.
We propose two statistics, the disease impact number and the population impact number. The disease impact number provides a population perspective by taking account of the number of people in the population with the disease, not just those eligible for the intervention according to the entry criteria for the trial from which the evidence of benefit is derived or those who actually have access to treatment. It is defined as “the number of those with the disease in question among whom one event will be prevented by the intervention.” It is given by the formula 1/(absolute risk reduction × proportion of people with the disease who are exposed to the intervention) where the absolute risk …
Correspondence to: L Smeeth
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