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Number needed to screen is a new statistic defined as the number of people that need to be screened for a given duration to prevent one death or one adverse event. It can be directly calculated from clinical trials of disease screening, and can also be estimated from clinical trials oftreatment and the prevalence of so far unrecognised or untreated disease
For prevention of all cause death, 418 people need to be screened with a lipid profile if detection of dyslipidaemia was followed by pravastatin treatment for 5 years
The estimated number needed to screen for hypertension to prevent all cause death was 274 to 1307 for 5 years if detection was followed by treatment with thiazide diuretic
Screening with haemoccult testing or mammography did not significantly prevent all cause death. Haemoccult screening significantly decreased deaths from colon cancer with a number needed to screen of 1274 for 5 years. Mammography significantly reduced deaths from breast cancer with a number needed to screen of 2451 for 5 years of women aged 50-59
Introduction
Too often politics,rather than evidence,dictates the national strategy for disease screening.There are too few clinical trials showing the efficacy of screening strategies. 1 4 More randomised trials are needed. In the meantime a strategy for disease screening based on available evidence is needed.
The ability to compare the efficacy of screening strategies is a prerequisite for the development of a national strategy for disease screening. Until now there has been no means of comparing the overall benefit of screening. The results of most clinical trials are presented as relative risk reduction or odds ratios, but these ignore the role of event rate on overall clinical benefit. For example, when presented as relative risk reduction a highly effective screening strategy for a disease with a low mortality will seem better than a less effective screening strategy for a disease with higher mortality. Furthermore, doctors and patients sometimes interpret the degree of statistical significance as an index of clinical relevance, but this ignores the effect of study size on significance. A modestly effective screening strategy studied in a large number of people can result in a lower P value than that observed with a highly effective screening strategy studied in a smaller...