The minimum annual volume of 500 mammograms required in North America is justified; radiologist accuracy may be compromised if interpretive volume is consistently less than this requirement. Raising interpretive volume may help to reduce the frequency of false positives without loss of sensitivity. Possible gains in accuracy may be greater with increases in volume of up to approximately 3000 mammograms interpreted annually.

Although not all mammograms in the Quebec screening program met the optimum quality required by the Canadian Association of Radiologists or American College of Radiology accreditation, the screening mammograms produced in this population-based organized screening program reached a high enough level of quality so that the remaining variation in quality is too little to impair screening sensitivity.

The effect of a cancer screening program can be measured through the standardized mortality ratio (SMR) statistic. The numerator of the SMR is the observed number of deaths from the screened disease among participants in the screening program, whereas the denominator of the SMR is an estimate of the expected number of deaths in these participants under the assumption that the screening program has no effect. In this article, we propose a variance estimator for the denominator of the SMR when this expected number of deaths is estimated with Sasieni's method. We give both a general formula for this variance as well as formulas for specific disease incidence and survival estimators. We show how this new variance estimator can be used to build confidence intervals for the SMR. We investigate the coverage properties of various types of confidence intervals by simulation and find that intervals that make use of the proposed variance estimator perform well. We illustrate the method by applying it to the Québec Breast Cancer Screening program.

OBJECTIVES: This article presents the first study of the economic consequences of obesity and overweight in the Canadian province of Quebec. The article examines three types of direct costs: hospitalizations, medical visits and drug consumption; and one type of indirect cost: productivity loss due to disability.

BackgroundWe estimated the relations of sociodemographic, organizational, disease, and treatment variables