Variance estimation and confidence intervals for the standardized mortality ratio with application to the assessment of a cancer screening program.
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.
Département de mathématiques et de statistique, Université Laval, Canada.
Denis
D
Talbot
Thierry
T
Duchesne
Jacques
J
Brisson
Nathalie
N
Vandal
D000368:Aged; D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000175:diagnosis / Q000401:mortality; D003198:Computer Simulation / Q000706:statistics & numerical data; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D055088:Early Detection of Cancer / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D015994:Incidence; D008875:Middle Aged; D011792:Quebec / Q000453:epidemiology; D012044:Regression Analysis; D016019:Survival Analysis