[Application of the intrinsic estimator to breast cancer mortality rates].

OBJECTIVE

Assess use of the intrinsic estimator (IE) technique in epidemiology.

METHODS

The IE approach was applied to the analysis of breast cancer data in Argentina in order to observe the trends associated with "age, period, and cohort" (APC). This method involves the use of a principal components regression to obtain a single set of estimated trends. The results were compared to the findings obtained with the conventional method, which consists of adjusting a generalized linear model that includes the traditional constraints of the statistical model as well as an additional constraint (CGLM).

RESULTS

Both methods yielded compatible results in the trends associated with APC. However, they differed in the confidence intervals, with IE yielding greater efficiency. The curve associated with age showed the expected pattern of change across the life course: the greater the age, the greater the risk. With regard to cohorts, a decrease in the effects associated with the most recent cohorts was evident, whereas there was very little variation in the estimated effects for the period.

CONCLUSIONS

A comparison of the results obtained with the IE method and the CGLM method revealed the reach of the generic solution provided by the IE to the problem of estimates in an APC model. The IE method is based on conversion of the data observed using a weighting matrix that is simple to apply and provides estimates with desirable statistical properties.