M Murphy1, C Osmond. 1. Department of Public Health and Primary Care, University of Oxford, Radcliffe Infirmary, U.K.
Abstract
STUDY OBJECTIVE: The aim was to provide benchmarks by which to judge the success of behaviour change and the cervical cancer screening programme in England and Wales in reducing mortality from this disease over the next decade. DESIGN: Log-linear models and cervical cancer mortality data by age and marital status from 1959-88 were used to predict future mortality in England and Wales. MEASUREMENTS AND MAIN RESULTS: Recombining "predicted" deaths in marital status groups for 1984-88 gave a closer agreement to total mortality observed in those years than predictions based on past trends from 1959-83 among women of all statuses combined. Mortality for 1989-2003 was then predicted, using the data for 1959-1988. CONCLUSIONS: The reaggregated marital status forecasts of mortality provide an upper boundary which future observed mortality should not cross if primary and secondary prevention measures are working effectively. The method allows swift comparison of observation with expectation and therefore the rapid evaluation of the overall performance of preventive strategies.
STUDY OBJECTIVE: The aim was to provide benchmarks by which to judge the success of behaviour change and the cervical cancer screening programme in England and Wales in reducing mortality from this disease over the next decade. DESIGN: Log-linear models and cervical cancer mortality data by age and marital status from 1959-88 were used to predict future mortality in England and Wales. MEASUREMENTS AND MAIN RESULTS: Recombining "predicted" deaths in marital status groups for 1984-88 gave a closer agreement to total mortality observed in those years than predictions based on past trends from 1959-83 among women of all statuses combined. Mortality for 1989-2003 was then predicted, using the data for 1959-1988. CONCLUSIONS: The reaggregated marital status forecasts of mortality provide an upper boundary which future observed mortality should not cross if primary and secondary prevention measures are working effectively. The method allows swift comparison of observation with expectation and therefore the rapid evaluation of the overall performance of preventive strategies.