It will be several years before the impact of population screening on CRC mortality
becomes observable, and many more years before the full effect is achieved. The timing of a reduction
depends on the natural history of the disease, and the ‘lead time’ due to screening (i.e. the
time by which screening advances the date of diagnosis) as well as on the time taken to cover the
target population. It will also depend on the quality of screening.
Methods to evaluate the impact of screening on CRC mortality include analyses of population trends,
cohort studies (aggregated or individual-based) and case-control studies.
Population trends
Mortality from CRC has been decreasing in many European countries since the mid 1990’s, (Karim-Kos
et al. 2008). Analyses of the routinely produced age-gender specific population rates over time will be
subject to limitations due to the dilution of the effect of screening from deaths occurring in cases diagnosed
prior to the introduction of screening, and/or at an age below which invitations begin. This
can be overcome by use of refined CRC mortality rates in which such deaths are excluded. However,
the rates will also be confounded by other factors such as cohort effects on underlying incidence, and
by the effects of improvements in treatment and/or the stage of diagnosis of symptomatic disease on
survival and mortality. Thus whilst a lack of any reduction in population mortality rates several years
after the introduction of a screening programme should be a cause for concern, it is difficult to use
such trends to quantify the effect, and attempts to do so should take account of the factors discussed
above.
Cohort studies
In some settings, the introduction of population screening will have been phased in such a way as to
facilitate comparisons of populations invited at different time points. Such a model has been used in
Finland (see Ch. 2, Sect. 2.6.4). In the absence of such a system, comparisons can be made between
geographical areas (regions invited/not invited to screening) or between the same population in different
time periods before and after the introduction of screening. Both types of comparison are liable
to possible bias due to underlying differences in the risk in the populations/time-periods. This may –
under certain circumstances – be compensated for by including also a comparison group from geographic
areas where no invitational program existed from before the introduction of screening. Cohort
studies using aggregated data need estimates of incidence in order to avoid dilution effect discussed
above.
These biases can be avoided by individual-based cohort studies in which deaths and cancer registrations
are linked to screening histories.
