CRC mortality rates

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.

Case-control studies 

Case control studies that compare ‘exposure’ (i.e. ‘screening’) between cases (deaths from CRC) and controls are an attractive alternative to cohort studies in terms of cost and effort. However, careful consideration of the design issues is necessary to avoid a number of potential biases, (Hosek, Flanders & Sasco 1996). The major problem with such studies is that of selection bias, due to different levels of underlying risk in participants and non-participants with screening. Methods to adjust for this are required both to estimate the mortality benefit in those actually screened, and the ‘impact’ on the population invited for screening.