These increases in incidence represent real overdiagnosis to only a limited extent. From the observed rates, one can not easily determine to what extent overdiagnosis is involved because screening is still being continued. In these circumstances, modelling of the natural history of breast cancer and its early lesions, and what screening is estimated to depict, is crucial and provides a 'best guess'. Using the microsimulation model MISCAN [6
], we first simulate individual life histories for women in the absence of screening and then assess how these histories would change as a consequence of a screening programme. The natural history is modelled as a progression from no breast cancer through pre-clinical disease (DCIS, T1a, 1b, 1c, T2+) to clinical disease (same stages). From a given pre-clinical state, a cancer may be detected by screening or become clinically apparent or, if undiagnosed, progress to the next pre-clinical state. To correctly model this natural history of breast cancer for women in a certain age group, one has to estimate mean durations of the different pre-clinical phases, transition probabilities, and sensitivity of the applied test [10
]. Basically, one therefore needs data from two sources: observed screen and clinical data. These data include clinical incidence data by age and stage in the situation without screening, data on screen-detected cancers by stage, screening round (and interval) and age, and corresponding clinical incidence data when screening is being implemented [11
]. Although the observed data can often be explained by a small range of parameters (e.g., a somewhat higher sensitivity and shorter mean duration of the stage may also result in a good fit), by having more detailed data from several screening rounds, by screening different age groups and/or by using different screening intervals, best parameters often fall into a smaller range [12
]. In the Netherlands, such detailed data have been used: in the past using pilot data [6
], and more recent data from the annual monitoring by the National Evaluation Team for Breast cancer screening [7
The fit of the model to the breast cancer screening pilot data [6
], as well as to the Dutch nation-wide data [9
], has been reported as quite satisfactory.
We also used the MISCAN approach to analyse the results of the Health Insurance Plan trial study. These comparisons show the potential power of modelling: the parameter values for the invariant part of the natural history of pre-clinical breast cancer are indeed the same, whereas the increase in the sensitivity reflects the improvement in mammography. Taking the obvious differences between HIP and Nijmegen (one of the two Dutch pilot studies) into account, the model shows that there is a good correspondence between the screening data from these studies. The findings about the duration of pre-clinical disease and the sensitivity of screening can be compared with results from other modelling approaches. Day and colleagues [13
] applied this model to data from Utrecht (the other Dutch pilot study). The study reports a good fit of the model (chi-square of 7.2 and 7 degrees of freedom) when assuming a sensitivity of 99% and a mean duration of 2.8 years. It is not indicated exactly what data from Utrecht were used, but it is clearly a less detailed subset of the data than we used for testing model assumptions. An adapted version of the Day and Walter model was applied to the Nijmegen data [14
]. In general, the estimated parameters are comparable to the values found with the MISCAN approach presented here, especially regarding the age-dependency of the estimated duration of the preclinical stage. The reported average duration is somewhat shorter, however, for example, 2.5 years in the 50 to 64 year old age group.
Data on the natural history at older ages have been very limited, but are slowly emerging now that the Dutch programme includes women aged 70 to 74 years [15
]. Data on the natural history of DCIS are scarce [16
], but parameters concerning the screen-detectable pre-clinical period can be estimated, based on the aforementioned data.
In our first analyses, we have assumed that 10% of invasive breast cancers are preceded by a screen-detectable DCIS phase and that the chance of progressing to invasive cancer or clinical DCIS is almost 90% in the long term. Recent data from randomised treatment trials support a high progression rate in the long term [17
]. The observed screen data are then consistent/compatible with a mammography sensitivity of 40% and a mean screen-detectable duration of 5 years.