Abstract
BackgroundAt present, it is complicated to use screening trials to determine the optimal age intervals and periodicities of breast cancer early detection. Mathematical models are an alternative that has been widely used. The aim of this study was to estimate the effect of different breast cancer early detection strategies in Catalonia (Spain), in terms of breast cancer mortality reduction (MR) and years of life gained (YLG), using the stochastic models developed by Lee and Zelen (LZ).MethodsWe used the LZ model to estimate the cumulative probability of death for a cohort exposed to different screening strategies after T years of follow-up. We also obtained the cumulative probability of death for a cohort with no screening. These probabilities were used to estimate the possible breast cancer MR and YLG by age, period and cohort of birth. The inputs of the model were: incidence of, mortality from and survival after breast cancer, mortality from other causes, distribution of breast cancer stages at diagnosis and sensitivity of mammography. The outputs were relative breast cancer MR and YLG.ResultsRelative breast cancer MR varied from 20% for biennial exams in the 50 to 69 age interval to 30% for annual exams in the 40 to 74 age interval. When strategies differ in periodicity but not in the age interval of exams, biennial screening achieved almost 80% of the annual screening MR. In contrast to MR, the effect on YLG of extending screening from 69 to 74 years of age was smaller than the effect of extending the screening from 50 to 45 or 40 years.ConclusionIn this study we have obtained a measure of the effect of breast cancer screening in terms of mortality and years of life gained. The Lee and Zelen mathematical models have been very useful for assessing the impact of different modalities of early detection on MR and YLG in Catalonia (Spain).
Highlights
At present, it is complicated to use screening trials to determine the optimal age intervals and periodicities of breast cancer early detection
In the United States (US), a consortium of researchers participating in the Cancer Intervention and Surveillance Modeling Network (CISNET) used statistical and simulation modeling to quantify the relative impact of adjuvant therapy and screening mammography on the decline of breast cancer mortality [3,4]
Effect of early screening on mortality reduction (MR) Table 1 presents the effect of early detection on breast cancer mortality MR, in the 40 to 80 year age interval, for cohorts born in the period 1955-59, with the following assumptions: 1) screening started in 1985, 2) all women in the target population participated in early detection and 3) survival pdfs are the estimated Catalan pdfs for the 1980-1989 period
Summary
It is complicated to use screening trials to determine the optimal age intervals and periodicities of breast cancer early detection. Mathematical models for assessing the effect of health interventions are structured representations of health states and the transitions between them These models may describe the relationship between an intervention and changes in incidence and mortality rates for a specific disease in a particular population. In the United States (US), a consortium of researchers participating in the Cancer Intervention and Surveillance Modeling Network (CISNET) used statistical and simulation modeling to quantify the relative impact of adjuvant therapy and screening mammography on the decline of breast cancer mortality [3,4]. The stochastic models that Sandra Lee and Marvin Zelen designed in the US under CISNET are an alternative to population trials for addressing and responding to most of the questions that arise when developing and assessing the effect of early detection [510]
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