Oliver Heidinger

Background: The European Guidelines for breast cancer screening suggest that the impact of population-based mammography screening programmes (MSP) may be assessed using the relative reduction in the incidence of advanced breast cancer (ABC, that is, stage UICC II and higher) as a surrogate indicator of screening effectiveness. Methods: This prospective, population register-based study contained individual data of 1,200,246 women (aged 50–69 years) who attended the initial prevalence screening between 2005 and 2009. Of them, 498,029 women returned for the regular (i.e., within 24 months) first subsequent, and 208,561 for the regular second subsequent incidence screenings. The incidence rate of ABC was calculated for the 24-months period following, but not including, the initial screening by incorporating all interval ABCs and all ABCs detected at the regular first incidence screening; the ABC rate for the second 24-months period was determined in the same way, including ABCs detected in the interval after the first and, respectively, at the second incidence screening. The relative reduction in the ABC incidence was derived by comparing the age-standardized rates in these two periods with an age-standardized reference incidence rate, observed in the target population before the MSP implementation. The strengths and weaknesses of this particular study design were contrasted with a recently published checklist of main methodological problems affecting studies of the effect of MSP on ABC incidence. Results: The age-standardized ABC incidence rate was 291.6 per 100,000 women for the 24-months period subsequent to the initial screening, and 275.0/100,000 for the 24-months period following the first subsequent screening. Compared to the 2-year incidence of 349.4/100,000 before the start of the MSP, this amounted to a relative reduction of 16.5 and 21.3%, respectively, in the incidence of ABC among regular MSP participants. Conclusions: The design employed in this study avoids some of the substantial methodological limitations that compromised previous observational studies. Nevertheless, specific limitations prevail that demand a cautious interpretation of the results. Therefore, the study findings, indicating a reduction in ABC for regular MSP participants, need to be followed with respect to potential impacts on breast cancer mortality rates.

Das Gesetz zur Qualitätssicherung durch klinische Krebsregister verpflichtet die Bundesländer, eine flächendeckende, klinische Krebsregistrierung zu implementieren. Der Beitrag beschreibt Vorgehen und Herausforderung am Beispiel der Implementierung im bevölkerungsreichsten Bundesland Nordrhein-Westfalen.

The population-based mammography screening program (MSP) was implemented by the end of 2005 in Germany, and all women between 50 and 69 years are actively invited to a free biennial screening examination. However, despite the expected benefits, the overall participation rates range only between 50 and 55 %. There is also increasing evidence that belonging to a vulnerable population, such as ethnic minorities or low income groups, is associated with a decreased likelihood of participating in screening programs. This study aimed to analyze in more detail the intra-urban variation of MSP uptake at the neighborhood level (i.e. statistical districts) for the city of Dortmund in northwest Germany and to identify demographic and socioeconomic risk factors that contribute to non-response to screening invitations. The numbers of participants by statistical district were aggregated over the three periods 2007/2008, 2009/2010, and 2011/2012. Participation rates were calculated as numbers of participants per female resident population averaged over each 2-year period. Bayesian hierarchical spatial models extended with a temporal and spatio-temporal interaction effect were used to analyze the participation rates applying integrated nested Laplace approximations (INLA). The model included explanatory covariates taken from the atlas of social structure of Dortmund. Generally, participation rates rose for all districts over the time periods. However, participation was persistently lowest in the inner city of Dortmund. Multivariable regression analysis showed that migrant status and long-term unemployment were associated with significant increases of non-attendance in the MSP. Low income groups and immigrant populations are clustered in the inner city of Dortmund and the observed spatial pattern of persistently low participation in the city center is likely linked to the underlying socioeconomic gradient. This corresponds with the findings of the ecological regression analysis manifesting socioeconomically deprived neighborhoods as risk factors for low attendance in the MSP. Spatio-temporal surveillance of participation in cancer screening programs may be used to identify spatial inequalities in screening uptake and plan spatially focused interventions.

Monitoring spatial disease risk (e.g. identifying risk areas) is of great relevance in public health research, especially in cancer epidemiology. A common strategy uses case-control studies and estimates a spatial relative risk function (sRRF) via kernel density estimation (KDE). This study was set up to evaluate the sRRF estimation methods, comparing fixed with adaptive bandwidth-based KDE, and how they were able to detect ‘risk areas’ with case data from a population-based cancer registry. The sRRF were estimated within a defined area, using locational information on incident cancer cases and on a spatial sample of controls, drawn from a high-resolution population grid recognized as underestimating the resident population in urban centers. The spatial extensions of these areas with underestimated resident population were quantified with population reference data and used in this study as ‘true risk areas’. Sensitivity and specificity analyses were conducted by spatial overlay of the ‘true risk areas’ and the significant (α=.05) p-contour lines obtained from the sRRF. We observed that the fixed bandwidth-based sRRF was distinguished by a conservative behavior in identifying these urban ‘risk areas’, that is, a reduced sensitivity but increased specificity due to oversmoothing as compared to the adaptive risk estimator. In contrast, the latter appeared more competitive through variance stabilization, resulting in a higher sensitivity, while the specificity was equal as compared to the fixed risk estimator. Halving the originally determined bandwidths led to a simultaneous improvement of sensitivity and specificity of the adaptive sRRF, while the specificity was reduced for the fixed estimator. The fixed risk estimator contrasts with an oversmoothing tendency in urban areas, while overestimating the risk in rural areas. The use of an adaptive bandwidth regime attenuated this pattern, but led in general to a higher false positive rate, because, in our study design, the majority of true risk areas were located in urban areas. However, there is a strong need for further optimizing the bandwidth selection methods, especially for the adaptive sRRF.

Evaluating cancer prevention programs requires collecting and linking data on a case specific level from multiple sources of the healthcare system. Therefore, one has to comply with data protection regulations which are restrictive in Germany and will likely become stricter in Europe in general. To facilitate the mortality evaluation of the German mammography screening program, with more than 10 Million eligible women, we developed a method that does not require written individual consent and is compliant to existing privacy regulations. Our setup is composed of different data owners, a data collection center (DCC) and an evaluation center (EC). Each data owner uses a dedicated software that preprocesses plain-text personal identifiers (IDAT) and plaintext evaluation data (EDAT) in such a way that only irreversibly encrypted record assignment numbers (RAN) and pre-aggregated, reversibly encrypted EDAT are transmitted to the DCC. The DCC uses the RANs to perform a probabilistic record linkage which is based on an established and evaluated algorithm. For potentially identifying attributes within the EDAT ('quasi-identifiers'), we developed a novel process, named 'blinded anonymization'. It allows selecting a specific generalization from the pre-processed and encrypted attribute aggregations, to create a new data set with assured k-anonymity, without using any plain-text information. The anonymized data is transferred to the EC where the EDAT is decrypted and used for evaluation. Our concept was approved by German data protection authorities. We implemented a prototype and tested it with more than 1.5 Million simulated records, containing realistically distributed IDAT. The core processes worked well with regard to performance parameters. We created different generalizations and calculated the respective suppression rates. We discuss modalities, implications and limitations for large data sets in the cancer registry domain, as well as approaches for further improvements like l-diversity and automatic computation of 'optimal' generalizations.

There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany.

Background: Cancer screening programs must meet high standards for quality and effectiveness, because many healthy persons need to be screened to detect relatively few cases of cancer. In this study, we use the rate of interval cancers as an important surrogate indicator for evaluating the German mammography screening program (MSP). Methods: All first-time participants in the MSP in the German federal state of North Rhine-Westphalia over the period 2005-2008 whose screening mammogram had been read as negative were followed over the next 24 months for the potential development of breast cancer (an "interval cancer" or IC). The screening data in the MSP database were compared in anonymized fashion with reports of cancer that were recorded at the Epidemiological Cancer Registry North Rhine-Westphalia. Results: Among the 878 764 women with negative screening mammograms in the first screening round, 2036 (23.2 per 10 000) developed an IC in the ensuing 24 months. These ICs accounted for 40% of all T2-T4 breast cancers occurring in first-time participants in the screening program in the 2 years after screening. The relative rate of IC compared to the background incidence of breast cancer before introduction of the MSP was 27% in the first year and 58% in the second. Screening detected 78% of all breast cancers that occurred during a maximum of 2 years after screening. Conclusion: The IC rates in the implementation phase of the MSP agree with those found in other, established European programs. The present study is the first one to assess this important surrogate parameter to characterize the effectiveness of the German MSP among women in North Rhine-Westphalia, Germany's largest state by population. Cite this as: Heidinger O, Batzler WU, Krieg V, Weigel S, Biesheuvel C, Heindel W, Hense HW: The incidence of interval cancers in the German mammography screening program-results from the population-based cancer registry in North Rhine-Westphalia. Dtsch Arztebl Int 2012; 109(46): 781-7. DOI: 10.3238/arztebl.2012.0781