Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

Background: 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. Methods: Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results: With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion: High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage.<br

Comparing adaptive and fixed bandwidth-based kernel density estimates in spatial cancer epidemiology

Background: 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. Methods: 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. Results: 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. Conclusion: 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.<br

Quality of record linkage in a highly automated cancer registry that relies on encrypted identity data

Objectives: In the absence of unique ID numbers, cancer and other registries in Germany and elsewhere rely on identity data to link records pertaining to the same patient. These data are often encrypted to ensure privacy. Some record linkage errors unavoidably occur. These errors were quantified for the cancer registry of North Rhine Westphalia which uses encrypted identity data. Methods: A sample of records was drawn from the registry, record linkage information was included. In parallel, plain text data for these records were retrieved to generate a gold standard. Record linkage error frequencies in the cancer registry were determined by comparison of the results of the routine linkage with the gold standard. Error rates were projected to larger registries. Results: In the sample studied, the homonym error rate was 0.015%; the synonym error rate was 0.2%. The F-measure was 0.9921. Projection to larger databases indicated that for a realistic development the homonym error rate will be around 1%, the synonym error rate around 2%. Conclusion: Observed error rates are low. This shows that effective methods to standardize and improve the quality of the input data have been implemented. This is crucial to keep error rates low when the registry’s database grows. The planned inclusion of unique health insurance numbers is likely to further improve record linkage quality. Cancer registration entirely based on electronic notification of records can process large amounts of data with high quality of record linkage

Preliminary design of the HEBT of IFMIF DONES

IFMIF-DONES (International Fusion Materials Irradiation Facility–DEMO Oriented Neutron Source) is currentlybeing developed in the frame of the EUROfusion Early Neutron Source work package (WPENS) and will be aninstallation for fusion material testing, that will generate aflux of neutrons of 1018m−2s−1with a broad peak at14 MeV by Li(d,xn) nuclear reactions thanks to a 40 MeV deuteron beam colliding on a liquid Liflow.The accelerator system is in charge of providing such high energy deuterons in order to produce the expectedneutronflux. The High Energy Beam Transport line (HEBT) is the last subsystem of the accelerator and its mainfunctions are to guide the deuteron beam towards the Lithium target and to shape it by the use of magneticelements to the reference beam footprint at the Lithium Target.The present work summarizes the current status of the HEBT design, including beam dynamics, vacuum,radioprotection, diagnostics and remote handling studies performed, along with the layout and integration of theline.This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 and 2019–2020 under grant agreement No 633053. The work done by IREC has been supported by the CERCA Programme from Generalitat de Catalunya (Government of Catalonia).Peer reviewe

Chemical vapour deposition synthetic diamond: materials, technology and applications

Substantial developments have been achieved in the synthesis of chemical vapour deposition (CVD) diamond in recent years, providing engineers and designers with access to a large range of new diamond materials. CVD diamond has a number of outstanding material properties that can enable exceptional performance in applications as diverse as medical diagnostics, water treatment, radiation detection, high power electronics, consumer audio, magnetometry and novel lasers. Often the material is synthesized in planar form, however non-planar geometries are also possible and enable a number of key applications. This article reviews the material properties and characteristics of single crystal and polycrystalline CVD diamond, and how these can be utilized, focusing particularly on optics, electronics and electrochemistry. It also summarizes how CVD diamond can be tailored for specific applications, based on the ability to synthesize a consistent and engineered high performance product.Comment: 51 pages, 16 figure

Anreicherung eines GKV-Datensatzes mit amtlichen Todesursachen über einen Abgleich mit dem Epidemiologischen Krebsregister Nordrhein-Westfalen: Machbarkeitsstudie und Methodenvergleich

ZIEL DER STUDIE: Für die Evaluation von Krebsvorsorgeprogrammen stellen Daten der Gesetzlichen Krankenversicherung (GKV) eine wichtige Datenquelle dar, die jedoch nicht die benötigten Daten zum genauen Sterbedatum und zur Todesursache enthält. Diese Studie sollte prüfen, ob eine diesbezügliche Anreicherung individueller GKV-Daten über einen Abgleich mit einer geeigneten externen Datenquelle erfolgen kann. METHODIK: In der pharmako-epidemiologischen Forschungsdatenbank GePaRD identifizierten wir eine Versichertenstichprobe von 25 528 Frauen, die laut den Angaben in GePaRD im Zeitraum 2006–2013 verstorben waren und ihren Wohnsitz in Nordrhein-Westfalen (NRW) hatten. Datum und Ursache des Todes aller Einwohner von NRW seit 2005 liegen im Epidemiologischen Krebsregister von NRW vor. In Kooperation mit 2 gesetzlichen Krankenkassen wurde mit einem probabilistischen bzw. deterministischen Abgleichverfahren versucht, jeder Verstorbenen der Stichprobe einen Todesfall aus NRW und damit eine Todesursache zuzuordnen. ERGEBNISSE: Für 94,72% der Verstorbenen der Versichertenstichprobe konnte probabilistisch und für 93,36% deterministisch ein Todesfall aus NRW zugeordnet werden. SCHLUSSFOLGERUNG: Das probabilistische und das deterministische Verfahren erreichten vergleichbar hohe Trefferquoten. Nicht erfolgte Zuordnungen sind vermutlich größtenteils auf Fehler bei der Erfassung der Personendaten zurückzuführen. Aufgrund des geringeren technischen Aufwands erscheint das deterministische Verfahren als die Methode der Wahl für die Anreicherung von GKV-Daten mit amtlichen Todesursachen aus geeigneten externen Datenquellen.BACKGROUND: Claims data of the statutory health insurance (SHI) are an important data source for the evaluation of cancer prevention programs. However, this source does not contain relevant information on cause of death. This study examined whether individual claims data can be enriched with data on the required cause of death using record linkage procedures with suitable external data sources. METHODS: In the German pharmacoepidemiologic research database (GePaRD) we identified a sample of 25,528 deceased female residents of North Rhine Westphalia (NRW) who, according to GePaRD information, died between 2006 and 2013. Date and cause of all deaths among inhabitants of NRW since 2005 were available in the epidemiological cancer registry of NRW. In cooperation with 2 SHI companies, we tried to match each individual of the sample with a case of death in NRW and the corresponding cause of death using a probabilistic and, alternatively, a deterministic linkage procedure. RESULTS: Of the study sample, 94.72% were successfully matched by the probabilistic and 93.36% by the deterministic method. CONCLUSIONS: The probabilistic and the deterministic record linkage approach produced comparably high matching rates. Cases without matches are probably due to errors occurring at the stage of personal data entry. Given the lower technical efforts, the deterministic approach appears to be the method of choice for the enrichment of claims data with cause of death information from suitable external data sources in Germany

Small-area spatio-temporal analyses of participation rates in the mammography screening program in the city of Dortmund (NW Germany)

Background 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. Methods 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. Results 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. Conclusion 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