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Objectives: To describe the epidemiology and geographical differences in prevalence of congenital cerebral anomalies in Europe., Design and Setting: Congenital cerebral anomalies (International Classification of Diseases, 10th Revision code Q04) recorded in 29 population-based EUROCAT registries conducting surveillance of 1.7 million births per annum (29% of all European births)., Participants: All birth outcomes (live births, fetal deaths from 20 weeks gestation and terminations of pregnancy after prenatal diagnosis of a fetal anomaly (TOPFA)) from 2005 to 2014., Main Outcome Measures: Prevalence, proportion of associated non-cerebral anomalies, prenatal detection rate., Results: 4927 cases with congenital cerebral anomalies were identified; a prevalence (adjusted for under-reporting) of 9.8 (95% CI: 8.5 to 11.2) per 10 000 births. There was a sixfold difference in prevalence across the registries. Registries with higher proportions of prenatal diagnoses had higher prevalence. Overall, 55% of all cases were liveborn, 3% were fetal deaths and 41% resulted in TOPFA. Forty-eight per cent of all cases were an isolated cerebral anomaly, 25% had associated non-cerebral anomalies and 27% were chromosomal or part of a syndrome (genetic or teratogenic). The prevalence excluding genetic or chromosomal conditions increased by 2.4% per annum (95% CI: 1.3% to 3.5%), with the increases occurring only for congenital malformations of the corpus callosum (3.0% per annum) and 'other reduction deformities of the brain' (2.8% per annum)., Conclusions: Only half of the cases were isolated cerebral anomalies. Improved prenatal and postnatal diagnosis may account for the increase in prevalence of congenital cerebral anomalies from 2005 to 2014. However, major differences in prevalence remain between regions., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The use of hospital discharge administrative data (HDAD) has been recommended for automating, improving, even substituting, population-based cancer registries. The frequency of false positive and false negative cases recommends local validation., Methods: The aim of this study was to detect newly diagnosed, false positive and false negative cases of cancer from hospital discharge claims, using four Spanish population-based cancer registries as the gold standard. Prostate cancer was used as a case study., Results: A total of 2286 incident cases of prostate cancer registered in 2000 were used for validation. In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5% (CI95% 10.3-19.6) to 45.7% (CI95% 41.4-50.1). In the most predictive algorithm (that using five diagnostic and five surgical codes) Positive Predictive Value estimates ranged from 55.9% (CI95% 42.4-68.8) to 74.3% (CI95% 67.0-80.6). The most frequent reason for false positive cases was the number of prevalent cases inadequately considered as newly diagnosed cancers, ranging from 61.1% to 82.3% of false positive cases. The most frequent reason for false negative cases was related to the number of cases not attended in hospital settings. In this case, figures ranged from 34.4% to 69.7% of false negative cases, in the most predictive algorithm., Conclusions: HDAD might be a helpful tool for cancer registries to reach their goals. The findings suggest that, for automating cancer registries, algorithms combining diagnoses and procedures are the best option. However, for cancer surveillance purposes, in those cancers like prostate cancer in which care is not only hospital-based, combining inpatient and outpatient information will be required.