PubMed · 15360040
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Anna M McDaniel, Mollie R Poynton. "Mining" data in public databases.. https://doi.org/10.1097/00002800-200405000-00007
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The Forensic Ear Identification (FearID) research project was started in order to study the strength of evidence of earprints found on crime scenes. For this purpose, a sample of earprints from 1229 donors over three countries was collected. From each donor three left and three right earprints were gathered. On the one hand, operators denoted contours of the earprints to facilitate segmentation of the images, on the other anthropological specialists denoted anatomically specific locations. On the basis of this, methods for automated classification were developed and used for training of a system that classifies pairs of prints as 'matching' or 'non-matching'. Comparing lab quality prints, the system has an equal error rate of 4%. Starting from a reference database containing two prints per ear, hitlist behaviour is such that in 90% of all query searches the best hit is in the top 0.1% of the list. The results become less favourable (equal error rate of 9%) for print/mark comparisons.
PURPOSE: The United Kingdom (UK) government changed the prescription policy of statins, making low-dose simvastatin (10 mg) available as an over-the-counter (OTC) drug in August 2004. We assessed the impact of this policy change on statin prescribing. METHODS: We examined all statin prescriptions in the General Practice Research Database (GPRD), a well-validated database of approximately 3.5 million patients, from the first quarter of 2001 to the second quarter of 2005. RESULTS: From 2001, the number of statin prescriptions written for GPRD patients was increasing by approximately 437 prescriptions per 100,000 people per quarter until the time of the policy change. Over the four quarters post-policy implementation, however, this trend changed abruptly (p < 0.0001) with a decrease of 281 prescriptions per 100,000 people per quarter. This decrease was not restricted to prescriptions of 10 mg statins but was also observed for statin prescriptions of >or=20 mg. Several other cardiovascular medications displayed a similar trend as that observed in the number of statin prescriptions. This trend was not observed among non-cardiovascular control medications. CONCLUSIONS: Our study suggests that the policy allowing the OTC sale of 10 mg simvastatin has had a significant impact on statin prescriptions by general practitioners. However, this new policy may also be leading to less aggressive statin therapy. An alternative explanation for the observed decrease in statin prescriptions may be related to the unknown factors responsible for the overall decrease observed with other cardiovascular prescription drugs.
Post-marketing drug safety data sets are often massive, and entail problems with heterogeneity and selection bias. Nevertheless, quantitative methods have proven a very useful aid to help clinical experts in screening for previously unknown associations in these data sets. The WHO international drug safety database is the world's largest data set of its kind with over three million reports on suspected adverse drug reaction incidents. Since 1998, an exploratory data analysis method has been in routine use to screen for quantitative associations in this data set. This method was originally based on large sample approximations and limited to pairwise associations, but in this article we propose more accurate credibility interval estimates and extend the method to allow for the analysis of more complex quantitative associations. The accuracy of the proposed credibility intervals is evaluated through comparison to precise Monte Carlo simulations. In addition, we propose a Mantel-Haenszel-type adjustment to control for suspected confounders.