Muhammad Younus

The role of exposures to animals and other risk factors in sporadic, non-typhoidal Salmonella infections in Michigan children.

Salmonellosis is largely a major foodborne disease. However, contact with animals particularly reptiles, has been increasingly recognized as a risk factor for Salmonella infection among children. The major risk factors for salmonellosis in Michigan children have not been assessed. Therefore, we have evaluated the association between Salmonella infections and contact with animals among Michigan children aged ≤10 years by conducting a population‐based case–control study. A total of 123 children with laboratory‐confirmed Salmonella infections and 139 control children, who had not experienced symptoms of gastrointestinal illness during the month prior to the interviews, were enrolled. A multivariable analysis matched on age group revealed that children with Salmonella infections had reported more commonly than controls contact with reptiles [adjusted matched odds ratio (MOR) = 7.90, 95% confidence interval (CI): 1.52–41.01] and cats (MOR = 2.53, 95% CI: 1.14–5.88). Results of this study suggest an association between salmonellosis and contact with cats and reptiles in Michigan children. Additional efforts are needed to educate caretakers of young children about the risk of Salmonella transmission through animal contact.

The role of neighborhood level socioeconomic characteristics in Salmonella infections in Michigan (1997-2007): assessment using geographic information system.

Background:The majority of U.S. disease surveillance systems contain incomplete information regarding socioeconomic status (SES) indicators like household or family income and educational attainment in case reports, which reduces the usefulness of surveillance data for these parameters. We investigated the association between select SES attributes at the neighborhood level and Salmonella infections in the three most populated counties in Michigan using a geographic information system.Methods:We obtained data on income, education, and race from the 2000 U.S. Census, and the aggregate number of laboratory-confirmed cases of salmonellosis (1997–2006) at the block group level from the Michigan Department of Community Health. We used ArcGIS to visualize the distribution, and Poisson regression analysis to study associations between potential predictor variables and Salmonella infections.Results:Based on data from 3,419 block groups, our final multivariate model revealed that block groups with lower educational attainment were less commonly represented among cases than their counterparts with higher education levels (< high school degree vs. ≥ college degree: rate ratio (RR) = 0.79, 95% confidence interval (CI):0.63, 0.99; ≥ and high school degree, but no college degree vs. ≥ college degree: RR = 0.84, 95% CI: 0.76, 0.92). Levels of education also showed a dose-response relation with the outcome variable, i.e., decreasing years of education was associated with a decrease in Salmonella infections incidence at the block group level.Conclusion:Education plays a significant role in health-seeking behavior at the population level. It is conceivable that a reporting bias may exist due to a greater detection of Salmonella infections among high education block groups compared to low education block groups resulting from differential access to healthcare. In addition, individuals of higher education block groups who also have greater discretionary income may eat outside the home frequently and be more likely to own pets considered reservoirs of Salmonella, which increase the likelihood of contracting Salmonella infections compared to their counterparts with lower levels of education. Public health authorities should focus on improving the level of disease detection and reporting among communities with lower income and education and further evaluate the role of higher educational attainment in the predisposition for salmonellosis.

Illusions of objectivity and a recommendation for reporting data mining results

ObjectiveData mining algorithms (DMAs) are being applied to spontaneous reporting system (SRS) databases in the hope of obtaining timely insights into post-licensure safety data. Some DMAs have been characterized as “objective” screening tools. However, there are numerous available modifiable configuration parameters to choose from, including choice of vendor, that may affect results. Our objective is to compare the data mining results on pre-selected drug-event combinations (DECs) between two commonly used software programs using similar protocols.MethodsTwo DMAs, using three thresholds, were retrospectively applied to the USFDA safety database through Q2 2005 to a set of eight pre-selected DECs.ResultsDifferences between the two vendors were found for the number of cases associated with a signal of disproportionate reporting (SDR), first year of SDRs, and the magnitude of the SDR scores for the selected DECs. These were deemed to be potentially significant for 45.8% (11/24) of the data points.ConclusionThe observed differences between vendors could partially be explained by their differing methods of data cleaning and transformation as well as by the specific features of individual algorithms. The choices of vendors and available data mining configurations maximize the exploratory capacity of data mining, but they also raise questions about the claimed objectivity of data mining results and can make data mining exercises susceptible to confirmation bias given the exploratory nature of data mining in pharmacovigilance. When reporting results, the vendor and all data mining configuration details should be specified.

Putting the Cardiovascular Safety of Aromatase Inhibitors in Patients with Early Breast Cancer into Perspective

In the adjuvant setting, the third-generation aromatase inhibitors (AIs) anastrozole, letrozole and exemestane are recommended at some point during treatment, either in the upfront, switch after tamoxifen or extended treatment setting after tamoxifen in postmenopausal patients with hormone receptor-positive early breast cancer. AIs have demonstrated superior disease-free survival and overall benefit-to-risk profiles compared with tamoxifen. Potential adverse events, including cardiovascular (CV) side effects, should be considered in the long-term management of patients undergoing treatment with AIs. AIs reduce estrogen levels by inhibiting the aromatase enzyme, thus reducing the levels of circulating estrogen. This further reduction in estrogen levels may potentially increase the risk of developing CV disease.This systematic review evaluated published clinical data for changes in plasma lipoproteins and ischaemic CV events during adjuvant therapy with AIs in patients with hormone receptor-positive early breast cancer. The electronic databases MEDLINE, EMBASE, Derwent Drug File and BIOSIS were searched to identify English-language articles published from January 1998 to 15 April 2011 that reported data on AIs and plasma lipoproteins and/or ischaemic CV events. Overall, available data did not show any definitive patterns or suggest an unfavourable effect of AIs on plasma lipoproteins from baseline to follow-up assessment in patients with hormone receptor-positive early breast cancer. Changes that occurred in plasma lipoproteins were observed soon after initiation of AI therapy and generally remained stable throughout the studies. Available data do not support a substantial risk of ischaemic CV events associated with adjuvant AI therapy; however, studies with longer follow-up are required to better characterize the CV profile of AIs.

Postmarketing hepatic adverse event experience with PEGylated/non-PEGylated drugs: a disproportionality analysis.

Objective To compare reporting frequencies of hepatic adverse events between PEGylated and non-PEGylated formulations of active medicinal compounds in spontaneous reporting systems using a data mining algorithm (DMA). Methods Statistical DMAs are being promoted as a means of identifying drug–event combinations that are disproportionately reported in large spontaneous reporting systems databases, a critical data source for pharmacovigilance. After a review of case reports of hepatotoxicity with PEGylated drugs possibly associated with the polyethylene glycol moiety, we carried out a retrospective disproportionality analysis of WHOs multinational drug safety database for events related to hepatic dysfunction comparing PEGylated versus non-PEGylated formulations of four active moieties. A threshold of posterior interval (PI) 95% lower limit >0 was used to define a signal of disproportionate reporting with a drug and an event and 90% PIs of the information component were compared to identify statistical differences between the two compounds. Results On the basis of a total of 18 477 cases containing at least one of the drug pairs, we found disproportionate reporting for hepatic-related events with both PEGylated and non-PEGylated formulations. Overlapping of 90% PIs of the information components, however, suggested that there was no statistically significant difference between the frequency of hepatic injury reported with PEGylated versus non-PEGylated drug formulations. Conclusion We did not find significant indicators of differential reporting of hepatic injury between PEGylated and non-PEGylated drug formulations in this exploratory analysis using one DMA. The analysis also suggests that comparative disproportionality methodology although not in itself determinative, could be one useful component of a risk management plan for monitoring the postmarketing experience of drug delivery systems that uses multiple methods and data streams.