Tree-based scan statistic - Application in manufacturing-related safety signal detection.

BACKGROUND AND OBJECTIVES: Over the last decades, medicinal regulations have been put into place and have considerably improved manufacturing practices. Nevertheless, safety issues may still arise. Using the simulation described in this manuscript, our aim is to develop adequate detection methods for manufacturing-related safety signals, especially in the context of biological products. METHODS: Pharmaceutical companies record the entire batch genealogies, from seed batches over intermediates to final product (FP) batches. We constructed a hierarchical tree based on this genealogy information and linked it to the spontaneous safety data available for the FP batch numbers. The tree-based scan statistic (TBSS) was used on simulated data as a proof of concept to locate the source that may have subsequently generated an excess of specific adverse events (AEs) within the manufacturing steps, and to evaluate the method's adjustment for multiple testing. All calculations were performed with a customized program in SAS v9.2. RESULTS: The TBSS generated a close to expected number of false positive signals, demonstrating that it adjusted for multiple testing. Overall, the method detected 71% of the simulated signals at the correct production step when a 6-fold increase in reports with AEs of interest (AEOI) was applied, and 31% when a 2-fold increase was applied. The relatively low detection performance may be attributed to the higher granularity associated with the lower levels of the hierarchy, leading to a lack of power and the stringent definition criteria that were applied for a true positive result. CONCLUSION: As a data-mining method for manufacturing-related safety signal detection, the TBSS may provide advantages over other disproportionality analyses (using batch information) but may benefit from complementary methods (not relaying on batch information). While the method warrants further refinement, it may improve safety signal detection and contribute to improvements in the quality of manufacturing processes.

Using time-to-onset for detecting safety signals in spontaneous reports of adverse events following immunization: a proof of concept study.

PURPOSE: Disproportionality analyses (DPA) are widely used in pharmacovigilance for detecting safety signals from spontaneous reports of adverse events. In these analyses, time-to-onset (TTO; the time between vaccination and the onset of the adverse event) is rarely considered. Our objective is to assess the potential use of TTO to improve signal detection (SD). METHODS: Adverse events were defined as signals for a vaccine if the TTO distribution was significantly different from the distribution of other events for the same vaccine and from the distribution obtained with the same event for other vaccines. Distributions were compared within a time window of 30 days by using the two-sample Kolmogorov-Smirnov statistic. With the use of the product label as a proxy of true positive safety signals, TTO SD was compared with a standard DPA method (based on stratified empirical Bayesian geometric mean) for an oral live pediatric vaccine (Rotarix™) and an inactivated adult vaccine (Fluarix™). RESULTS: With the use of the GlaxoSmithKline spontaneous reports database for Rotarix™, 10 Medical Dictionary for Regulatory Activities preferred terms were identified as signals, and among them, five were listed in the product label. The DPA method identified only three preferred terms from the label, that is, TTO SD showed higher sensitivity and specificity. For Fluarix™, TTO SD also showed higher sensitivity but lower specificity. CONCLUSION: This TTO SD method is complementary, conceptually and practically, to more traditional DPA and does not share the major drawback of DPA known as the masking effect. Higher sensitivity and/or specificity can be achieved using TTO SD.

Quantitative signal detection for vaccines: effects of stratification, background and masking on GlaxoSmithKline's spontaneous reports database.

Disproportionality analyses are increasingly gaining acceptance as signal detection tools for drug adverse events. Their application to vaccine adverse events has not been well evaluated. Disproportionality analyses based on the Multi-Item Gamma Poisson Shrinkage principle (MGPS) were applied to spontaneous adverse events reports for five vaccines with different reporting profiles. Sensitivity analyses were used to assess the potential impact of changing key parameters. We used the Company's in-house spontaneous adverse events database. We evaluated the impact of stratification, the comparator dataset and the potential for masking. We conducted a semi-quantitative assessment by comparing the changes in the disproportionality scores and the number of vaccine-event pairs that exceeded an arbitrary threshold as a measure of the impact of any of these choices. The results show that stratification by age and region has a significant impact. The effect of the comparator dataset was dependent on the vaccine being evaluated. The potential for a masking effect was only weakly noticeable. In conclusion, we opt to start with a conservative approach in which we will supplement our primary stratification against the vaccine database with unstratified analyses as well as analyses against the entire database. We recommend that similar studies be performed before introducing disproportionality analyses to a new vaccine adverse events database.

Glucose and pharmacological modulators of ATP-sensitive K+ channels control [Ca2+]c by different mechanisms in isolated mouse alpha-cells.

OBJECTIVE: We studied how glucose and ATP-sensitive K(+) (K(ATP)) channel modulators affect alpha-cell [Ca(2+)](c). RESEARCH DESIGN AND METHODS: GYY mice (expressing enhanced yellow fluorescent protein in alpha-cells) and NMRI mice were used. [Ca(2+)](c), the K(ATP) current (I(KATP), perforated mode) and cell metabolism [NAD(P)H fluorescence] were monitored in single alpha-cells and, for comparison, in single beta-cells. RESULTS: In 0.5 mmol/l glucose, [Ca(2+)](c) oscillated in some alpha-cells and was basal in the others. Increasing glucose to 15 mmol/l decreased [Ca(2+)](c) by approximately 30% in oscillating cells and was ineffective in the others. alpha-Cell I(KATP) was inhibited by tolbutamide and activated by diazoxide or the mitochondrial poison azide, as in beta-cells. Tolbutamide increased alpha-cell [Ca(2+)](c), whereas diazoxide and azide abolished [Ca(2+)](c) oscillations. Increasing glucose from 0.5 to 15 mmol/l did not change I(KATP) and NAD(P)H fluorescence in alpha-cells in contrast to beta-cells. The use of nimodipine showed that L-type Ca(2+) channels are the main conduits for Ca(2+) influx in alpha-cells. gamma-Aminobutyric acid and zinc did not decrease alpha-cell [Ca(2+)](c), and insulin, although lowering [Ca(2+)](c) very modestly, did not affect glucagon secretion. CONCLUSIONS: alpha-Cells display similarities with beta-cells: K(ATP) channels control Ca(2+) influx mainly through L-type Ca(2+) channels. However, alpha-cells have distinct features from beta-cells: Most K(ATP) channels are already closed at low glucose, glucose does not affect cell metabolism and I(KATP), and it slightly decreases [Ca(2+)](c). Hence, glucose and K(ATP) channel modulators exert distinct effects on alpha-cell [Ca(2+)](c). The direct small glucose-induced drop in alpha-cell [Ca(2+)](c) contributes likely only partly to the strong glucose-induced inhibition of glucagon secretion in islets.

Restoration of an impaired TGF-beta1 autocrine growth-inhibitory circuit results in growth inhibition of ovarian epithelial cancer cells and complete inhibition of their tumorigenicity.

The disruption of the transforming growth factor beta1 (TGF-beta1) autocrine growth-suppressive circuit is a major and possibly early event mediating the malignant transformation of normal epithelia. TGF-beta1 is secreted as a latent homodimer-peptide that, upon activation, binds a receptor complex. This in turn activates a signal transduction cascade that results in proliferation inhibition of epithelial cells. The growth-inhibitory pathway can be interrupted at several levels: insufficient secretion and activation of TGF-beta1 ligand, mutational inactivation of the receptors or signal transduction intermediates or at the level of the nuclear effector molecules. We have investigated the effect of restoring the growth-inhibitory autocrine circuit in epithelial cancer cells that have retained sensitivity to growth inhibition by TGF-beta1 but which produce and secrete insufficient amounts of endogenous peptide. These cancer cells were transduced with a recombinant adenovirus containing a TGF-beta1 cDNA driven by a CMV promoter and coding for a constitutively bioactive TGF-beta1 peptide. Restituting the TGF-beta1 autocrine growth-suppressive circuit in these cancer cells had a potent growth-inhibitory effect in vitro. Moreover, in vitro transduced cells lost their tumorigenicity in nude mice. As disruption of TGF-beta's autocrine growth circuit is thought to be an early event in the malignant transformation of several epithelial cancers, early correction of this defect might in the future lead to cancer preventive strategies.